LUE C-SHIFT (2019-2022)

C-SHIFT

(LUE IMPACT; 2019-2022)

This project is an excellence action of the French PIA project “Lorraine University of Excellence” (LUE, ANR-15-IDEX-04-LUE) concerning the Factory of the Future. It is a multi-disciplinary project involving 6 different laboratories (LORIA, CRAN, DEVAH, PERSEUS, CEREFIGE, DITEX) around the theme “Impact of of intelligent collaborative devices such as cobots in the service of human activity at work”. Our research, in collaboration with CRAN, addresses the following questions: how to estimate the human status during a continuous role exchange? How can the robot adapt to this role exchange (leader/follower)? How to design and evaluate decision-making algorithms that make the robot adaptively execute the right action in response to the human’s current and predicted action? How to evaluate if the robot adaptation is beneficial to the collaboration, and how to design efficient adaptive robot control algorithms? Our aim is to experimentally prove if the mutual robot/human adaptation converges in time, leading to an “optimal” collaboration, and if such equilibrium exists, if it is convient for the human in terms of ergonomics/health and to the task in terms of performance.

Our team

Serena Ivaldi, Alexis Aubry (CRAN), Lorenzo Vianello (PhD)

Short video about the project (in French)

Main publications

  • Vianello, L.; Gomes, W.; Stulp, F.; Aubry, A.; Maurice, P.; Ivaldi, S. (2022) Latent Ergonomics Maps: Real-Time Visualization of Estimated Ergonomics of Human Movements. Sensors. 22(11), 3981; https://doi.org/10.3390/s22113981
  • Vianello, L.; Penco, L.; Gomes, W.; You, Y.; Anzalone, S. M.; Maurice, P.; Thomas, V.; Ivaldi, S. (2021) Human-Humanoid Interaction and Cooperation: a Review. Current Robotics Reports. https://doi.org/10.1007/s43154-021-00068-z
  • Vianello, L.; Mouret, J.-B.; Dalin, S.; Aubry, A.; Ivaldi, S. (2021) Human Posture Prediction during Physical Human-Robot Interaction. IEEE Robotics and Automation Letters. https://doi: 10.1109/LRA.2021.3086666 .
    Selected for presentation at HUMANOIDS 2020. Best Interactive Paper Award finalist.