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Robotics has the power to help our society in managing many current and foreseeable challenges, and contribute to a responsible future, as formally structured in the United Nations' Sustainable Development Goals (SDGs) initiative. Prior work has already investigated the impact of Artificial Intelligence (AI) on the SDGs, using a systematic consensus-based expert elicitation process. However, the existing literature has not focused on the intricacies of robotics and the unique dynamics this domain presents regarding the SDGs. In this vein, this work adapts an established approach, to focus on and dive deeper into the field of robotics and social responsibility. We introduce a multidisciplinary analysis of both the enabling and disabling roles of robotics, in achieving the SDG-presented, major economic, social and environmental priorities. The United Nation's 17 SDG and the 169 Targets, were individually examined within the context of state-of-the-art robotics already documented in scientific literature. The significance and the quality-of-evidence of enabling/inhibiting impacts, were assessed by an international panel of experts, to quantify the positive or negative effect of the applied robotic systems. Results from this study indicate that robotics has the potential to enable 46 % of the Targets, particularly for the industry and environment-related SDGs, forecasting a huge impact on our production systems and thus on our entire society. Inversely, robotics could inhibit 19 % of the SDG Targets, mainly through exacerbation of inequalities and tensions in the SDGs. The objective of this paper is to assess and grade the current impact of the robotics megatrend on the SDGs, provide comparable data, and encourage the robotics community to work on these targets, in a unified way and eventually improve the quality of the related outcomes., SCOPUS: ar.j, info:eu-repo/semantics/published

QC 20220601

Soft robots are, due to their softness, inherently safe and adapt well to unstructured environments. However, they are prone to various damage types. Self-healing polymers address this vulnerability. Self-healing soft robots can recover completely from macroscopic damage, extending their lifetime. For developing healable soft robots, various formative and additive manufacturing methods have been exploited to shape self-healing polymers into complex structures. Additionally, several novel manufacturing techniques, noted as (re)assembly binding techniques that are specific to self-healing polymers, have been created. Herein, the wide variety of processing techniques of self-healing polymers for robotics available in the literature is reviewed, and limitations and opportunities discussed thoroughly. Based on defined requirements for soft robots, these techniques are critically compared and validated. A strong focus is drawn to the reversible covalent and (physico)chemical cross-links present in the self-healing polymers that do not only endow healability to the resulting soft robotic components, but are also beneficial in many manufacturing techniques. They solve current obstacles in soft robots, including the formation of robust multi-material parts, recyclability, and stress relaxation. This review bridges two promising research fields, and guides the reader toward selecting a suitable processing method based on a self-healing polymer and the intended soft robotics application.

Sensory receptors in biological systems are an essential part of natural organisms to perceive, understand and adapt to their environment and evaluate their internal state. They are interlinked with the senses of living organisms and are an important tool for the survival and evolution of species. Researchers have implemented the biomimetic receptor approach into the development of artificial sensors, in an attempt to mimic the sensory transduction of organisms, like self-healing ability and flexibility. However, aspects of biological transduction like selectivity and multi-sensing are still underdeveloped in the field of soft self-healing sensors (SSHS). The multi-sensing aspect is discussed in this review paper, focusing on resistive-based SSHS for detecting different stimuli, like strain, pressure, tactile, temperature, chemical species and structural damage. The inspiration from sensory transduction of biological systems will be a key factor for the further development of SSHS and their application in soft robotics, electronic skin, smart wearables and haptic devices.

Self-healing materials can prolong the lifetime of structures and products by enabling the repairing of damage. However, detecting the damage and the progress of the healing process remains an important issue. In this study, self-healing, piezoresistive strain sensor fibers (ShSFs) are used for detecting strain deformation and damage in a self-healing elastomeric matrix. The ShSFs were embedded in the self-healing matrix for the development of self-healing sensor fiber composites (ShSFC) with elongation at break values of up to 100%. A quadruple hydrogen-bonded supramolecular elastomer was used as a matrix material. The ShSFCs exhibited a reproducible and monotonic response. The ShSFCs were investigated for use as sensorized electronic skin on 3D-printed soft robotic modules, such as bending actuators. Depending on the bending actuator module, the electronic skin was loaded under either compression (pneumatic-based module) or tension (tendon-based module). In both configurations, the ShSFs could be successfully used as deformation sensors, and in addition, detect the presence of damage based on the sensor signal drift. The sensor under tension showed better recovery of the signal after healing, and smaller signal relaxation. Even with the complete severing of the fiber, the piezoresistive properties returned after the healing, but in that case, thermal heat treatment was required. With their resilient response and self-healing properties, the supramolecular fiber composites can be used for the next generation of soft robotic modules.

