db-CBS: Discontinuity-Bounded Conflict-Based Search for Multi-Robot Kinodynamic Motion Planning

TL;DR

This paper introduces db-CBS, a multi-robot kinodynamic motion planner combining conflict-based search and discontinuity-bounded A* to efficiently generate near-optimal trajectories for robots with diverse dynamics in complex environments.

Contribution

The paper presents a novel multi-level planning approach that integrates conflict resolution with kinodynamic motion primitives, improving success rates and solution quality over existing methods.

Findings

Higher success rate in challenging environments

Lower cost solutions compared to state-of-the-art

Capable of handling diverse robot dynamics

Abstract

This paper presents a multi-robot kinodynamic motion planner that enables a team of robots with different dynamics, actuation limits, and shapes to reach their goals in challenging environments. We solve this problem by combining Conflict-Based Search (CBS), a multi-agent path finding method, and discontinuity-bounded A*, a single-robot kinodynamic motion planner. Our method, db-CBS, operates in three levels. Initially, we compute trajectories for individual robots using a graph search that allows bounded discontinuities between precomputed motion primitives. The second level identifies inter-robot collisions and resolves them by imposing constraints on the first level. The third and final level uses the resulting solution with discontinuities as an initial guess for a joint space trajectory optimization. The procedure is repeated with a reduced discontinuity bound. Our approach is anytime, probabilistically complete, asymptotically optimal, and finds near-optimal solutions quickly. Experimental results with robot dynamics such as unicycle, double integrator, and car with trailer in different settings show that our method is capable of solving challenging tasks with a higher success rate and lower cost than the existing state-of-the-art.