2025/12/09 by Pustilnik, Mark, Borrelli, Francesco
Engineering · Computer Science · #Robot Manipulation and Learning #Distributed Control Multi-Agent Systems #Reinforcement Learning in Robotics
paper · doi:10.48550/arxiv.2512.08688
This paper proposes a dynamic game formulation for cooperative human-robot navigation in shared workspaces with obstacles, where the human and robot jointly satisfy shared safety constraints while pursuing a common task. A key contribution is the introduction of a non-normalized equilibrium structure for the shared constraints. This structure allows the two agents to contribute different levels of effort towards enforcing safety requirements such as collision avoidance and inter-players spacing. We embed this non-normalized equilibrium into a receding-horizon optimal control scheme.