Publications

The contractile nature of skeletal muscle tissue makes it especially attractive for powering biohybrid actuators. Significant efforts have been dedicated to the improvement and control of contraction force, going one step forward toward the automation of these biohybrid platforms. Herein, 3D-bioengineered skeletal muscle tissues are integrated with organic transistor-based sensors to define a soft bioactuator with real-time force monitoring capabilities. The muscle tissue is electrically stimulated while the organic sensor ensures transduction of the exerted force into an electrical signal that allows direct monitoring of the bioactuator performance. Sensor calibration is carried out to define its sensitivity at different biasing conditions: as opposed to standard, two-terminal piezoresistive devices, transistor-based strain sensors show tunable sensitivity by acting on the voltage applied to a third terminal-the gate. A complete evaluation of sensing performances is provided, demonstrating that real-time monitoring is effective under different conditions, including stimulation signal frequency and chemical modulation of the bioactuator contraction, demonstrating its potential use as a drug testing platform. In the reported results, the way is paved for a complete exploitation of organic devices in soft robotic applications and to the development of novel biohybrid machines in bioengineering and biomedicine. The integration of sensing elements in bioengineered actuators is key to obtain real-time information about their performance and further control/automation. By coupling flexible organic field-effect transistor to a skeletal muscle actuator we demonstrate the feasibility to record in real-time its contractile behavior when stimulated by electrical pulses, showing both high sensitivity absence of cross talk between stimulation and readout.image (c) 2024 WILEY-VCH GmbH

JTD Keywords: Bioengineerings, Flexible electronics, Muscle-based actuators, Organic field-effect transistors, Soft robotic

Over the past decades, the development of nanoparticles (NPs) to increase the efficiency of clinical treatments has been subject of intense research. Yet, most NPs have been reported to possess low efficacy as their actuation is hindered by biological barriers. For instance, synovial fluid (SF) present in the joints is mainly composed of hyaluronic acid (HA). These viscous media pose a challenge for many applications in nanomedicine, as passive NPs tend to become trapped in complex networks, which reduces their ability to reach the target location. This problem can be addressed by using active NPs (nanomotors, NMs) that are self-propelled by enzymatic reactions, although the development of enzyme-powered NMs, capable of navigating these viscous environments, remains a considerable challenge. Here, the synergistic effects of two NMs troops, namely hyaluronidase NMs (HyaNMs, Troop 1) and urease NMs (UrNMs, Troop 2) are demonstrated. Troop 1 interacts with the SF by reducing its viscosity, thus allowing Troop 2 to swim more easily through the SF. Through their collective motion, Troop 2 increases the diffusion of macromolecules. These results pave the way for more widespread use of enzyme-powered NMs, e.g., for treating joint injuries and improving therapeutic effectiveness compared with traditional methods. The conceptual idea of the novel approach using hyaluronidase NMs (HyaNMs) to interact with and reduce the viscosity of the synovial fluid (SF) and urease NMs (UrNMs) for a more efficient transport of therapeutic agents in joints.image

JTD Keywords: Biological barrier, Clinical research, Clinical treatments, Collective motion, Collective motion,nanomotors,nanorobots,swarming,viscous medi, Collective motions, Complex networks, Enzymatic reaction, Enzymes, Hyaluronic acid, Hyaluronic-acid,ph,viscoelasticity,adsorption,barriers,behavior,ureas, Macromolecules, Medical nanotechnology, Nano robots, Nanomotors, Nanorobots, Swarming, Synovial fluid, Target location, Viscous media, Viscous medium

Cell membrane potential affects the electrostatic self-assembly of magnetizable nanoparticles around the flagellum of sperm cells, leading to the formation of biohybrid microrobots (i.e., IRONSperm) with various bending stiffness. Here we explain the influence of bull sperm cell membrane potential on the formation of two types of IRONSperm samples that are produced by electrostatic self-assembly. The first type is a proximal-coated soft body with nanoparticles concentrated on the head to maintain high flexibility of the flagellum and create a passively propagating transverse bending wave under the influence of an external rotating magnetic field. The second type is a rigid-body with nanoparticles approximately uniformly distributed along the length to provide arbitrary geometry that maintains a constant chiral shape and propel by rotation about its long axis. We present a magneto-elastohydrodynamic model to predict the swimming speed at low Reynolds number for rigid IRONSperm with arbitrary shapes, and show that decreasing the bending stiffness allows the model to capture the behavior of its soft counterpart. While the response of a rigid chiral IRONSperm is distinguished by a greater swimming speed with a smooth decay with frequency, the benefit of a soft flagellum in certain scenarios would present a much smaller range of frequencies for wireless actuation.

JTD Keywords: Biohybrid, Magnetic, Microrobots, Nanoparticles, Propulsion, Sperm cells

JTD Keywords: coverage path planning (cpp), gas distribution map (gdm), gas source localization (gsl), metal oxide semiconductor sensor, quality, robot, system, Nano-quadcopter, Source localization

(1) Background: Restoring arm and hand function is a priority for individuals with cervical spinal cord injury (cSCI) for independence and quality of life. Transcutaneous spinal cord stimulation (tSCS) promotes the upper extremity (UE) motor function when applied at the cervical region. The aim of the study was to determine the effects of cervical tSCS, combined with an exoskeleton, on motor strength and functionality of UE in subjects with cSCI. (2) Methods: twenty-two subjects participated in the randomized mix of parallel-group and crossover clinical trial, consisting of an intervention group (n = 15; tSCS exoskeleton) and a control group (n = 14; exoskeleton). The assessment was carried out at baseline, after the last session, and two weeks after the last session. We assessed graded redefined assessment of strength, sensibility, and prehension (GRASSP), box and block test (BBT), spinal cord independence measure III (SCIM-III), maximal voluntary contraction (MVC), ASIA impairment scale (AIS), and WhoQol-Bref; (3) Results: GRASSP, BBT, SCIM III, cylindrical grip force and AIS motor score showed significant improvement in both groups (p ≤ 0.05), however, it was significantly higher in the intervention group than the control group for GRASSP strength, and GRASSP prehension ability (p ≤ 0.05); (4) Conclusion: our findings show potential advantages of the combination of cervical tSCS with an exoskeleton to optimize the outcome for UE.

JTD Keywords: arm function, cervical spinal cord injury, electrical-stimulation, functional walking, functionality, grip force, hand function, individuals, injury, motor function, reliability, robotics, spasticity, transcutaneous electrical spinal cord stimulation, upper extremity, Epidural stimulation, Transcutaneous electrical spinal cord stimulation, Upper extremity

Biohybrid robots, or bio-bots, integrate living and synthetic materials following a synergistic strategy to acquire some of the unique properties of biological organisms, like adaptability or bio-sensing, which are difficult to obtain exclusively using artificial materials. Skeletal muscle is one of the preferred candidates to power bio-bots, enabling a wide variety of movements from walking to swimming. Conductive nanocomposites, like gold nanoparticles or graphene, can provide benefits to muscle cells by improving the scaffolds' mechanical and conductive properties. Here, boron nitride nanotubes (BNNTs), with piezoelectric properties, are integrated in muscle-based bio-bots and an improvement in their force output and motion speed is demonstrated. A full characterization of the BNNTs is provided, and their piezoelectric behavior with piezometer and dynamometer measurements is confirmed. It is hypothesized that the improved performance is a result of an electric field generated by the nanocomposites due to stresses produced by the cells during differentiation. This hypothesis is backed with finite element simulations supporting that this stress can generate a non-zero electric field within the matrix. With this work, it is shown that the integration of nanocomposite into muscle-based bio-bots can improve their performance, paving the way toward stronger and faster bio-hybrid robots.

JTD Keywords: Bio-bots, Biohybrid robots, Biomaterials, Boron nitride nanotubes, Cells, Cytotoxicity, Differentiation, Myoblasts, Skeletal muscle tissue, Skeletal-muscle, Stimulation

A variety of wound healing platforms have been proposed to alleviate the hypoxic condition and/or to modulate the immune responses for the treatment of chronic wounds in diabetes. However, these platforms with the passive diffusion of therapeutic agents through the blood clot result in the relatively low delivery efficiency into the deep wound site. Here, a microalgae-based biohybrid microrobot for accelerated diabetic wound healing is developed. The biohybrid microrobot autonomously moves at velocity of 33.3 µm s-1 and generates oxygen for the alleviation of hypoxic condition. In addition, the microrobot efficiently bound with inflammatory chemokines of interleukin-8 (IL-8) and monocyte chemoattractant protein-1 (MCP-1) for modulating the immune responses. The enhanced penetration of microrobot is corroborated by measuring fibrin clots in biomimetic wound using microfluidic devices and the enhanced retention of microrobot is confirmed in the real wounded mouse skin tissue. After deposition on the chronic wound in diabetic mice without wound dressing, the wounds treated with microrobots are completely healed after 9 days with the significant decrease of inflammatory cytokines below 31% of the control level and the upregulated angiogenesis above 20 times of CD31+ cells. These results confirm the feasibility of microrobots as a next-generation platform for diabetic wound healing.© 2022 Wiley-VCH GmbH.

