Improving Motor Coordination in HRI with Bio-Inspired Controllers

International audienceGestural communication is an important aspect of HRI in social, assistance and rehabilitation robotics. Indeed, social synchrony is a key component of interpersonal interactions which affects the interaction at a behavioral level, as well as at a social level. It is therefore paramount for the robot to be able to adapt to its interaction partner, at the risk of experiencing an awkward interaction. Bio-inspired controllers endowed with plasticity mechanisms can be employed in order to make these interactions as natural and enjoyable as possible. Integrating adaptive properties can lead to the emergence of motor coordination and hence to social synchrony. A non-negligible aspect of the work consists in studying humans in HRI to understand human behavior better and design better interactions. On the long term, this could be quite useful for improved robot-assisted motor therapy

Real Time Movement Classification in Versatile CPG Control

International audienceEveryday human tasks are composed of a succession of discrete and rhythmic movements. If we want robots to be able to interact appropriately , it appears paramount for them to be able to perform both types of movements too. Though Central Pattern Generators (CPGs) are usually employed for rhythmic movement generation, they are also able of producing discrete movements. In this paper , we present a classification method to distinguish rhythmic and discrete movements so that the CPG can switch from one mode to the other. Moreover, we introduce several new plasticity rules more suitable for discrete movements

CPG-based Controllers can Generate Both Discrete and Rhythmic Movements

International audienceComplex tasks require the combination of both discrete and rhythmic movements. Though scientists do not yet agree on the neural architecture involved in both types and in the transition from one to the other, the importance of having robot controllers able to behave rhythmically and discretely is universally recognized. In this paper, a bio-inspired robot controller based on oscillating neurons is proposed to realize both discrete and rhythmic movements and easily transition from one to the other. It is shown that, under certain parameter conditions, the CPG controller behaves like a PID controller. In order to demonstrate the feasibility of controlling both discrete and rhythmic movements, the CPG is applied to the initiation of handshaking, namely, reach towards the human hand and start to shake it. Results show that this architecture is suitable for both discrete and rhythmic movements and can easily transition from one to the other

Real Time Movement Classification in Versatile CPG Control

International audienceEveryday human tasks are composed of a succession of discrete and rhythmic movements. If we want robots to be able to interact appropriately , it appears paramount for them to be able to perform both types of movements too. Though Central Pattern Generators (CPGs) are usually employed for rhythmic movement generation, they are also able of producing discrete movements. In this paper , we present a classification method to distinguish rhythmic and discrete movements so that the CPG can switch from one mode to the other. Moreover, we introduce several new plasticity rules more suitable for discrete movements

CPG-based Controllers can Trigger the Emergence of Social Synchrony in Human-Robot Interactions

International audienceSynchronization is an indissociable part of social interactions between humans, especially in gestural communication. With the emergence of social robotics and assistance robots, it becomes paramount for robots to be socially accepted and for humans to be able to connect with them. As a consequence, synchronization mechanisms should be inherent to any robot controllers, allowing the adaption to the interacting partner in any rhythmic way necessary. In this paper, plastic Central Pattern Generators (CPG) have been implemented in the joints of the robot Pepper that has to learn to wave back at a human partner. Results show that the CPG-based controller leads to adaptive waving synchronized with the human partner, thus proving that the CPG-based controller can achieve synchronization

The Sound of Actuators in Children with ASD, Beneficial or Disruptive?

International audienceIt is often overlooked in human-robot gestural interactions that, robot produce sound when they move. That aspect might be either beneficial or detrimental to the interaction, but it should be taken into account, especially in the context of robot-assisted therapy. In this paper, we therefore considered sensory perception in the case of typically developing children and children with Autistic Spectrum Disorders and designed a pilot study with twenty participants to evaluate the impact the sound of actuators has on a rhythmic gestural interaction. Participants were asked to perform a waving-like gesture back at a robot in three different conditions: with visual perception only, auditory perception only and both perceptions. We analyze coordination performance and focus of gaze in each condition. Preliminary results indicate that the sound of actuators might be beneficial for children with autism and only slightly disruptive for typically developing children

Hebbian Plasticity in CPG Controllers Facilitates Self-Synchronization for Human-Robot Handshaking

It is well-known that human social interactions generate synchrony phenomena which are often unconscious. If the interaction between individuals is based on rhythmic movements, synchronized and coordinated movements will emerge from the social synchrony. This paper proposes a plausible model of plastic neural controllers that allows the emergence of synchronized movements in physical and rhythmical interactions. The controller is designed with central pattern generators (CPG) based on rhythmic Rowat-Selverston neurons endowed with neuronal and synaptic Hebbian plasticity. To demonstrate the interest of the proposed model, the case of handshaking is considered because it is a very common, both physically and socially, but also, a very complex act in the point of view of robotics, neuroscience and psychology. Plastic CPGs controllers are implemented in the joints of a simulated robotic arm that has to learn the frequency and amplitude of an external force applied to its effector, thus reproducing the act of handshaking with a human. Results show that the neural and synaptic Hebbian plasticity are working together leading to a natural and autonomous synchronization between the arm and the external force even if the frequency is changing during the movement. Moreover, a power consumption analysis shows that, by offering emergence of synchronized and coordinated movements, the plasticity mechanisms lead to a significant decrease in the energy spend by the robot actuators thus generating a more adaptive and natural human/robot handshake

Améliorer la coordination motrice dans les interactions Homme-Robot avec des contrôleurs bio-inspirés

