Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks

By Hang Ma, Jiaoyang Li, T. K. Satish Kumar, Sven Koenig. Adaptive Agents and Multi-Agent Systems, 2017

331 citations recorded by the source corpus.

The multi-agent path-finding (MAPF) problem has recently received a lot of attention. However, it does not capture important characteristics of many real-world domains, such as automated warehouses, where agents are constantly engaged with new tasks. In this paper, we therefore study a lifelong version of the MAPF problem, called the multi-agent pickup and delivery (MAPD) problem. In the MAPD problem, agents have to attend to a stream of delivery tasks in an online setting. One agent has to be assigned to each delivery task. This agent has to first move to a given pickup location and then to a given delivery location while avoiding collisions with other agents. We present two decoupled MAPD algorithms, Token Passing (TP) and Token Passing with Task Swaps (TPTS). Theoretically, we show that they solve all well-formed MAPD instances, a realistic subclass of MAPD instances. Experimentally, we compare them against a centralized strawman MAPD algorithm without this guarantee in a simulated warehouse system. TP can easily be extended to a fully distributed MAPD algorithm and is the best choice when real-time computation is of primary concern since it remains efficient for MAPD instances with hundreds of agents and tasks. TPTS requires limited communication among agents and balances well between TP and the centralized MAPD algorithm.

Subfields: Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/792f19f137323e335b144e548465d483b9786068

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In Computer Vision and Pattern Recognition

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Peter James Stuckey

Citations in the corpus

Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks (2019, methodology): “Inspired by real-world autonomous warehouse applications, recent MAPF papers also experimented with grids shaped to be similar to an automated warehouse, with long corridors (Ma et al. 2017; Cohen et al. 2018a).”
Lifelong Multi-Agent Path Finding in Large-Scale Warehouses (2020, methodology): “For example, one needs to force the agents to “hold” their goal locations (Ma et al. 2017) or plan “dummy paths” for the agents (Liu et al. 2019) after they reach their goal locations.”
Searching with Consistent Prioritization for Multi-Agent Path Finding (2018, background): “…(MAPF) is a coordination problem that arises in many applications, such as for aircrafttowing vehicles (Morris et al. 2016), warehouse and office robots (Wurman, D’Andrea, and Mountz 2008; Veloso et al. 2015), game characters (Ma et al. 2017c), and other multiagent systems (Ma et al. 2017a).”