JTD Keywords: biohybrid, microrobots, polyions, wound healing, Algae, Biohybrid, Chemokines, Microrobots, Polyions, Wound healing

Individual biohybrid microrobots have the potential to perform biomedical in vivo tasks such as remote-controlled drug and cell delivery and minimally invasive surgery. This work demonstrates the formation of biohybrid sperm-templated clusters under the influence of an external magnetic field and essential functionalities for wireless actuation and drug delivery. Ferromagnetic nanoparticles are electrostatically assembled around dead sperm cells, and the resulting nanoparticle-coated cells are magnetically assembled into three-dimensional biohybrid clusters. The aim of this clustering is threefold: First, to enable rolling locomotion on a nearby solid boundary using a rotating magnetic field; second, to allow for noninvasive localization; third, to load the cells inside the cluster with drugs for targeted therapy. A magneto-hydrodynamic model captures the rotational response of the clusters in a viscous fluid, and predicts an upper bound for their step-out frequency, which is independent of their volume or aspect ratio. Below the step-out frequency, the rolling velocity of the clusters increases nonlinearly with their perimeter and actuation frequency. During rolling locomotion, the clusters are localized using ultrasound images at a relatively large distance, which makes these biohybrid clusters promising for deep-tissue applications. Finally, we show that the estimated drug load scales with the number of cells in the cluster and can be retained for more than 10 h. The aggregation of microrobots enables them to collectively roll in a predictable way in response to an external rotating magnetic field, and enhances ultrasound detectability and drug loading capacity compared to the individual microrobots. The favorable features of biohybrid microrobot clusters place emphasis on the importance of the investigation and development of collective microrobots and their potential for in vivo applications.

JTD Keywords: drug delivery, magnetic actuation, microrobot aggregation, sperm, Driven, Drug delivery, Magnetic actuation, Magnetotactic bacteria, Microrobot aggregation, Microrobots, Motion, Movement, Propulsion, Sperm, Sphere, Ultrasound, Wall

JTD Keywords: coordination, embodied cognition, human-robot interaction, sensorimotor coupling, Coordination, Embodied cognition, Human-robot interaction, Sensorimotor coupling, Social cognition

The presence of organic pollutants in the environment is a global threat to human health and ecosystems due to their bioaccumulation and long-term persistence. Hereby a micromotor-in-sponge concept is presented that aims not only at pollutant removal, but towards an efficient in situ degradation by exploiting the synergy between the sponge hydrophobic nature and the rapid pollutant degradation promoted by the cobalt-ferrite (CFO) micromotors embedded at the sponge's core. Such a platform allows the use of extremely low fuel concentration (0.13% H2 O2 ), as well as its reusability and easy recovery. Moreover, the authors demonstrate an efficient multicycle pollutant degradation and treatment of large volumes (1 L in 15 min) by using multiple sponges. Such a fast degradation process is due to the CFO bubble-propulsion motion mechanism, which induces both an enhanced fluid mixing within the sponge and an outward flow that allows a rapid fluid exchange. Also, the magnetic control of the system is demonstrated, guiding the sponge position during the degradation process. The micromotor-in-sponge configuration can be extrapolated to other catalytic micromotors, establishing an alternative platform for an easier implementation and recovery of micromotors in real environmental applications.© 2022 Wiley-VCH GmbH.

JTD Keywords: effective removal, fabrication, microbots, microjets, organic pollutants, propelled micromotors, self-propelled micromotors, sponges, water treatment, Oil-water separation, Organic pollutants, Water treatment

© 2021 Wiley Periodicals LLC. Biohybrid robotics is a field in which biological entities are combined with artificial materials in order to obtain improved performance or features that are difficult to mimic with hand-made materials. Three main level of integration can be envisioned depending on the complexity of the biological entity, ranging from the nanoscale to the macroscale. At the nanoscale, enzymes that catalyze biocompatible reactions can be used as power sources for self-propelled nanoparticles of different geometries and compositions, obtaining rather interesting active matter systems that acquire importance in the biomedical field as drug delivery systems. At the microscale, single enzymes are substituted by complete cells, such as bacteria or spermatozoa, whose self-propelling capabilities can be used to transport cargo and can also be used as drug delivery systems, for in vitro fertilization practices or for biofilm removal. Finally, at the macroscale, the combinations of millions of cells forming tissues can be used to power biorobotic devices or bioactuators by using muscle cells. Both cardiac and skeletal muscle tissue have been part of remarkable examples of untethered biorobots that can crawl or swim due to the contractions of the tissue and current developments aim at the integration of several types of tissue to obtain more realistic biomimetic devices, which could lead to the next generation of hybrid robotics. Tethered bioactuators, however, result in excellent candidates for tissue models for drug screening purposes or the study of muscle myopathies due to their three-dimensional architecture. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

JTD Keywords: bacteria-bots, based biorobots, biorobots, bots, enzymatic nanomotors, hybrid robotics, muscle‐, Bacteria‐, Bacteria-bots, Biorobots, Enzymatic nanomotors, Hybrid robotics, Muscle-based biorobots

Bioinspired hybrid soft robots that combine living and synthetic components are an emerging field in the development of advanced actuators and other robotic platforms (i.e., swimmers, crawlers, and walkers). The integration of biological components offers unique characteristics that artificial materials cannot precisely replicate, such as adaptability and response to external stimuli. Here, we present a skeletal muscle–based swimming biobot with a three-dimensional (3D)–printed serpentine spring skeleton that provides mechanical integrity and self-stimulation during the cell maturation process. The restoring force inherent to the spring system allows a dynamic skeleton compliance upon spontaneous muscle contraction, leading to a cyclic mechanical stimulation process that improves the muscle force output without external stimuli. Optimization of the 3D-printed skeletons is carried out by studying the geometrical stiffnesses of different designs via finite element analysis. Upon electrical actuation of the muscle tissue, two types of motion mechanisms are experimentally observed: directional swimming when the biobot is at the liquid-air interface and coasting motion when it is near the bottom surface. The integrated compliant skeleton provides both the mechanical self-stimulation and the required asymmetry for directional motion, displaying its maximum velocity at 5 hertz (800 micrometers per second, 3 body lengths per second). This skeletal muscle–based biohybrid swimmer attains speeds comparable with those of cardiac-based biohybrid robots and outperforms other muscle-based swimmers. The integration of serpentine-like structures in hybrid robotic systems allows self-stimulation processes that could lead to higher force outputs in current and future biomimetic robotic platforms. Copyright © 2021 The Authors, some rights reserved;

JTD Keywords: actuators, design, fabrication, mechanics, mems, myotubes, platform, tissue, 3d printers, Agricultural robots, Biological components, Biomimetic processes, Electrical actuation, Geometrical stiffness, Intelligent robots, Liquefied gases, Liquid-air interface, Mechanical integrity, Mechanical stimulation, Muscle, Muscle contractions, Phase interfaces, Robotics, Serpentine, Springs (components), Threedimensional (3-d)

© 2021 The Authors. Advanced Science published by Wiley-VCH GmbH Technical design features for improving the way a passive elastic filament produces propulsive thrust can be understood by analyzing the deformation of sperm-templated microrobots with segmented magnetization. Magnetic nanoparticles are electrostatically self-assembled on bovine sperm cells with nonuniform surface charge, producing different categories of sperm-templated microrobots. Depending on the amount and location of the nanoparticles on each cellular segment, magnetoelastic and viscous forces determine the wave pattern of each category during flagellar motion. Passively propagating waves are induced along the length of these microrobots using external rotating magnetic fields and the resultant wave patterns are measured. The response of the microrobots to the external field reveals distinct flow fields, propulsive thrust, and frequency responses during flagellar propulsion. This work allows predictions for optimizing the design and propulsion of flexible magnetic microrobots with segmented magnetization.

