A Combination of Theta*, ORCA and Push and Rotate for Multi-agent Navigation
This addresses the problem of deadlocks in decentralized multi-agent navigation for applications like robotics, though it is incremental as it combines existing algorithms.
The paper tackles multi-agent navigation in static environments without centralized control by combining Theta* for path planning, ORCA* for collision avoidance, and Push and Rotate for deadlock resolution in confined areas, resulting in significantly fewer deadlocks and more agents reaching their goals compared to collision-avoidance-only methods.
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