RLSS: Real-time Multi-Robot Trajectory Replanning using Linear Spatial Separations
This addresses safety and efficiency for multi-robot systems in constrained environments, representing a novel method for a known bottleneck.
The paper tackled real-time trajectory replanning for multi-robot teams in dynamic environments by introducing RLSS, which uses linear spatial separations to enforce safety without communication, resulting in significantly fewer collisions and effective deadlock avoidance compared to a state-of-the-art MPC-based method.
Trajectory replanning is a critical problem for multi-robot teams navigating dynamic environments. We present RLSS (Replanning using Linear Spatial Separations): a real-time trajectory replanning algorithm for cooperative multi-robot teams that uses linear spatial separations to enforce safety. Our algorithm handles the dynamic limits of the robots explicitly, is completely distributed, and is robust to environment changes, robot failures, and trajectory tracking errors. It requires no communication between robots and relies instead on local relative measurements only. We demonstrate that the algorithm works in real-time both in simulations and in experiments using physical robots. We compare our algorithm to a state-of-the-art online trajectory generation algorithm based on model predictive control, and show that our algorithm results in significantly fewer collisions in highly constrained environments, and effectively avoids deadlocks.