JTD Keywords: biohybrid microrobots, flagellar propulsion, magnetic actuation, nanoparticles, sperm cells, Biohybrid microrobots, Flagellar propulsion, Magnetic actuation, Nanoparticles, Sperm cells

Enzyme-powered nanomotors are an exciting technology for biomedical applications due to their ability to navigate within biological environments using endogenous fuels. However, limited studies into their collective behavior and demonstrations of tracking enzyme nanomotors in vivo have hindered progress toward their clinical translation. Here, we report the swarming behavior of urease-powered nanomotors and its tracking using positron emission tomography (PET), both in vitro and in vivo. For that, mesoporous silica nanoparticles containing urease enzymes and gold nanoparticles were used as nanomotors. To image them, nanomotors were radiolabeled with either I on gold nanoparticles or F-labeled prosthetic group to urease. In vitro experiments showed enhanced fluid mixing and collective migration of nanomotors, demonstrating higher capability to swim across complex paths inside microfabricated phantoms, compared with inactive nanomotors. In vivo intravenous administration in mice confirmed their biocompatibility at the administered dose and the suitability of PET to quantitatively track nanomotors in vivo. Furthermore, nanomotors were administered directly into the bladder of mice by intravesical injection. When injected with the fuel, urea, a homogeneous distribution was observed even after the entrance of fresh urine. By contrast, control experiments using nonmotile nanomotors (i.e., without fuel or without urease) resulted in sustained phase separation, indicating that the nanomotors’ self-propulsion promotes convection and mixing in living reservoirs. Active collective dynamics, together with the medical imaging tracking, constitute a key milestone and a step forward in the field of biomedical nanorobotics, paving the way toward their use in theranostic applications. 124 18

JTD Keywords: cell, reversal, silica nanoparticles, size, step, transport, Administration, intravesical, Animals, Equipment design, Female, Gold, Metal nanoparticles, Mice, Mice, inbred c57bl, Motion, Phantoms, imaging, Positron emission tomography computed tomography, Precision medicine, Propelled micromotors, Robotics, Translational research, biomedical, Urease, Urinary bladder

© 2020 Wiley-VCH GmbH In recent years, magnetism has gained an enormous amount of interest among researchers for actuating different sizes and types of bio/soft robots, which can be via an electromagnetic-coil system, or a system of moving permanent magnets. Different actuation strategies are used in robots with magnetic actuation having a number of advantages in possible realization of microscale robots such as bioinspired microrobots, tetherless microrobots, cellular microrobots, or even normal size soft robots such as electromagnetic soft robots and medical robots. This review provides a summary of recent research in magnetically actuated bio/soft robots, discussing fabrication processes and actuation methods together with relevant applications in biomedical area and discusses future prospects of this way of actuation for possible improvements in performance of different types of bio/soft robots.

JTD Keywords: capsule endoscope, controlled propulsion, conventional gastroscopy, digital microfluidics, guided capsule, liquid-metal, magnetic drug delivery, magnetic microrobots, magnetically guided capsule endoscopy, magnetotactic bacteria, nanoscribe ip-dip, navigation system, Gallium-indium egain, Magnetic bioinspired micromanipulation, Magnetic drug delivery, Magnetic microrobots, Magnetically guided capsule endoscopy, Magnetotactic bacteria

Animals in their ecological context behave not only in response to external events, such as opportunities and threats but also according to their internal needs. As a result, the survival of the organism is achieved through regulatory behaviour. Although homeostatic and allostatic principles play an important role in such behaviour, how an animal's brain implements these principles is not fully understood yet. In this paper, we propose a new model of regulatory behaviour inspired by the functioning of the medial Reticular Formation (mRF). This structure is spread throughout the brainstem and has shown generalized Central Nervous System (CNS) arousal control and fundamental action-selection properties. We propose that a model based on the mRF allows the flexibility needed to be implemented in diverse domains, while it would allow integration of other components such as place cells to enrich the agent's performance. Such a model will be implemented in a mobile robot that will navigate replicating the behaviour of the sand-diving lizard, a benchmark for regulatory behaviour. © 2020 Elsevier B.V.. All rights reserved.

JTD Keywords: Action selection, Allostasi, Allostasis, Animal brain, Animals, Behavior-based, Brainstem, Central nervous systems, Cognitive architecture, Cognitive architectures, Elsevier, Homeostasis, Homoeostasis, Magnetorheological fluids, Regulatory behavior, Regulatory behaviour, Reticular formation, Robots

This paper describes the design of a linear phase low-pass differentiator filter with a finite impulse response (FIR) for extracting transient features of gas sensor signals (the so-called “bouts”). The detection of these bouts is relevant for estimating the distance of a gas source in a turbulent plume. Our current proposal addresses the shortcomings of previous ‘bout’ estimation methods, namely: (i) they were based in non-causal digital filters precluding real time operation, (ii) they used non-linear phase filters leading to waveform distortions and (iii) the smoothing action was achieved by two filters in cascade, precluding an easy tuning of filter performance. The presented method is based on a low-pass FIR differentiator, plus proper post-processing, allowing easy algorithmic implementation for real-time robotic exploration. Linear phase filters preserve signal waveform in the bandpass region for maximum reliability concerning both ‘bout’ detection and amplitude estimation. As a case study, we apply the proposed filter to predict the source distance from recordings obtained with metal oxide (MOX) gas sensors in a wind tunnel. We first perform a joint optimization of the cut-off frequency of the filter and the bout amplitude threshold, for different wind speeds, uncovering interesting relationships between these two parameters. We demonstrate that certain combinations of parameters can reduce the prediction error to 8 cm (in a distance range of 1.45 m) improving previously reported performances in the same dataset by a factor of 2.5. These results are benchmarked against traditional source distance estimators such as the mean, variance and maximum of the response. We also study how the length of the measurement window affects the performance of different signal features, and how to select the filter parameters to make the predictive models more robust to changes in wind speed. Finally, we provide a MATLAB implementation of the bout detection algorithm and all analysis code used in this study.

JTD Keywords: Gas sensors, Differentiator, Low pass filter, Metal oxide semiconductor, MOX sensors, Signal processing, Feature extraction, Gas source localization, Robotics

The difficulty to obtain ground truth (i.e. empirical evidence) about how a gas disperses in an environment is one of the major hurdles in the field of mobile robotic olfaction (MRO), impairing our ability to develop efficient gas source localization strategies and to validate gas distribution maps produced by autonomous mobile robots. Previous ground truth measurements of gas dispersion have been mostly based on expensive tracer optical methods or 2D chemical sensor grids deployed only at ground level. With the ever-increasing trend towards gas-sensitive aerial robots, 3D measurements of gas dispersion become necessary to characterize the environment these platforms can explore. This paper presents ten different experiments performed with a 3D grid of 27 metal oxide semiconductor (MOX) sensors to visualize the temporal evolution of gas distribution produced by an evaporating ethanol source placed at different locations in an office room, including variations in height, release rate and air flow. We also studied which features of the MOX sensor signals are optimal for predicting the source location, considering different lengths of the measurement window. We found strongly time-varying and counter-intuitive gas distribution patterns that disprove some assumptions commonly held in the MRO field, such as that heavy gases disperse along ground level. Correspondingly, ground-level gas distributions were rarely useful for localizing the gas source and elevated measurements were much more informative. We make the dataset and the code publicly available to enable the community to develop, validate, and compare new approaches related to gas sensing in complex environments.

JTD Keywords: Mobile robotic olfaction, Metal oxide gas sensors, Signal processing, Sensor networks, Gas source localization, Gas distribution mapping

Metal Oxide (MOX) gas sensors rely on chemical reactions that occur efficiently at high temperatures, resulting in too-demanding power requirements for certain applications. Operating the sensor under a Pulsed-Temperature Operation (PTO), by which the sensor heater is switched ON and OFF periodically, is a common practice to reduce the power consumption. However, the sensor performance is degraded as the OFF periods become larger. Other research works studied, generally, PTO schemes applying waveforms to the heater with time periods of seconds and duty cycles above 20%. Here, instead, we explore the behaviour of PTO sensors working under aggressive schemes, reaching power savings of 99% and beyond with respect to continuous heater stimulation. Using sensor sensitivity and the limit of detection, we evaluated four Ultra Low Power (ULP) sensors under different PTO schemes exposed to ammonia, ethylene, and acetaldehyde. Results show that it is possible to operate the sensors with total power consumption in the range of microwatts. Despite the aggressive power reduction, sensor sensitivity suffers only a moderate decline and the limit of detection may degrade up to a factor five. This is, however, gas-dependent and should be explored on a case-by-case basis since, for example, the same degradation has not been observed for ammonia. Finally, the run-in time, i.e., the time required to get a stable response immediately after switching on the sensor, increases when reducing the power consumption, from 10 minutes to values in the range of 10–20 hours for power consumptions smaller than 200 microwatts.

JTD Keywords: Robot sensing systems, Temperature sensors, Heating systems, Gas detectors, Power demand, Sensitivity, Electronic nose, gas sensors, low-power operation, machine olfaction, pulsed-temperature operation, temperature modulation

Learning programming and robotics offers the opportunity to practice problem-solving, creativity, and team-work and it provides important competencies to train for the 21st century. However, programming can be challenging, and children may encounter difficulties in learning the syntax or using the coding environment. To address this issue, we have developed a methodology for teaching programming, design and robotics based on inquiry-based learning and hands-on oriented activities together with visual programming. We have applied and evaluated this new methodology within the extracurricular activity of an international elementary school in Barcelona. Our findings showed acquisition and learning of technical language, understanding of electronics devices, understanding the mapping of coding into action via the robot’s behavior. This suggests that our approach is a valid and effective teaching methodology for the instructional design of robotics and programming.