Self-healing materials can prolong the lifetime of structures and products by enabling the repairing of damage. However, detecting the damage and the progress of the healing process remains an important issue. In this study, self-healing, piezoresistive strain sensor fibers (ShSFs) are used for detecting strain deformation and damage in a self-healing elastomeric matrix. The ShSFs were embedded in the self-healing matrix for the development of self-healing sensor fiber composites (ShSFC) with elongation at break values of up to 100%. A quadruple hydrogen-bonded supramolecular elastomer was used as a matrix material. The ShSFCs exhibited a reproducible and monotonic response. The ShSFCs were investigated for use as sensorized electronic skin on 3D-printed soft robotic modules, such as bending actuators. Depending on the bending actuator module, the electronic skin was loaded under either compression (pneumatic-based module) or tension (tendon-based module). In both configurations, the ShSFs could be successfully used as deformation sensors, and in addition, detect the presence of damage based on the sensor signal drift. The sensor under tension showed better recovery of the signal after healing, and smaller signal relaxation. Even with the complete severing of the fiber, the piezoresistive properties returned after the healing, but in that case, thermal heat treatment was required. With their resilient response and self-healing properties, the supramolecular fiber composites can be used for the next generation of soft robotic modules.

info:eu-repo/semantics/published

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., CC BY 4.0, DREAM - Development of robot-enhanced therapy for children with autism spectrum disorders.

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., CC BY 4.0, DREAM - Development of robot-enhanced therapy for children with autism spectrum disorders.

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of childrens behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., Funding Agencies|EU, under the Seventh Frame Programme grant: Development of Robot-Enhanced therapy for children with AutisM spectrum disorders (DREAM) [611391]

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of childrens behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., Funding Agencies|EU, under the Seventh Frame Programme grant: Development of Robot-Enhanced therapy for children with AutisM spectrum disorders (DREAM) [611391]

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of childrens behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., Funding Agencies|EU, under the Seventh Frame Programme grant: Development of Robot-Enhanced therapy for children with AutisM spectrum disorders (DREAM) [611391]

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of childrens behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., Funding Agencies|EU, under the Seventh Frame Programme grant: Development of Robot-Enhanced therapy for children with AutisM spectrum disorders (DREAM) [611391]

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., CC BY 4.0, DREAM - Development of robot-enhanced therapy for children with autism spectrum disorders.

We consider solving a cooperative multi-robot object manipulation task using reinforcement learning (RL). We propose two distributed multi-agent RL approaches: distributed approximate RL (DA-RL), where each agent applies Q-learning with individual reward functions; and game-theoretic RL (GT-RL), where the agents update their Q-values based on the Nash equilibrium of a bimatrix Q-value game. We validate the proposed approaches in the setting of cooperative object manipulation with two simulated robot arms. Although we focus on a small system of two agents in this paper, both DA-RL and GT-RL apply to general multi-agent systems, and are expected to scale well to large systems., Comment: 3 pages, 3 figures

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., CC BY 4.0, DREAM - Development of robot-enhanced therapy for children with autism spectrum disorders.

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of childrens behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., Funding Agencies|EU, under the Seventh Frame Programme grant: Development of Robot-Enhanced therapy for children with AutisM spectrum disorders (DREAM) [611391]

Elastic actuators can provide safe human-robot interaction and energy efficient mobility. For this purpose they are ideal for wearable robotic applications. However, such actuators are subject to stiffness faults. We present a stiffness-fault-tolerant control strategy for complex elastic actuators, capable of adapting to changes in output stiffness, and demonstrate it on a smart variable stiffness actuator based on the MACCEPA concept. We develop the dynamics of the actuator and a model-based impedance control scheme. Biomechanical data extracted from the flexion/extension of a real knee joint are used as trajectory reference for the evaluation of the control concept in simulation. Results show that the controlled actuator is capable of tracking a reference trajectory under fault conditions and interaction disturbance while maintaining physical human-robot characteristics., Postprint (published version)

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general., CC BY 4.0, DREAM - Development of robot-enhanced therapy for children with autism spectrum disorders.

