Virtual Traffic Lights for Multi-Robot Navigation: Decentralized Planning with Centralized Conflict Resolution

TL;DR

This paper introduces a hybrid multi-robot coordination system that uses decentralized path planning combined with centralized conflict resolution, functioning as virtual traffic lights to improve success rates and reduce deadlocks.

Contribution

It proposes a novel hybrid framework that integrates decentralized planning with centralized conflict management, functioning as virtual traffic lights for multi-robot navigation.

Findings

Increased success rate of robots reaching goals in simulations.

Reduced deadlocks compared to traditional methods.

Validated in real-world experiments with quadruped robots and Duckiebots.

Abstract

We present a hybrid multi-robot coordination framework that combines decentralized path planning with centralized conflict resolution. In our approach, each robot autonomously plans its path and shares this information with a centralized node. The centralized system detects potential conflicts and allows only one of the conflicting robots to proceed at a time, instructing others to stop outside the conflicting area to avoid deadlocks. Unlike traditional centralized planning methods, our system does not dictate robot paths but instead provides stop commands, functioning as a virtual traffic light. In simulation experiments with multiple robots, our approach increased the success rate of robots reaching their goals while reducing deadlocks. Furthermore, we successfully validated the system in real-world experiments with two quadruped robots and separately with wheeled Duckiebots.