JTD Keywords: Educational technology, Instructional design, Robotics

In the past decade, society has experienced notable growth in a variety of technological areas. However, the Fourth Industrial Revolution has not been embraced yet. Industry 4.0 imposes several challenges which include the necessity of new architectural models to tackle the uncertainty that open environments represent to cyber-physical systems (CPS). Waste Electrical and Electronic Equipment (WEEE) recycling plants stand for one of such open environments. Here, CPSs must work harmoniously in a changing environment, interacting with similar and not so similar CPSs, and adaptively collaborating with human workers. In this paper, we support the Distributed Adaptive Control (DAC) theory as a suitable Cognitive Architecture for managing a recycling plant. Specifically, a recursive implementation of DAC (between both single-agent and large-scale levels) is proposed to meet the expected demands of the European Project HR-Recycler. Additionally, with the aim of having a realistic benchmark for future implementations of the recursive DAC, a micro-recycling plant prototype is presented.

JTD Keywords: Cognitive architecture, Distributed Adaptive Control, Recycling plant, Navigation, Motor control, Human-Robot Interaction

We present a new computational framework for modeling moral decision-making in artificial agents based on the notion of ‘Machine Morality as Cooperation’. This framework integrates recent advances from cross-disciplinary moral decision-making literature into a single architecture. We build upon previous work outlining cognitive elements that an artificial agent would need for exhibiting latent morality, and we extend it by providing a computational realization of the cognitive architecture of such an agent. Our work has implications for cognitive and social robotics. Recent studies in human neuroimaging have pointed to three different decision-making processes, Pavlovian, model-free and model-based, that are defined by distinct neural substrates in the brain. Here, we describe how computational models of these three cognitive processes can be implemented in a single cognitive architecture by using the distributed and hierarchical organization proposed by the DAC theoretical framework. Moreover, we propose that a pro-social drive to cooperate exists at the Pavlovian level that can also bias the rest of the decision system, thus extending current state-of-the-art descriptive models based on harm-aversion.

JTD Keywords: Morality, Moral decision-making, Computational models, Cognitive architectures, Cognitive robotics, Human-robot interaction

Low-cost gas sensors allow for large-scale spatial monitoring of air quality in the environment. However they require calibration before deployment. Methods such as multivariate regression techniques have been applied towards sensor calibration. In this work, we propose instead, the use of deep learning methods, particularly, recurrent neural networks for predicting the gas concentrations based on the outputs of these sensors. This paper presents a first study of using Gated Recurrent Unit (GRU) neural network models for gas concentration prediction. The GRU networks achieve on average, a 44.69% and a 25.17% RMSE improvement in concentration prediction on a gas dataset when compared with Support Vector Regression (SVR) and Multilayer Perceptron (MLP) models respectively. With the current advances in deep network hardware accelerators, these networks can be combined with the sensors for a compact embedded system suitable for edge applications.

JTD Keywords: Robot sensing systems, Predictive models, Logic gates, Gas detectors, Training, Temperature measurement, Support vector machines

This pilot study investigates the role of social sensorimotor contingencies as exhibited from a humanoid robot to allow mutual understanding and social entrainment in a group social activity. The goal is to evaluate whether sensorimotor contingencies can lead to transparent and understandable interactions while we explore the dimension of personality. We propose the task of taking a selfie with a robot and a group of humans as the benchmark to evaluate the social sensorimotor contingencies displayed. We have constructed two models of interaction with an introverted and extroverted robot. We also seek to address the gap in research in context and personality of social sensorimotor contingencies in HRI and contribute to the field of personality in social robotics by determining what type of behaviour of the robot attracts certain personalities in humans in group settings. Although the sample size was small, and there were no significant differences between conditions, results suggest that the expression of sensorimotor contingencies can lead to successful coupling and interactions.

JTD Keywords: Human-robot interaction, Personality, Social robots, Social sensorimotor contingencies

This book constitutes the proceedings of the )th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020, held in Freiburg, Germany, in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 32 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Soft robotics, Biomimetics, Insect navigation, Synthetic nervous system, Computer vision, Bio-inspired materials, Visual homing, Locomotion+, Image processing, Intelligent robots, Human-robot interaction, Machine learning, Snake robot, Mobile robots, Robotic systems, Drosophila, Robots, Sensors, Signal processing

This paper proposes the application of a low-cost gas sensor array in an assistant personal robot (APR) in order to extend the capabilities of the mobile robot as an early gas leak detector for safety purposes. The gas sensor array is composed of 16 low-cost metal-oxide (MOX) gas sensors, which are continuously in operation. The mobile robot was modified to keep the gas sensor array always switched on, even in the case of battery recharge. The gas sensor array provides 16 individual gas measurements and one output that is a cumulative summary of all measurements, used as an overall indicator of a gas concentration change. The results of preliminary experiments were used to train a partial least squares discriminant analysis (PLS-DA) classifier with air, ethanol, and acetone as output classes. Then, the mobile robot gas leak detection capabilities were experimentally evaluated in a public facility, by forcing the evaporation of (1) ethanol, (2) acetone, and (3) ethanol and acetone at different locations. The positive results obtained in different operation conditions over the course of one month confirmed the early detection capabilities of the proposed mobile system. For example, the APR was able to detect a gas leak produced inside a closed room from the external corridor due to small leakages under the door induced by the forced ventilation system of the building.

JTD Keywords: Metal-oxide semiconductor, Gas sensor, Gas leak detection, Assistant personal robot, Mobile robot

This paper describes the development and validation of the currently smallest aerial platform with olfaction capabilities. The developed Smelling Nano Aerial Vehicle (SNAV) is based on a lightweight commercial nano-quadcopter (27 g) equipped with a custom gas sensing board that can host up to two in situ metal oxide semiconductor (MOX) gas sensors. Due to its small form-factor, the SNAV is not a hazard for humans, enabling its use in public areas or inside buildings. It can autonomously carry out gas sensing missions of hazardous environments inaccessible to terrestrial robots and bigger drones, for example searching for victims and hazardous gas leaks inside pockets that form within the wreckage of collapsed buildings in the aftermath of an earthquake or explosion. The first contribution of this work is assessing the impact of the nano-propellers on the MOX sensor signals at different distances to a gas source. A second contribution is adapting the ‘bout’ detection algorithm, proposed by Schmuker et al. (2016) to extract specific features from the derivative of the MOX sensor response, for real-time operation. The third and main contribution is the experimental validation of the SNAV for gas source localization (GSL) and mapping in a large indoor environment (160 m2) with a gas source placed in challenging positions for the drone, for example hidden in the ceiling of the room or inside a power outlet box. Two GSL strategies are compared, one based on the instantaneous gas sensor response and the other one based on the bout frequency. From the measurements collected (in motion) along a predefined sweeping path we built (in less than 3 min) a 3D map of the gas distribution and identified the most likely source location. Using the bout frequency yielded on average a higher localization accuracy than using the instantaneous gas sensor response (1.38 m versus 2.05 m error), however accurate tuning of an additional parameter (the noise threshold) is required in the former case. The main conclusion of this paper is that a nano-drone has the potential to perform gas sensing tasks in complex environments.

JTD Keywords: Robotics, Signal processing, Electronics, Gas source localization, Gas distribution mapping, Gas sensors, Drone, UAV, MOX sensor, Quadcopter

Providing force feedback as relevant information in current Robot-Assisted Minimally Invasive Surgery systems constitutes a technological challenge due to the constraints imposed by the surgical environment. In this context, force estimation techniques represent a potential solution, enabling to sense the interaction forces between the surgical instruments and soft-tissues. Specifically, if visual feedback is available for observing soft-tissues’ deformation, this feedback can be used to estimate the forces applied to these tissues. To this end, a force estimation model, based on Convolutional Neural Networks and Long-Short Term Memory networks, is proposed in this work. This model is designed to process both, the spatiotemporal information present in video sequences and the temporal structure of tool data (the surgical tool-tip trajectory and its grasping status). A series of analyses are carried out to reveal the advantages of the proposal and the challenges that remain for real applications. This research work focuses on two surgical task scenarios, referred to as pushing and pulling tissue. For these two scenarios, different input data modalities and their effect on the force estimation quality are investigated. These input data modalities are tool data, video sequences and a combination of both. The results suggest that the force estimation quality is better when both, the tool data and video sequences, are processed by the neural network model. Moreover, this study reveals the need for a loss function, designed to promote the modeling of smooth and sharp details found in force signals. Finally, the results show that the modeling of forces due to pulling tasks is more challenging than for the simplest pushing actions.

JTD Keywords: Convolutional neural networks, Force estimation, LSTM networks, Robotic surgery

The field of bio-hybrid robotics aims at the integration of biological components with artificial materials in order to take advantage of many unique features occurring in nature, such as adaptability, self-healing or resilience. In particular, skeletal muscle tissue has been used to fabricate bio-actuators or bio-robots that can perform simple actions. In this paper, we present 3D bioprinting as a versatile technique to develop these kinds of actuators and we focus on the importance of optimizing the designs and properly characterizing their performance. For that, we introduce a method to calculate the force generated by the bio-actuators based on the deflection of two posts included in the bio-actuator design by means of image processing algorithms. Finally, we present some results related to the adaptation, controllability and force modulation of our bio-actuators, paving the way towards a design- and optimization-driven development of more complex 3D-bioprinted bio-actuators.