A large portion of the working population is affected by back and shoulder pain. Lower back support exoskeletons were introduced as a preventative measure, but they are not widely adopted by the industry yet. Their adoption is hindered chiefly by discomfort, loss of range of motion and kinematic incompatibility. In this work, we discuss the range of motion of the trunk in the sagittal plane, once wearing a flexible exoskeleton and once without wearing an exoskeleton (N = 2).

A large portion of the working population is affected by back and shoulder pain. Lower back support exoskeletons were introduced as a preventative measure, but they are not widely adopted by the industry yet. Their adoption is hindered chiefly by discomfort, loss of range of motion and kinematic incompatibility. In this work, we discuss the range of motion of the trunk in the sagittal plane, once wearing a flexible exoskeleton and once without wearing an exoskeleton (N = 2).

It is evident that recently reported robot-assisted therapy systems for assessment of children with autism spectrum disorder (ASD) lack autonomous interaction abilities and require significant human resources. This paper proposes a sensing system that automatically extracts and fuses sensory features such as body motion features, facial expressions, and gaze features, further assessing the children behaviours by mapping them to therapist-specified behavioural classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behaviour assessment. IEEE

DREAM, FP7 grant #611391.

n/a, Funding Agencies|European Commissions Seventh Framework Program as part of the DREAM project [611391]

It is evident that recently reported robot-assisted therapy systems for assessment of children with autism spectrum disorder (ASD) lack autonomous interaction abilities and require significant human resources. This paper proposes a sensing system that automatically extracts and fuses sensory features, such as body motion features, facial expressions, and gaze features, further assessing the children behaviors by mapping them to therapist-specified behavioral classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behavior assessment., Funding Agencies|EU [611391]

The assembly industry is shifting more towards customizable products, or requiring assembly of small batches. This requires a lot of reprogramming, which is expensive because a specialized engineer is required. It would be an improvement if untrained workers could help a cobot to learn an assembly sequence by giving advice. Learning an assembly sequence is a hard task for a cobot, because the solution space increases drastically when the complexity of the task increases. This work introduces a novel method where human knowledge is used to reduce this solution space, and as a result increases the learning speed. The method proposed is the IRL-PBRS method, which uses Interactive Reinforcement Learning (IRL) to learn from human advice in an interactive way, and uses Potential Based Reward Shaping (PBRS), in a simulated environment, to focus learning on a smaller part of the solution space. The method was compared in simulation to two other feedback strategies. The results show that IRL-PBRS convergesmore quickly to a valid assembly sequence policy and does this with the fewest human interactions. Finally, a use case is presented where participants were asked to program an assembly task. Here, the results show that IRL-PBRS learns quickly enough to keep up with advice given by a user, and is able to adapt online to a changing knowledge base., SCOPUS: ar.j, info:eu-repo/semantics/published

This thesis describes the design and development of a hovering flapping two-winged robot of the size of a hummingbird (named COLIBRI ). The robot is tailless and the attitude is actively controlled by changing the wing camber with a mechanism known as wing twist modulation. The current version of our robot has a total mass of 23 gr, a wingspan of 21cm and a flapping frequency of 21Hz. The robot has demonstrated a successful hovering flight with on-board batteries and control board. The flight endurance is more than one minute. The thesis provides a detailed explanation of the design of the robot sub-systems, including flapping mechanism, wing aerodynamics, control mechanism, and implemented control algorithm to achieve a sustained precision hovering flight.The first part of the thesis (Chapter 2) explains the development of a string-based flapping mechanism aiming at minimizing the parasitic torques resulting from the asymmetric profile of the wing trajectories. The contribution of leading edge bar flexibility to the wing aerodynamic efficiency and to the noise level of the flapping frame are also investigated by experiments with various leading edge bar diameters. Additionally, the design of the flapping mechanism gearbox for enhancing the flight duration is provided. The performance of the developed flapping mechanism is evaluated using a high speed camera and conducting flight experiments.The development of the wing-based control mechanism is described in Chapter 3. The control mechanism generates control torques around the three axes of the robot by modifying the wing kinematics while minimizing the cross-coupling effects. To achieve this, two architectures of series and parallels mechanisms are investigated. The two mechanisms are mathematically analysed to evaluate their behaviour with respect to cross-coupling effects. The analysis is verified by measuring the control torque characteristics. The effectiveness of the proposed method is explored by flight testi, Doctorat en Sciences de l'ingénieur et technologie, info:eu-repo/semantics/nonPublished

