{"id":621,"date":"2021-01-18T12:26:34","date_gmt":"2021-01-18T10:26:34","guid":{"rendered":"http:\/\/members.loria.fr\/PMaurice\/?page_id=621"},"modified":"2024-05-28T10:57:36","modified_gmt":"2024-05-28T08:57:36","slug":"rooibos-2021-2025","status":"publish","type":"page","link":"https:\/\/members.loria.fr\/PMaurice\/rooibos-2021-2025\/","title":{"rendered":"ROOIBOS (2021–2025)"},"content":{"rendered":"

I am the scientific coordinator of the ANR JCJC ROOIBOS, on User-Specific Adaptation of Collaborative Robot Motion for Improved Ergonomics.<\/p>\n

Summary<\/h4>\n

Collaborative robots have the potential to reduce work-related musculoskeletal disorders not only by decreasing the workers’ physical load, but also by modifying and improving their postures. Imposing a sudden modification of one’s movement can however be detrimental to the acceptance and efficacy of the human-robot collaboration. In ROOIBOS, we will develop a framework to plan user-specific trajectories for collaborative robots, to gradually optimize the efficacy of the collaboration and the long-term occupational health of the user. We will use machine learning and probabilistic methods to perform user-specific prediction of whole-body movements. We will define dedicated metrics to evaluate the movement ergonomic performance and intuitiveness. We will integrate those elements in a digital human simulation to plan a progressive adaptation of the robot motion accounting for the user’s motor preferences. We will then use probabilistic decision-making to adapt the plan on-line to the user’s motor adaptation capabilities. This will enable a smooth deployment of collaborative robots at work.<\/p>\n

Loria scientific team<\/h4>\n