JTD Keywords: 3D bioprinting, Bio-hybrid robotics, Muscle-based bio-actuators

Facial expressions are salient social features that crucial in communication, and humans are capable of reading the messages faces convey and the emotions they display. Robots that interact with humans will need to employ similar communication channels for successful interactions. Here, we focus on the readability of the facial expressions of a humanoid robot. We conducted an online survey where participants evaluated emotional stimuli and assessed the robot’s expressions. Results suggest that the robot’s facial expressions are correctly recognised and the appraisal of the robots expressive elements are consistent with the literature.

JTD Keywords: Emotion recognition, Facial expressions, Human-robot interaction

This book constitutes the proceedings of the 8th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2019, held in Nara, Japan, in July 2019. The 26 full and 16 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Biomimetics, Computer architecture, Human robot interaction, Human-Computer Interaction (HCI), Humanoid robot, Image processing, Learning algorithms, Mobile robots, Multipurpose robots, Neural networks, Quadruped robots, Reinforcement learning, Robot learning, Robotics, Robots, Sensor, Sensors, Swarm robotics, User interfaces

Generating complex, human-like behaviour in a humanoid robot like the iCub requires the integration of a wide range of open source components and a scalable cognitive architecture. Hence, we present the iCub-HRI library which provides convenience wrappers for components related to perception (object recognition, agent tracking, speech recognition, touch detection), object manipulation (basic and complex motor actions) and social interaction (speech synthesis, joint attention) exposed as a C++ library with bindings for Java (allowing to use iCub-HRI within Matlab) and Python. In addition to previously integrated components, the library allows for simple extension to new components and rapid prototyping by adapting to changes in interfaces between components. We also provide a set of modules which make use of the library, such as a high-level knowledge acquisition module and an action recognition module. The proposed architecture has been successfully employed for a complex human-robot interaction scenario involving the acquisition of language capabilities, execution of goal-oriented behaviour and expression of a verbal narrative of the robot's experience in the world. Accompanying this paper is a tutorial which allows a subset of this interaction to be reproduced. The architecture is aimed at researchers familiarising themselves with the iCub ecosystem, as well as expert users, and we expect the library to be widely used in the iCub community.

JTD Keywords: Robotics, iCub Humanoid, YARP, Software architecture, C++, Python, Java, Human-robot interaction

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.

JTD Keywords: Autobiographical Memory., Biology, Cognition, Cognitive Robotics, Computer architecture, Distributed Adaptive Control, Grounding, Human-Robot Interaction, Humanoid robots, Robot sensing systems, Symbol Grounding

This chapter takes the view that emotions of living machines can be seen from the perspective of self-regulation and appraisal. We will first look at the pragmatic needs to endow machines with emotions and subsequently describe some of the historical background of the science of emotions and its different interpretations and links to affective neuroscience. Subsequently, we argue that emotions can be cast in terms of self-regulation where they provide for a descriptor of the state of the homeostatic processes that maintain the relationship between the agent and its internal and external environment. We augment the notion of homeostasis with that of allostasis which signifies a change from stability through a fixed equilibrium to stability through continuous change. The chapter shows how this view can be used to create complex living machines where emotions are anchored in the need fulfillment of the agent, in this case considering both utilitarian and epistemic needs.

JTD Keywords: Emotion, Motivation, Needs, Appraisal, Self-regulation, Homeostasis, Allostasis, Human–robot interaction, James–Lange theory

This book constitutes the proceedings of the 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2018, held in Paris, France, in July 2018. The 40 full and 18 short papers presented in this volume were carefully reviewed and selected from 60 submissions. The theme of the conference targeted at the intersection of research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial neural network, Bio-actuators, Bio-robotics, Biohybrid systems, Biomimetics, Bipedal robots, Earthoworm-like robots, Robotics, Decision-making, Tactile sensing, Soft robots, Locomotion, Insects, Sensors, Actuators, Robots, Artificial intelligence, Neural networks, Motion planning, Learning algorithms

Self-propelled micromotors have previously shown to enhance pollutant removal compared to non-motile nano-micro particles. However, these systems are expensive, difficult to scale-up and require surfactant for efficient work. Efficient and inexpensive micromotors are desirable for their practical applications in water treatment technologies. We describe cobalt-ferrite based micromotors (CFO micromotors) fabricated by a facile and scalable synthesis, that produce hydroxyl radicals via Fenton-like reaction and take advantage of oxygen gas generated during this reaction for self-propulsion. Once the reaction is complete, the CFO micromotors can be easily separated and collected due to their magnetic nature. The CFO micromotors are demonstrated for highly efficient advanced oxidative removal of tetracycline antibiotic from the water. Furthermore, the effects of different concentrations of micromotors and hydrogen peroxide on the antibiotic degradation were studied, as well as the generation of the highly reactive hydroxyl radicals responsible for the oxidation reaction.

JTD Keywords: Degradation, Fenton reaction, Microbots, Nanomotors, Self-propelled Micromotors, Water treatment

JTD Keywords: Drug delivery, Nanomachines, Nanomotors, Nanorobots, Target delivery

We present the estimation of a likelihood map for the location of the source of a chemical plume dispersed under atmospheric turbulence under uniform wind conditions. The main contribution of this work is to extend previous proposals based on Bayesian inference with binary detections to the use of concentration information while at the same time being robust against the presence of background chemical noise. For that, the algorithm builds a background model with robust statistics measurements to assess the posterior probability that a given chemical concentration reading comes from the background or from a source emitting at a distance with a specific release rate. In addition, our algorithm allows multiple mobile gas sensors to be used. Ten realistic simulations and ten real data experiments are used for evaluation purposes. For the simulations, we have supposed that sensors are mounted on cars which do not have among its main tasks navigating toward the source. To collect the real dataset, a special arena with induced wind is built, and an autonomous vehicle equipped with several sensors, including a photo ionization detector (PID) for sensing chemical concentration, is used. Simulation results show that our algorithm, provides a better estimation of the source location even for a low background level that benefits the performance of binary version. The improvement is clear for the synthetic data while for real data the estimation is only slightly better, probably because our exploration arena is not able to provide uniform wind conditions. Finally, an estimation of the computational cost of the algorithmic proposal is presented.

JTD Keywords: Machine olfaction, Odor robots, Chemical sensors, Bayesian inference

Self-powered micromachines are promising tools for future environmental remediation technology. Waste-water treatment and water reuse is an essential part of environmental sustainability. Herein, we present reusable Fe/Pt multi-functional active microcleaners that are capable of degrading organic pollutants (malachite green and 4-nitrophenol) by generated hydroxyl radicals via a Fenton-like reaction. Various different properties of microcleaners, such as the effect of their size, short-term storage, long-term storage, reusability, continuous swimming capability, surface composition, and mechanical properties, are studied. It is found that these microcleaners can continuously swim for more than 24 hours and can be stored more than 5 weeks during multiple cleaning cycles. The produced microcleaners can also be reused, which reduces the cost of the process. During the reuse cycles the outer iron surface of the Fe/Pt microcleaners generates the in-situ, heterogeneous Fenton catalyst and releases a low concentration of iron into the treated water, while the mechanical properties also appear to be improved due to both its surface composition and structural changes. The microcleaners are characterized by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), nanoindentation, and finite-element modeling (FEM).

JTD Keywords: Catalysts, Heterogeneous catalysis, Microcleaners, Micromotors, Nanorobots, Wastewater treatment

Fuzzy theory was motivated by the need to create human-like solutions that allow representing vagueness and uncertainty that exist in the real-world. These capabilities have been recently further enhanced by deep learning since it allows converting complex relation between data into knowledge. In this paper, we present a novel Deep-Neuro-Fuzzy strategy for unsupervised estimation of the interaction forces in Robotic Assisted Minimally Invasive scenarios. In our approach, the capability of Neuro-Fuzzy systems for handling visual uncertainty, as well as the inherent imprecision of real physical problems, is reinforced by the advantages provided by Deep Learning methods. Experiments conducted in a realistic setting have demonstrated the superior performance of the proposed approach over existing alternatives. More precisely, our method increased the accuracy of the force estimation and compared favorably to existing state of the art approaches, offering a percentage of improvement that ranges from about 35% to 85%.

JTD Keywords: Estimation, Force, Machine learning, Robots, Three-dimensional displays, Uncertainty, Visualization

Chemically powered micro- and nanomotors are small devices that are self-propelled by catalytic reactions in fluids. Taking inspiration from biomotors, scientists are aiming to find the best architecture for self-propulsion, understand the mechanisms of motion, and develop accurate control over the motion. Remotely guided nanomotors can transport cargo to desired targets, drill into biomaterials, sense their environment, mix or pump fluids, and clean polluted water. This Review summarizes the major advances in the growing field of catalytic nanomotors, which started ten years ago.

