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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 9: AAAI-22 Technical Tracks 9

Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees

February 1, 2023

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Authors

Christopher Leet

University of Southern California


Jiaoyang Li

University of Southern California


Sven Koenig

University of Southern California


DOI:

10.1609/aaai.v36i9.21170


Abstract:

Modern multi-agent robotic systems increasingly require scalable, robust and persistent Multi-Agent Path Finding (MAPF) with performance guarantees. While many MAPF solvers that provide some of these properties exist, none provides them all. To fill this need, we propose a new MAPF framework, the shard system. A shard system partitions the workspace into geographic regions, called shards, linked by a novel system of buffers. Agents are routed optimally within a shard by a local controller to local goals set by a global controller. The buffer system novelly allows shards to plan with perfect parallelism, providing scalability. A novel global controller algorithm can rapidly generate an inter-shard routing plan for thousands of agents while minimizing the traffic routed through any shard. A novel workspace partitioning algorithm produces shards small enough to replan rapidly. These innovations allow a shard system to adjust its routing plan in real time if an agent is delayed or assigned a new goal, enabling robust, persistent MAPF. A shard system's local optimality and optimized inter-shard routing bring the sum-of-costs of its solutions to single-shot MAPF problems to < 20-60% of optimal on a diversity of workspaces. Its scalability allows it to plan paths for 1000s of agents in seconds. If any of their goals change or move actions fails, a shard system can replan in under a second.

Topics: AAAI

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HOW TO CITE:

Christopher Leet||Jiaoyang Li||Sven Koenig Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees Proceedings of the AAAI Conference on Artificial Intelligence (2022) 9386-9395.

Christopher Leet||Jiaoyang Li||Sven Koenig Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees AAAI 2022, 9386-9395.

Christopher Leet||Jiaoyang Li||Sven Koenig (2022). Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees. Proceedings of the AAAI Conference on Artificial Intelligence, 9386-9395.

Christopher Leet||Jiaoyang Li||Sven Koenig. Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.9386-9395.

Christopher Leet||Jiaoyang Li||Sven Koenig. 2022. Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees. "Proceedings of the AAAI Conference on Artificial Intelligence". 9386-9395.

Christopher Leet||Jiaoyang Li||Sven Koenig. (2022) "Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees", Proceedings of the AAAI Conference on Artificial Intelligence, p.9386-9395

Christopher Leet||Jiaoyang Li||Sven Koenig, "Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees", AAAI, p.9386-9395, 2022.

Christopher Leet||Jiaoyang Li||Sven Koenig. "Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.9386-9395.

Christopher Leet||Jiaoyang Li||Sven Koenig. "Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 9386-9395.

Christopher Leet||Jiaoyang Li||Sven Koenig. Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees. AAAI[Internet]. 2022[cited 2023]; 9386-9395.


ISSN: 2374-3468


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Copyright 2022, Association for the Advancement of
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