Objectives The objectives are to determine neural dynamics during gait using electro-encephalography and source localization, and to investigate the attentional demand during walking in able-bodied individuals, and individuals with an amputation. Materials & methods Six able-bodied individuals conducted one experimental trial, and 6 unilateral transtibial and 6 unilateral transfemoral amputees performed 2 experimental trials; the first with the prosthesis currently used by the subjects and the second with a novel powered transtibial prosthesis, i.e. the Ankle Mimicking Prosthetic foot 4.0. Each experimental trial comprised 2 walking tasks; 6 and 2 minutes treadmill walking at normal speed interspersed by 5 minutes of rest. During 6 minutes walking the Sustained Attention to Response (go-no go) Task, which measures reaction time and accuracy, was performed. Electro-encephalographic data were gathered when subjects walked 2 minutes. Motor-related cortical potentials and brain source activity during gait were examined. Normality and (non-) parametric tests were conducted (p<0.05). Results and discussion In contrast to transtibial amputees, transfemoral amputees required more attentional demands during walking with Ankle Mimicking Prosthetic foot 4.0 compared to the current passive prosthetic device and able-bodied individuals (reaction time and accuracy: p0.028). Since risk of falling is associated with altered attentional demands, propulsive forces of the novel device need to be better controlled for transfemoral amputees. No motor-related cortical potentials at Cz were observed in transfemoral amputees walking with the novel prosthesis, whereas motor-related cortical potentials between transtibial amputees and able-bodied individuals during walking at normal speed did not differ. The first positive electro-physiological peak deflection appeared during toe-off phase and showed higher activity within the underlying brain sources in transtibial amputees walking with Ank, SCOPUS: ar.j, info:eu-repo/semantics/published

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied.

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied.

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied.

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied.

The development of social robots for children with autism has been a growth field for the past 15 years. This article reviews studies in robots and autism as a neurodevelopmental disorder that impacts socialcommunication development, and the ways social robots could help children with autism develop social skills. Drawing on ethics research from the EU-funded Development of Robot-Enhanced Therapy for Children with Autism (DREAM) project (framework 7), this paper explores how ethics evolves and developed in this European project., Development of robot-enhanced therapy for children with autism spectrum disorders (DREAM), FP7 grant #611391

Robotic manipulators that are intended to interact with humans in their operating region are systems that need formal safety guarantees. Current solutions cannot handle both input and state constraints, have difficulties handling nonconvex constraints, or are computationally too expensive. To tackle these drawbacks, we analyzed a constrained control strategy, the Explicit Reference Governor (ERG), which can address both input and state constraints, and does not require any online optimization, thus making it computationally inexpensive. This paper presents the theory of the ERG for a general robotic manipulator and shows simulations for a specific 2DOF planar robotic manipulator. The proposed control scheme is able to steer the robot arm to the desired end-effector position, or an admissible approximation, in the presence of limited joint ranges, actuator saturations, and static obstacles. As a result, the ERG is a promising tool for the control of robotic manipulators subject to constraints., SCOPUS: cp.p, info:eu-repo/semantics/published

