Collision Avoidance in Model Predictive Control using Velocity Damper

Arthur Haffemayer (1, 2, 3) , Armand Jordana (4) , Ludovic de Matteis (3) , Krzysztof Wojciechowski (3) , Florent Lamiraux (3) , Nicolas Mansard (3, 1)

1 UT3 - Université Toulouse III - Paul Sabatier
2 Continental Automotive France [Toulouse]
3 LAAS-GEPETTO - Équipe Mouvement des Systèmes Anthropomorphes
4 MiM - Machines in Motion Laboratory, New York University, USA

We propose an advanced method for controlling the motion of a manipulator robot with strict collision avoidance in dynamic environments, leveraging a velocity damper constraint. Unlike conventional distance-based constraints, which tend to saturate near obstacles to reach optimality, the velocity damper constraint considers both distance and relative velocity, ensuring a safer separation. This constraint is incorporated into a model predictive control framework and enforced as a hard constraint through analytical derivatives supplied to the numerical solver. The approach has been fully implemented on a Franka Emika Panda robot and validated through experimental trials, demonstrating effective collision avoidance during dynamic tasks and robustness to unmodeled disturbances. An efficient open-source implementation along examples are provided here: https://gepettoweb.laas.fr/articles/ haffemayer2025.html.

Domaines: Robotique [cs.RO]

Arthur Haffemayer, Armand Jordana, Ludovic de Matteis, Krzysztof Wojciechowski, Florent Lamiraux, et al.. Collision Avoidance in Model Predictive Control using Velocity Damper. 2024. ⟨hal-04707324v1⟩