JTD Keywords: Catalysis, Micromotors, Nanomotors, Robots, Self-propulsion

Bioactive nanocomposite scaffolds with cell-adhesive surface have excellent bone regeneration capacities. Fibronectin (FN)-immobilized nanobioactive glass (nBG)/polycaprolactone (PCL) (FN-nBG/PCL) scaffolds with an open pore architecture were generated by a robotic-dispensing technique. The surface immobilization level of FN was significantly higher on the nBG/PCL scaffolds than on the PCL scaffolds, mainly due to the incorporated nBG that provided hydrophilic chemical-linking sites. FN-nBG/PCL scaffolds significantly improved cell responses, including initial anchorage and subsequent cell proliferation. Although further in-depth studies on cell differentiation and the in vivo animal responses are required, bioactive nanocomposite scaffolds with cell-favoring surface are considered to provide promising three-dimensional substrate for bone regeneration.

JTD Keywords: Bone scaffolds, Cell response, Fibronectin, Nanobioactive glass, Nanocomposites, Polycaprolactone, Bone, Cell proliferation, Cells, Cytology, Glass, Nanocomposites, Polycaprolactone, Robotics, Bone scaffolds, Bone tissue engineering, Cell response, Fibronectin, Fibronectin immobilizations, Nano bioactive glass, Nanocomposite scaffolds, Three-dimensional substrates, Scaffolds (biology)

The use of multiple robots working cooperatively in a redundant way offers new possibilities in the execution of complex tasks in dynamic workspaces. The aim of this work is to increase the range of applicability of teleoperated systems by means of the automatic cooperation of multiple slave robots which, controlled by a human operator, act as if they were a unique robot: a Multi-Robot Cooperation Platform for Task-Oriented Teleoperation, MRCP. From the human operator commands, this robotic platform, the MRCP, dynamically selects the most suitable slave robot and manages, when necessary, a task transfer from one robot to another in order to achieve a smooth execution of teleoperated tasks. The result of the proposed methodology is an improved teleoperated system in terms of reachable workspace (volume, manoeuvrability and accessibility) and dexterity, thus widening its range of applicability. This approach allows human operators to focus their attention on the ongoing task more than on the teleoperated robots.

JTD Keywords: Multi-robot cooperation, Single-operator-multiple-robot, Task-oriented teleoperation

This paper presents a new rehabilitation system that is able to adapt its performance to patient's psychophysiological state during the execution of robotic rehabilitation tasks. Using this approach, the motivation and participation of the patient during rehabilitation activity can be maximized. In this paper, the results of the study with healthy subjects presented in (Badesa et al., 2014b) have been extended for using them with patients who have suffered a stroke. In the first part of the article, the different components of the adaptive system are exposed, as well as a comparison of different machine learning techniques to classify the patient's psychophysiological state between three possible states: stressed, average excitation level and relaxed are presented. Finally, the results of the auto-adaptive system which modifies the behavior of the rehabilitation robot and virtual task in function of measured physiological signals are shown for a patient in the chronic phase of stroke.

JTD Keywords: Physiological state multimodal interfaces rehabilitation robotics control

An automatic gait initialization strategy based on user intention sensing in the context of rehabilitation with a lower-limb wearable robot is proposed and evaluated. The proposed strategy involves monitoring the human-orthosis interaction torques and initial position deviation to determine the gait initiation instant and to modify orthosis operation for gait assistance, when needed. During gait, the compliant control algorithm relies on the adaptation of the joints' stiffness in function of their interaction torques and their deviation from the desired trajectories, while maintaining the dynamic stability. As a reference input, the average of a set of recorded gaits obtained from healthy subjects is used. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.

JTD Keywords: Biomedical monitoring, Exoskeletons, Joints, Knee, Legged locomotion, Trajectory, Exoskeleton, adaptive control, gait assistance, gait initiation, rehabilitation, wearable robot

The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach that starts with the reconstruction of a 3D deformation structure of the tissue surface by minimizing an energy functional. A Recurrent Neural Network-Long Short Term Memory (RNN-LSTM) based architecture is then presented to accurately estimate the applied forces. According to the results, our solution offers long-term stability and shows a significant percentage of accuracy improvement, ranging from about 54% to 78%, over existing approaches.

JTD Keywords: Computer architecture, Estimation, Force, Microprocessors, Robot sensing systems, Surgery

In this paper, we propose a new approach to domestic action recognition based on a set of features which describe the relation between poses and movements of both hands. These features represent a set of basic actions in a kitchen in terms of the mimics of the hand movements, without needing information of the objects present in the scene. They address specifically the intra-class dissimilarity problem, which occurs when the same action is performed in different ways. The goal is to create a generic methodology that enables a robotic assistant system to recognize actions related to daily life activities and then, be endowed with a proactive behavior. The proposed system uses depth and color data acquired from a Kinect-style sensor and a hand tracking system. We analyze the relevance of the proposed hand-based features using a state-space search approach. Finally, we show the effectiveness of our action recognition approach using our own dataset.

JTD Keywords: Histograms, Joints, Robot sensing systems, Thumb, Tracking, Human activity recognition, Disable and elderly assistance

This paper addresses the issue of lack of force feedback in robotic-assisted minimally invasive surgeries. Force is an important measure for surgeons in order to prevent intra-operative complications and tissue damage. Thus, an innovative neuro-vision based force estimation approach is proposed. Tissue surface displacement is first measured via minimization of an energy functional. A neuro approach is then used to establish a geometric-visual relation and estimate the applied force. The proposed approach eliminates the need of add-on sensors, carrying out biocompatibility studies and is applicable to tissues of any shape. Moreover, we provided an improvement from 15.14% to 56.16% over other approaches which demonstrate the potential of our proposal.

JTD Keywords: Estimation, Force, Minimally invasive surgery, Robot sensing systems, Three-dimensional displays

In this paper, a heuristic method based on Firefly Algorithm is proposed for inverse kinematics problems in articulated robotics. The proposal is called, IK-FA. Solving inverse kinematics, IK, consists in finding a set of joint-positions allowing a specific point of the system to achieve a target position. In IK-FA, the Fireflies positions are assumed to be a possible solution for joints elementary motions. For a robotic system with a known forward kinematic model, IK-Fireflies, is used to generate iteratively a set of joint motions, then the forward kinematic model of the system is used to compute the relative Cartesian positions of a specific end-segment, and to compare it to the needed target position. This is a heuristic approach for solving inverse kinematics without computing the inverse model. IK-FA tends to minimize the distance to a target position, the fitness function could be established as the distance between the obtained forward positions and the desired one, it is subject to minimization. In this paper IK-FA is tested over a 3 links articulated planar system, the evaluation is based on statistical analysis of the convergence and the solution quality for 100 tests. The impact of key FA parameters is also investigated with a focus on the impact of the number of fireflies, the impact of the maximum iteration number and also the impact of (α, β, γ, δ) parameters. For a given set of valuable parameters, the heuristic converges to a static fitness value within a fix maximum number of iterations. IK-FA has a fair convergence time, for the tested configuration, the average was about 2.3394 × 10−3 seconds with a position error fitness around 3.116 × 10−8 for 100 tests. The algorithm showed also evidence of robustness over the target position, since for all conducted tests with a random target position IK-FA achieved a solution with a position error lower or equal to 5.4722 × 10−9.

JTD Keywords: Robotics, Inverse kinematics, Heuristics, Computational kinematics, Swarm intelligence

A user intention based rehabilitation strategy for a lower-limb wearable robot is proposed and evaluated. The control strategy, which involves monitoring the human-orthosis interaction torques, determines the gait initiation instant and modifies orthosis operation for gait assistance, when needed. Orthosis operation is classified as assistive or resistive in function of its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints’ stiffness in function of their interaction torques and their deviation from the desired trajectories. An average of recorded gaits obtained from healthy subjects is used as reference input. The objective of this work is to develop a control strategy that can trigger the gait initiation from the user’s intention and maintain the dynamic stability, using an efficient real-time stiffness adaptation for multiple joints, simultaneously maintaining their synchronization. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.

JTD Keywords: Adaptive control, Exoskeleton, Gait assistance, Gait initiation, Wearable robot

The use of an autonomous mobile robot to locate gas-leaks and air quality monitoring in indoor environments are promising tasks that will avoid risky human operations. However, these are challenging tasks due to the chaotic gas profile propagation originated by uncontrolled air flows. This paper proposes the localization of an acetone gas-leak in a 44 m-length indoor corridor with a mobile robot equipped with a PID sensor. This paper assesses the influence of the mobile robot velocity and the relative height of the PID sensor in the profile of the measurements. The results show weak influence of the robot velocity and strong influence of the relative height of the PID sensor. An estimate of the gas-leak location is also performed by computing the center of mass of the highest gas concentrations.