info:eu-repo/semantics/nonPublished

This dissertation focuses on the constrained control of multi-body systems which are actuated by vectorized thrusters. A general control framework is proposed to stabilize the task configuration while ensuring constraints satisfaction at all times. For this purpose, the equations of motion of the system are derived using the Euler-Lagrange method. It is seen that under some reasonable conditions, the system dynamics are decoupled. This property is exploited in a cascade control scheme to stabilize the points of equilibrium of the system. The control scheme is composed of an inner loop, tasked to control the attitude of the vectorized thrusters, and an outer loop which is tasked to stabilize the task configuration of the system to a desired configuration. To prove stability, input-to-state stability and small gain arguments are used. All stability properties are derived in the absence of constraints, and are shown to be local. The main result of this analysis is that the proposed control scheme can be directly applied under the assumption that a suitable mapping between the generalized force and the real inputs of the system is designed. This thesis proposes to enforce constraints by augmenting the control scheme with two types of Reference Governor units: the Scalar Reference Governor, and the Explicit Reference Governor. This dissertation presents two case studies which inspired the main generalization of this thesis: (i) the control of an unmanned aerial and ground vehicle manipulating an object, and (ii) the control of a tethered quadrotor. Two further case studies are discussed afterwards to show that the generalized control framework can be directly applied when a suitable mapping is designed., Doctorat en Sciences de l'ingénieur et technologie, info:eu-repo/semantics/nonPublished

Throughout the last decade, a whole new generation of powered transtibial prostheses and exoskeletons has been developed. However, these technologies are limited by a gait phase detection which controls the wearable device as a function of the activities of the wearer. Consequently, gait phase detection is considered to be of great importance, as achieving high detection accuracy will produce a more precise, stable, and safe rehabilitation device. In this paper, we propose a novel gait percent detection algorithm that can predict a full gait cycle discretised within a 1% interval. We called this algorithm an exponentially delayed fully connected neural network (ED-FNN). A dataset was obtained from seven healthy subjects that performed daily walking activities on the flat ground and a 15-degree slope. The signals were taken from only one inertial measurement unit (IMU) attached to the lower shank. The dataset was divided into training and validation datasets for every subject, and the mean square error (MSE) error between the model prediction and the real percentage of the gait was computed. An average MSE of 0.00522 was obtained for every subject in both training and validation sets, and an average MSE of 0.006 for the training set and 0.0116 for the validation set was obtained when combining all subjects’ signals together. Although our experiments were conducted in an offline setting, due to the forecasting capabilities of the ED-FNN, our system provides an opportunity to eliminate detection delays for real-time applications., SCOPUS: ar.j, info:eu-repo/semantics/published

Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.

Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.

Robotics and more particularly humanoid robots are envisioned as a solution to support humans in dangerous, repetitive and demeaning tasks. Indeed, humanoid robots, with their human shape, are perfectly tailored to integrate our environment and use tools originally designed for humans. However, unstabilized vision of such robots severely degrades their perception, thus preventing them to autonomously operate in unknown environments. In this context, gaze stabilization emerged as a promising way to overcome this limitation. It consists in actively controlling the motors of the robot head and eyes in order to stabilize the perceived images. In this thesis, driven by bio-inspiration, we explore the potential use of the concept of internal model to support humanoid robot gaze stabilization. This concept from neuroscience, internally simulating the sensorimotor system, is indeed known to play a central role in human motor control and could also benefit to robot control. This doctoral dissertation starts by describing the tools developed to implement and test gaze stabilization controllers. More precisely, dynamic modelling of humanoid robots and middleware based software architecture are addressed. After that, two beneficial uses of internal model for robotic gaze stabilization are demonstrated. First, an anticipatory gaze stabilization based on the concept of virtual linkage is proposed. Then, a multimodal control scheme based on the reafference principle is presented. It complements the first controller with visual and inertial reflexes., (FSA - Sciences de l'ingénieur) -- UCL, 2017

Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.

Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.

Human-swarm interaction studies how human beings can interact with a robotswarm---a large number of robots cooperating with each other without any form of centralizedcontrol. In today's human-swarm interaction literature, the large majority of the works investigatehow human beings can issue commands to and receive feedback from a robot swarm. However, only a few ofthese works study the effect of the interaction with a robot swarm on human psychology (e.g. on thehuman stress or on the human workload). Understanding human psychology in human-swarm interaction isimportant because the human psychological state can have significant impact on the way humansinteract with robot swarms (e.g. a high level of stress can cause a human operator to freeze in themiddle of a critical task, such as a search-and-rescue task). Most existing works that study human psychology in human-swarm interaction conduct their experimentsusing robot swarms simulated on a computer screen. The use of simulation is convenient becauseexperimental conditions can be repeated perfectly in different experimental runs and becauseexperimentation using real robots is expensive both in money and time. However, simulation suffersfrom the so-called reality gap: the inherent discrepancy between simulation and reality. Itis therefore important to study whether this inherent discrepancy can affect humanpsychology---human operators interacting with a simulated robot swarm can react differently thanwhen interacting with a real robot swarm.A large literature in human-robot interaction has studied the psychological impact of theinteraction between human beings and single robots. This literature could in principle be highlyrelevant to human-swarm interaction. However, an inherent difference between human-robot interactionand human-swarm interaction is that in the latter, human operators interact with a large number ofrobots. This large number of robots can affect human psychology---human operators interacting with alar, Doctorat en Sciences de l'ingénieur et technologie, info:eu-repo/semantics/nonPublished

Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.