Gestural communication is an important aspect of HRI in social, assistance and rehabilitation robotics. Indeed, social synchrony is a key component of interpersonal interactions which affects the interaction on the behavioural level, as well as on the social level. It is paramount for the robot to be able to adapt to its interaction partner. In rhythmic social interactions, humans experience two physical phenomena which can also be observed in oscillators: the magnet effect which entrains both systems until they are coupled and synchronised; the maintenance effect which is the struggle of each system to conserve its own intrinsic frequency. These mechanisms could play a fundamental role in physical and social interpersonal interactions. To reproduce this behaviour, bio-inspired controllers endowed with plasticity mechanisms can be employed. The main goal consists in making these interactions as natural and enjoyable as possible by integrating adaptive properties, which leads to the emergence of motor coordination and hence social synchrony. A non-negligible part of this research also consists in studying humans in HRI to understand human behaviour better and design better interactions. In the first part of this thesis, we will introduce synchrony in interpersonal interactions but also in human-robot interactions. We will also observe and endeavour to understand human behaviour in rhythmic human-robot interactions. The second part will present the bio-inspired controller. We will integrate some new plasticity mechanisms, develop its discrete functioning mode and extend the model so that it can adapt to any rhythmic or discrete movement. We also analyse the results of a comparison study with other oscillators and controllers to highlight the capabilities of this model. Moreover, we will validate the controller experimentally in two user studies on human-robot interactions with and without contact. This chapter will evaluate several aspects, such as robot power consumption, controller learning rate, human muscular effort, user perception, coordination performance and engagement. Finally, the third part will focus on the applications and perspectives of this thesis in robot- assisted therapy for children with motor deficits, notably with autistic children.La communication gestuelle est un aspect important de l’interaction humain-robot pour la robotique sociale, d’assistance et de réhabilitation. En effet, la synchronie sociale est un élément clé des interactions interpersonnelles, aussi bien sur le plan comportemental que sur le plan social. Il est essentiel pour les robots d’être capables de s’adapter à leur partenaire d’interaction. Dans les interactions sociales rythmiques, les humains sont soumis à deux phénomènes physiques qui peuvent également être observés dans les oscillateurs: l’effet magnet qui entraîne les deux systèmes jusqu’à ce qu’ils soient couplés et synchronisés; l’effet maintenance qui représente l’effort de chaque système pour conserver sa propre fréquence. Ces mécanismes jouent un rôle fondamental dans les interactions interpersonnelles physiques et sociales. Afin de reproduire ce comportement, des contrôleurs bio-inspirés dotés de mécanismes de plasticité peuvent être employés. Le but principal consiste à rendre ces interactions aussi naturelles et agréables que possible en intégrant des propriétés adaptatives, ce qui mène à l’émergence d’une coordination motrice et par conséquent d’une synchronie sociale. Une partie non négligeable du travail de recherche consiste à étudier l’humain dans les interactions humain-robot pour comprendre le comportement humain et donc mieux penser les interactions. La première partie de cette thèse focalisera sur l’interaction humain-robot avec et sans contact. Nous introduirons plusieurs études d’interaction humain-robot où nous observerons le comportement humain lors d’une interaction rythmique avec un robot. Dans la seconde partie, nous tenterons de reproduire le comportement humain grâce à un contrôleur bio-inspiré. Nous allons également présenter le contrôleur CPG (Central Pattern Generator). Les CPGs sont des structures biologiques présentes dans la moelle épinière des vertébrés et responsables de la génération de mouvements rythmiques. Ils peuvent générer un mouvement sans aucun signal d’entrée et s’adapter à un signal extérieur. Nous avons également intégré de nouveaux mécanismes de plasticité et présentons les résultats d’une étude comparative avec d’autres modèles d’oscillateurs pour souligner les capacités du modèle. Dans la troisième partie, nous testons le contrôleur lors d’interactions humain-robot pour évaluer la performance et la perception du contrôleur. Finalement, la dernière partie dévoilera les applications et perspectives de cette thèse pour la thérapie assistée par robot et plus particulièrement avec des enfants autistes

Motor Imitation:Bio-Inspired vs Direct Geometric Control

Achieving pose imitation with robots is a quite popular topic in robotics. It is widely used for children therapy, notably autistic children, but also to teach new actions to robots. While a lot of very effective methods exist for pose imitation, most of these rely on supplementary equipment for motion capture which rule out a natural interaction and even prevent an interaction which could take place outside of the laboratory.In this paper, we propose a bio-inspired method to achieve imitation with minimal equipment, relying solely on the information provided by the robot Pepper 2D camera. To do so, we perform 2D pose estimation using OpenPose to infer the 3D pose estimation of the human. Using this information, we performed rhythmic and discrete pose imitation using CPG (Central Pattern Generators) controllers endowed with plasticity mechanisms and compared this method with a geometric control approach. Although CPG control has been used previously for rhythmic tasks, it has never been, to our knowledge, been used for imitation

What Kind of Player are You? Continuous Learning of a Player Profile for Adaptive Robot Teleoperation

Play is important for child development and robot-assisted play is very popular in Human-Robot Interaction as it creates more engaging and realistic setups for user studies. Adaptive game-play is also an emerging research field and a good way to provide a personalized experience while adapting to individual user’s needs. In this paper, we analyze joystick data and investigate player learning during a robot navigation game. We collected joystick data from healthy adult participants playing a game with our custom robot MyJay, while participants teleoperated the robot to perform goal-directed navigation. We evaluated the performance of both novice and proficient joystick users. Based on this analysis, we propose some robot learning mechanisms to provide a personalized game experience. Our findings can help improving human-robot interaction in the context of teleoperation in general, and could be particularly impactful for children with disabilities who have problems operating off-the-shelf joysticks