JTD Keywords: Gas source detection, LIDAR sensor, Mobile robot, PID sensor, SLAM, Acetone, Air quality, Gases, Indoor air pollution, Mobile robots, Robots, Air quality monitoring, Autonomous Mobile Robot, Gas sources, Indoor environment, Leak localization, LIDAR sensors, Profile propagation, SLAM, Ionization of gases

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

JTD Keywords: Ambient intelligence, Human thermal comfort, Robotic exploration

In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources.

JTD Keywords: Environmental monitoring, Gas discrimination, Gas distribution mapping, Service robots, Open sampling systems, PID, Metal oxide sensors

A connection between two vessels or other tubular structures is known as anastomosis, one of the most common procedures in its field but, at the same time, one of the most complex suture-based techniques. This procedure requires not only a lot of skill and dexterity but also a lot of attention and plenty of concentration from the surgeon. This makes many of the actions to be performed irregularly, exposing the patient to human error resulting from the monotony. On the other hand, the field of robotics has earned itself a place in medicine, especially as assistants during a surgical intervention. Even so, medical robotics is quite young and still has not done much in the field of vessel anastomosis. Therefore, this paper presents a preliminary study of the most common suturing techniques, taking into account their typology and performance, within all the possible anastomosis procedures known. Subsequently, a detailed study of workflow and actions during an anastomosis is made, obtaining a diagram for each of the suturing techniques studied. This allows analyzing all procedures and to create a tool to find those actions and repeated tasks and/or common in all of them, indicating which of these are potential candidates for an automation study. This preliminary work focuses on finding where robotics can help to avoid rutinary tasks, which can be learned in a mechanical level and therefore, relatively easy to be automated using a robotic system or to assist the surgeon in certain tasks that need a lot of skill and attention.

JTD Keywords: Suture, Robot Assisted Surgery, Robot Knotting

One of the challenges of the robotics community is to develop robots that behave more and more autonomously. Therefore, it is necessary to establish new design criteria, as well as more complex methodologies supporting the analysis of associated risks. The procedure described in this paper includes civil liability as an additional criterion to validate the safety of a surgical robot. In order to understand the concept, a methodology is presented through the description of a simple case. This work aims to establish the basis for a further implementation.

JTD Keywords: Design methodology, Product development, Product liability, Safety, Robotic surgery, Cognitive robotics

Cerebral Palsy (CP) is the most frequent disability affecting children. Although the effects of CP are diverse this chapter focuses on the impaired motor control of children suffering from spastic diplegia, particularly in the lower limb. The chapter collects the most relevant techniques that are used or might be useful to overcome the current limitations existing in the diagnosis and rehabilitation of CP. Special emphasis is placed on the role that emerging technologies can play in this field. Knowing in advance the type and site of brain injury could assist the clinician in selecting the appropriate therapy. In this context, neuroimaging techniques are being recommended as an evaluation tool in children with CP; we describe a variety of imaging technologies such as Magnetic Resonance Imaging (MRI), Diffusion Tensor Imaging (DTI), etc. But creating new knowledge in itself is not enough; there must be a transfer from progress through research to advances in the clinical field. The classic therapeutic approach of CP thus hampers the optimal rehabilitation of the targeted component. Traditional therapies may be optimized if complemented with treatments. We try to collect a wide range of emerging technologies and provide some criteria to select the adequate technology based on the characteristics of the neurological injury. For example, exoskeleton based over-ground gait training is suggested to be more effective than treadmill-based gait training. So, we suggest a new point of view combining different technologies in order to provide the foundations of a rational design of the individual rehabilitation strategy.

JTD Keywords: Cerebral palsy, Robotics, Neurostimulation, Neuroimaging, Myoelectric signals

Robotic rehabilitation therapies are an emerging tool in the field of Neurorehabilitation in order to achieve an effective therapeutic development in the patient. In this paper, the role of disturbances caused by muscle synergies or unpredictable effects of artificial stimulation in muscles during rehabilitation therapies is analyzed. In terms of gait assistance it is also important to maintain synchronized movements to ensure a dynamically stable gait. Although, disturbances affecting joints are corrected by a force control approach, we define two methods to ensure stability and synchronization of joint movements in the trajectory to be followed. The performance of the presented methods is evaluated in comparison with a preplanned trajectory to be followed by the patients.

JTD Keywords: Exoskeleton, Force control, Gait assistance, Neurorobot, Trajectory planning

Endowing current surgical robotic systems with haptic feedback to perform minimally invasive surgery (MIS), such as laparoscopy, is still a challenge. Haptic is a feature lost in surgical teleoperated systems limiting surgeons capabilities and ability. The availability of haptics would provide important advantages to the surgeon: Improved tissue manipulation, reducing the breaking of sutures and increase the feeling of telepresence, among others. To design and develop a haptic system, the measurement of forces can be implemented based on two approaches: Direct and indirect force sensing. MIS performed with surgical robots, imposes many technical constraints to measure forces, such as: Miniaturization, need of sterilization or materials compatibility, making it necessary to rely on indirect force sensing. Based on mathematical models of the components involved in an intervention and indirect force sensing techniques, a global perspective on how to address the problem of measurement of tool-tissue interaction forces is presented.

JTD Keywords: Surgical robotics, Haptic feedback, Indirect force sensing, Machine learning, Data fusion, Mathematical models

This work introduces an interactive robotic system for assistance, conceived to tackle some of the challenges that domestic environments impose. The system is organized into a network of heterogeneous components that share both physical and logical functions to perform complex tasks. It consists of several robots for object manipulation, an advanced vision system that supplies in-formation about objects in the scene and human activity, and a spatial augmented reality interface that constitutes a comfortable means for interacting with the system. A first analysis based on users' experiences confirms the importance of having a friendly user interface. The inclusion of context awareness from visual perception enriches this interface allowing the robotic system to become a flexible and proactive assistant.

JTD Keywords: Accessibility, Activity Recognition, Ambient Intelligence, Human-Robot Interaction, Robot Assistance, Augmented reality, Complex networks, Computer vision, User interfaces, Accessibility, Activity recognition, Ambient intelligence, Domestic environments, Heterogeneous component, Interactive robotics, Robot assistance, Spatial augmented realities, Human assistance, Robotics

This paper presents an autonomous agent for gas leak source detection. The main objective of the robot is to estimate the localization of the gas leak source in an indoor environment without any human intervention. The agent implements an SLAM procedure to scan and map the indoor area. The mobile robot samples gas concentrations with a gas and a wind sensor in order to estimate the source of the gas leak. The mobile robot agent will use the information obtained from the onboard sensors in order to define an efficient scanning path. This paper describes the measurement results obtained in a long corridor with a gas leak source placed close to a wall.

JTD Keywords: Gas detection, Mobile robot agent, Laser sensor, Self-localization

Heart motion compensation is a challenging problem within medical robotics and it is still considered an open research area due to the lack of robustness. As it can be formulated as an energy minimization problem, an optimization technique is needed. The selection of an adequate method has a significant impact over the global solution. For this reason, a new methodology is presented here for solving heart motion compensation in which the central topic is oriented to increase robustness with the goal of achieving a balance between efficiency and efficacy. Particularly, genetic algorithms are used as optimization technique since they can be adapted to any real application, complex and oriented to work in real-time problems.

JTD Keywords: Genetic Algorithms, Deformation, Stochastic Optimization, Beating Heart Surgery, Robotic Assisted Surgery

The authors present an introductory work for the implementation of an international cooperative project aimed at designing, developing and validating a new generation of ergonomic robotic suits, wearable by the users and controlled by the human brain. The aim of the proposers is to allow the motion of people affected by paralysis or with reduced motor abilities. Therefore, the project will focus on the fusion between neuroergonomics and robotics, also by means of brain-machine interfaces. Breakthrough solutions will compose the advanced robotic suit, endowed with soft structures to increment safety and human comfort, and with an advanced real-time control that takes into account the interaction with the human body.

JTD Keywords: Neuroergonomics, Brain computer interfaces, Robotics, Robotic suits, Compliant actuators, Exoskeleton, EEG, Dynamic balance control

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

JTD Keywords: Antennal lobes, Artificial olfaction, Computational neuroscience, Olfactory bulbs, Plume tracking, Abstracting, Actuators, Algorithms, Biomimetic processes, Chemical sensors, Conducting polymers, Data processing, Flavors, Odors, Robots, Smart sensors, Embedded systems

Due to its environmental, economical and safety implications, methane leak detection is a crucial task to address in the biogas production industry. In this paper, we introduce Gasbot, a robotic platform that aims to automatize methane emission monitoring in landfills and biogas production sites. The distinctive characteristic of the Gasbot platform is the use of a Tunable Laser Absorption Spectroscopy (TDLAS) sensor. This sensor provides integral concentration measurements over the path of the laser beam. Existing gas distribution mapping algorithms can only handle local measurements obtained from traditional in-situ chemical sensors. In this paper we also describe an algorithm to generate 3D methane concentration maps from integral concentration and depth measurements. The Gasbot platform has been tested in two different scenarios: an underground corridor, where a pipeline leak was simulated and in a decommissioned landfill site, where an artificial methane emission source was introduced.

