The SHAARE associate team is created in 2024 between the IRiS lab at KAIST and the Auctus team at Inria, to share our complementary methodological orientations in haptic shared control. Together, we aim at developing shared-control approaches that, either, better guide the human through adaptive haptic guidance, or adjust the robot behavior according to the human gestures. The IRiS lab develops virtual-fixture feedback, generated from a task description given by the user. Our partner also … [Read More]

Context Recent progresses in robotics, which tend toward assistive systems or versatile collaborative robots, could make a reorganization of industrial sites possible in order to preserve the health of human workers, by improving their working conditions, while enhancing the value of human expertise and skills. Such a transformation of work requires to rethink robotic control approaches, both in terms of safety and physical capabilities, to enable the robots to help humans in their activity and … [Read More]

Paper Abstract Robots require the ability to autonomously and continuously react to unexpected online changes in the task definition and in the environment, especially those cohabited with humans. To react to these changes, the task, from the current state up to the finish, must instantly be reconsidered. This implies a prohibitive re-computation cost. This paper proposes a modular control architecture based on Model Predictive Control, that offers a good compromise between optimally achieving … [Read More]

This collaborative project started in 2021 between the AUCTUS team at Inria, the RoBioSS team at the Pprime Institute (CNRS), and the Interaction team at the CeRCA laboratory (CNRS). It is co-funded by the ASAP-HRC young-researcher ANR grant and the Perception-HRI Nouvelle-Aquitaine Regional Aid. It aims at rethinking Autonomy for Shared Action and Perception in Human-Robot Collaboration, through transverse studies in robotics and cognitive sciences. Three scientific axes are studied to develop … [Read More]

Paper Abstract Efficient workspace sharing of collaborative robots and human operators remains an unsolved problem in the industry. This problem goes beyond the use of a priori or a posteriori safety measures and has to be tackled at the control level. To address the need of adaptation to human presence as well as to endow the robot with the ability to adapt interactively to new Cartesian targets, a linear Model Predictive Controller is proposed in this paper. This controller computes … [Read More]