There is a lack of autonomy on traditional Robot-Assisted Therapy systems interacting with children with autism. To overcome this limitation a supervised autonomous robot controller is being built. In this paper we present a multilayer reactive system within such controller. The goal of this Reactive system is to allow the robot to appropriately react to the child's behavior creating the illusion of being alive., Comment: 5th International Symposium on New Frontiers in Human-Robot Interaction 2016 (arXiv:1602.05456)

While social robots are developed to provide assistance to users through social interactions, their behaviors are dominantly pre-programmed and remote-controlled. Despite the numerous robot control architectures being developed, very few offer reutilization opportunities in various therapeutic contexts. To bridge this gap, we propose a robot control architecture to be applied in different scenarios taking into account requirements from both therapeutic and robotic perspectives. As robot behaviors are kept at an abstract level and afterward mapped with the robot's morphology, the proposed architecture accommodates its applicability to a variety of social robot platforms., Comment: 5th International Symposium on New Frontiers in Human-Robot Interaction 2016 (arXiv:1602.05456)

The last decades, rehabilitation has become a challenging context for mechatronical engineering. From the state-of-the-art it is seen that the field of prosthetics offers very promising perspectives to roboticist. Today’s prosthetic feet tend to improve amputee walking experience by delivering the necessary push-off forces while walking. Therefore, several new types of (compliant) actuators are developed in order to fulfill the torque and power requirements of a sound ankle-foot complex with minimized power consumption. At the Vrije Universiteit Brussel, the Robotics and Multibody Mechanics research group puts a lot of effort in the design and development of new bionic feet. In 2013, the Ankle Mimicking Prosthetic (AMP-) Foot 2, as a proof-of-concept, showed the advantage of using the explosive elastic actuator capable of delivering the full ankle torques ( $$\pm 120$$ ± 120 Nm) and power ( $$\pm 250$$ ± 250 W) with only a 60 W motor. In this article, the authors present the AMP-Foot 3, using an improved actuation method and using two locking mechanisms for improved energy storage during walking. The article focusses on the mechanical design of the device and validation of its working principle.

The rubber hand illusion is an experimental paradigm in which participants consider a fake hand to be part of their body. This paradigm has been used in many domains of psychology (i.e. research on pain, body ownership, agency) and is of clinical importance. The classic rubber hand paradigm nevertheless suffers from limitations, such as the absence of active motion or the reliance on approximate measurements, which makes strict experimental conditions difficult to obtain. Here, we report on the development of a novel technology—a robotic, user- and computer-controllable hand—that addresses many of the limitations associated with the classic rubber hand paradigm. Because participants can actively control the robotic hand, the device affords higher realism and authenticity. Our robotic hand has a comparatively low cost and opens up novel and innovative methods. In order to validate the robotic hand, we have carried out three experiments. The first two studies were based on previous research using the rubber hand, while the third was specific to the robotic hand. We measured both sense of agency and ownership. Overall, results show that participants experienced a “robotic hand illusion” in the baseline conditions. Furthermore, we also replicated previous results about agency and ownership., SCOPUS: ar.j, info:eu-repo/semantics/published

There is a growing need to assist those who have suffered an amputation due to vascular diseases, especially in those who have general lower limb weakness and need additional assistance to retain independence and overall quality of life. The CYBERLEGs system is a new artificial physical and cognitive lower-limb replacement system for dysvascular transfemoral amputees intended for assistance in activities of daily living. By lowering the cognitive and metabolic effort of using a prosthetic system, CYBERLEGs is intended to increase the number of amputees using prosthetic systems as well as expand the capabilities of those who use currently available technology.