A Combination of Theta*, ORCA and Push and Rotate for Multi-agent Navigation

TL;DR

This paper presents a multi-agent navigation system combining Theta*, ORCA*, and Push and Rotate algorithms to improve collision avoidance and deadlock prevention in static environments without centralized control.

Contribution

It introduces an integrated navigation pipeline that effectively combines path planning, collision avoidance, and local multi-agent path planning to reduce deadlocks and enhance agent goal achievement.

Findings

Significant reduction in deadlocks compared to collision-avoidance only methods.

More agents successfully reach their goals in simulation.

The pipeline effectively handles narrow passages and confined areas.

Abstract

We study the problem of multi-agent navigation in static environments when no centralized controller is present. Each agent is controlled individually and relies on three algorithmic components to achieve its goal while avoiding collisions with the other agents and the obstacles: i) individual path planning which is done by Theta* algorithm; ii) collision avoidance while path following which is performed by ORCA* algorithm; iii) locally-confined multi-agent path planning done by Push and Rotate algorithm. The latter component is crucial to avoid deadlocks in confined areas, such as narrow passages or doors. We describe how the suggested components interact and form a coherent navigation pipeline. We carry out an extensive empirical evaluation of this pipeline in simulation. The obtained results clearly demonstrate that the number of occurring deadlocks significantly decreases enabling more agents to reach their goals compared to techniques that rely on collision-avoidance only and do not include multi-agent path planning component