Quelles conceptions de la coopération humains‑robots collaboratifs ?

Cet article relate une expérience de participation de chercheures en ergonomie à un projet de recherche de développement d’un démonstrateur de robotique collaborative. Cette contribution empirique est mise en perspective avec des éléments théoriques portant sur les modèles de la coopération dans un système travailleur-robot et la conduite de projet de conception en ergonomie de l’activité. Sur cette base, nous discutons : (1) du modèle de la coopération effectivement réifiée dans le démonstrateur, qui en l’état des développements technologiques incorpore plus un modèle de coordination et non de coopération, en ce sens qu’il ne permet pas de gérer de manière dynamique l’interdépendance entre les tâches du travailleur et du robot ; (2) des apports et limites de la double conduite de projet mise en place (au sein du consortium de recherche et d’une usine). Nous soulignons que la présence de chercheures en ergonomie de l’activité au sein du projet de recherche s’est révélée être une condition nécessaire à la conception d’une technologie potentiellement « préservante » pour la santé et la performance, mais elle n’a en aucun cas été suffisante, car elle n’a pas permis de construite le futur usage socio-organisationnel de la technologie. Ceci appelle des perspectives de recherche permettant de poursuivre ces travaux en s’intéressant de plus près aux processus décisionnels relatifs aux transitions vers une « Industrie du futur » et à leurs accompagnements, dans des perspectives politiques et historico-culturel.This article presents a case study on the participation of activity-centered ergonomics researchers in a collaborative robot development research project. This empirical contribution is grounded in and framed by theoretical aspects relating to models of cooperation in a worker-robot system and to activity-centered ergonomics proposals relating to design project management. We therefore discuss: (1) the model of cooperation which is actually reified in the technology. Given the current potentialities of the technology, this model deals more with coordination than with cooperation, as it does not support dynamic management of the interdependence between worker-robot tasks; (2) the contributions and limits of the dual project management approach set up in the research consortium and in a factory. We stress that participation of ergonomists proved to be a necessary condition for designing a technology that potentially “preserves” health and performance; however, this participation was in no way sufficient as it did not support the future socio-organisational use of the technology. We conclude by highlighting ongoing research issues that focus on the aforementioned point by investigating decision-making processes relating to transitions towards a “Factory of the future” and to their supports, from political and historical-cultural perspectives

Human robot interaction in a crowded environment

Human Robot Interaction (HRI) is the primary means of establishing natural and affective communication between humans and robots. HRI enables robots to act in a way similar to humans in order to assist in activities that are considered to be laborious, unsafe, or repetitive. Vision based human robot interaction is a major component of HRI, with which visual information is used to interpret how human interaction takes place. Common tasks of HRI include finding pre-trained static or dynamic gestures in an image, which involves localising different key parts of the human body such as the face and hands. This information is subsequently used to extract different gestures. After the initial detection process, the robot is required to comprehend the underlying meaning of these gestures [3]. Thus far, most gesture recognition systems can only detect gestures and identify a person in relatively static environments. This is not realistic for practical applications as difficulties may arise from people‟s movements and changing illumination conditions. Another issue to consider is that of identifying the commanding person in a crowded scene, which is important for interpreting the navigation commands. To this end, it is necessary to associate the gesture to the correct person and automatic reasoning is required to extract the most probable location of the person who has initiated the gesture. In this thesis, we have proposed a practical framework for addressing the above issues. It attempts to achieve a coarse level understanding about a given environment before engaging in active communication. This includes recognizing human robot interaction, where a person has the intention to communicate with the robot. In this regard, it is necessary to differentiate if people present are engaged with each other or their surrounding environment. The basic task is to detect and reason about the environmental context and different interactions so as to respond accordingly. For example, if individuals are engaged in conversation, the robot should realize it is best not to disturb or, if an individual is receptive to the robot‟s interaction, it may approach the person. Finally, if the user is moving in the environment, it can analyse further to understand if any help can be offered in assisting this user. The method proposed in this thesis combines multiple visual cues in a Bayesian framework to identify people in a scene and determine potential intentions. For improving system performance, contextual feedback is used, which allows the Bayesian network to evolve and adjust itself according to the surrounding environment. The results achieved demonstrate the effectiveness of the technique in dealing with human-robot interaction in a relatively crowded environment [7]