RLSS: Real-time Multi-Robot Trajectory Replanning using Linear Spatial Separations

TL;DR

RLSS is a real-time, distributed multi-robot trajectory replanning algorithm that ensures safety and robustness in dynamic environments without inter-robot communication, demonstrated through simulations and physical robot experiments.

Contribution

The paper introduces RLSS, a novel distributed trajectory replanning method using linear spatial separations that operates in real-time without communication between robots.

Findings

Fewer collisions compared to MPC-based algorithms in constrained environments.

Effective deadlock avoidance in dynamic scenarios.

Works in real-time on physical robots and simulations.

Abstract

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.