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

• Main Authors: Dergachev, Stepan, Yakovlev, Konstantin, Prakapovich, Ryhor
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: arXiv 2020
• Subjects: Multiagent Systems cs.MA; Artificial Intelligence cs.AI; FOS Computer and information sciences; I.2.11; I.2.8; I.2.9; Orca
• Online Access: https://dx.doi.org/10.48550/arxiv.2008.01227; https://arxiv.org/abs/2008.01227

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 : This is a preprint of the paper accepted to ICR'20. It contains 12 pages and 7 figures