JTD Keywords: Laser beams, Measurement by laser beam, Mobile robots, Robot kinematics, Robot sensing systems

Teleoperation, by adequately adapting computer interfaces, can benefit from the knowledge on human factors and psychomotor models in order to improve the effectiveness and efficiency in the execution of a task. While scaling is one of the performances frequently used in teleoperation tasks that require high precision, such as surgery, this article presents a scaling method that considers the system dynamics as well. The proposed dynamic scaling factor depends on the apparent position and velocity of the robot and targets. Such scaling improves the performance of teleoperation interfaces, thereby reducing user's workload.

JTD Keywords: Human-robot interaction, Throughput, Scaling functions, Motor control performance

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

JTD Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb

Teleoperation, by adequately adapting computer interfaces, can benefit from the knowledge on human factors and psychomotor models in order to improve the effectiveness and efficiency in the execution of a task. While scaling is one of the performances frequently used in teleoperation tasks that require high precision, such as surgery, this article presents a scaling method that considers the system dynamics as well. The proposed dynamic scaling factor depends on the apparent position and velocity of the robot and targets. Such scaling improves the performance of teleoperation interfaces, thereby reducing user's workload.

JTD Keywords: Human-robot interaction, Motor control performance, Scaling functions, Throughput

The design of mechanical joints that kinematically behave as their biological counterparts is a challenge that if not addressed properly can cause inadequate forces transmission between robot and patient. This paper studies the interaction forces in rehabilitation therapies of the elbow joint. To measure the effect of orthosis-patient misalignments, a force sensor with a novel distributed architecture has been designed and used for this study. A test-bed based on an industrial robot acting as a virtual exoskeleton that emulates the action of a therapist has been developed and the interaction forces analyzed.

JTD Keywords: Force, Force measurement, Force sensors, Joints, Medical treatment, Robot sensing systems, Force sensors, Medical robotics, Patient rehabilitation, Biological counterparts, Distributed architecture, Elbow joint, Force sensor, Inadequate forces transmission, Industrial robot, Mechanical joints design, Orthosis-patient misalignments, Patient-orthosis interaction forces, Rehabilitation therapies, Robot, Test-bed, Virtual exoskeleton

This paper presents a novel teleoperation paradigm, the Virtual Robot (VR), focused on facilitating the surgeon tasks in minimally invasive robotic surgery. The VR has been conceived to increase the range of applicability of traditional master slave teleoperation architectures by means of an automatic cooperative behavior that assigns the execution of the ongoing task to the most suitable robot. From the user's point of view, the VR internal operation must be automatic and transparent. A set of evaluation indexes have been developed to obtain the suitability of each robot as well as an algorithm to determine the optimal instant of time to execute a task transfer. Several experiments demonstrate the usefulness of the VR, as well as indicates the next steps of the research.

JTD Keywords: Cameras, Collision avoidance, Indexes, Joints, Robots, Surgery, Trajectory, Medical robotics, Surgery, Telerobotics, VR internal operation, Automatic cooperative behavior, Evaluation indexes, Master slave teleoperation architectures, Minimally invasive robotic surgery, Task transfer, Virtual robot

This work describes the data from navigation experiments with the mobile robot, equipped with the sensor array of three MOX gas sensors. Performed four series of measurements aim to explore the capabilities of sensor array to build the odour map with one or two odour sources in the wind tunnel space. It was demonstrated that the method based on Independent Component Analysis (ICA) is able to discriminate two odour sources, that in future can be used in the surge-and-cast robot navigation algorithm.

JTD Keywords: Mobile robots, Data acquisition, MIS devices, Chemioception

Robotics has shown its potential not only in assisting the surgeon during an intervention but also as a tool for training and for surgical procedure's evaluation. Thus, robotics can constitute an extension of simulators that are based on the high capabilities of computer graphics. In addition, haptics has taken a first step in increasing the performance of current virtual reality systems based uniquely on computer simulation and their corresponding interface devices. As a further step in the field of training and learning in surgery, this work describes a robotic experimental workstation composed of robots and specific measuring devices, together with their corresponding control and monitoring strategies for orthopaedic surgery. Through a case study, humerus arthroplasty, experimental evaluation shows the possibilities of having a test bed available for repetitive and quantifiable trials, which make a reliable scientific comparison between different surgical strategies possible.

JTD Keywords: Surgical robotics, Training robotics, Optimisation of surgical procedures, Surgical techniques evaluation

The concept and design of a friendly human-machine interaction system for an adapted robotized kitchen is presented. The kitchen is conceived in a modular way in order to be adaptable to a great diversity in level and type of assistance needs. An interaction manager has been developed which assist the user to control the system actions dynamically according to the given orders and the present state of the environment. Real time enhanced perception of the scenario is achieved by means of a 3D computer vision system. The main goal of the present project is to provide this kitchen with the necessary intelligent behavior to be able to actuate efficiently by interpreting the users' will.

JTD Keywords: Human computer interaction, Intelligent robots, Robot vision

The growth of robotics in the surgical field is consequence of the progress in all its related areas, as: perception, instrumentation, actuators, materials, computers, and so. However, the lack of intelligence of current robots makes teleoperation an essential means for robotizing the Operating Room (OR), helping in the improvement of surgical procedures and making the best of the human-robot couple, as it already happens in other robotic application fields. The assistance a teleoperated system can provide is the result of the control strategies that can combine the high performance of computers with the surgeon knowledge, expertise and will. In this lecture, an overview of teleoperation techniques and operating modes suitable in the OR is presented, considering different cooperation levels. A special emphasis will be put on the selection of the most adequate interfaces currently available, able to operate in such quite special environments.

JTD Keywords: Medical Robotics, Human Robot Interaction, Human Machine Interfaces, Surgical Robots

The design of orthotic devices that tries to fit to the anthropomorphic structure of human limbs faces the problem of achieving the highest approximation to the anatomical kinematics. This paper studies the main characteristics and performances of orthotic devices, mainly focusing on the upper limbs, and proposes a solution to the problem of the superposition of rotation and displacement of some joints, as the shoulder, elbow or knee. A 3 DoF virtual joint is proposed to emulate a human joint, solving the isocentricity and size adaptation of most current orthosis.

JTD Keywords: Prosthetics and other practical applications, Prosthetics and orthotics, Prosthetic and orthotic control systems, Robotics, Biomechanics (mechanical engineering), Robot and manipulator mechanics

The main goal of this work is to propose a haptics guideline in human-robot systems focused on the relationship between the human and robot task, the use of a physical interface and the object to manipulate. With this aim, this guideline presents two main parts: a set of heuristic indicators and a qualitative evaluation. In order to assess its ergonomic validation, an application over a well known haptics interface is presented. The final goal of this work is the study of possible applications in regular laboratory conditions in order to improve the design and use of human-robot haptic interfaces in telerobotics applications.

JTD Keywords: Haptic interface design, Human-robot interaction, Surgical applications, Teleoperation

Teleoperation is essential for applications in which, despite the availability of a precise geometrical definition of the working area, a task cannot be explicitly programmed. This paper describes a method of assisted teleoperation that improves the execution of such tasks in terms of ergonomics, precision, and reduction of execution time. The relationships between the operating spaces corresponding to the human-robot interface triangle are analyzed. The proposed teleoperation aid is based on applying adaptive transformations between these spaces.

JTD Keywords: Human factors, Human-robot interaction, Teleoperation

Continuous advances on diagnostic techniques based on medical images, as well as the incorporation of new techniques in surgical instruments are progressively changing the new surgical procedures. Also, new minimally invasive techniques, which are currently highly consolidated, have produced significant advances, both from the technological and from the surgical treatment perspectives. The limitations that the manual realization of surgical interventions implies, in what refers to precision and accessibility, can be tackled with the help of robotics. In the same way, sensor based robot control techniques are opening new possibilities for the introduction of more improvements in these procedures, either relying on teleoperation, in which the surgeon and the robot establish their best synergy to get the optimal results, or by means of the automation of some specific actions or tasks. In this article the effect of robotics in the evolution of surgical techniques is described. Starting with a review of the robotics application fields, the article continues analyzing the methods and technologies involved in the process of robotizing surgical procedures, as well as the surgeon-robot interaction systems.

JTD Keywords: Robotics, Medical Applications, Teleoperation, Biomedical Systems, Computer Aided Surgery, Human-Machine Interaction

This paper presents a strategy for a cooperative multirobot system, constituting a virtual robot. The virtual robot is composed of a set of robotic arms acting as only one, transferring the execution of a teleoperated task from one to another when necessary. To decide which of the robots is the most suitable to execute the task at every instant, a multiparametric decision function has been defined. This function is based on a set of intrinsic and extrinsic evaluation indexes of the robot. Since the internal operation of the virtual robot must be transparent to the user, a control architecture has been developed.

JTD Keywords: Control engineering computing, Manipulators, Multi-robot systems, Optimsation, Telerobotics, Virtual reality