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

arXiv: https://arxiv.org/abs/1705.10868 · HTML: https://mlsanity.com/paper/1705.10868/

## Key facts

- Cited by 64 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2017.

## Built on by (most cited first, 30 of 64)

- [Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers](https://mlsanity.com/paper/2212.11498/) (2022)
- [Learn to Follow: Decentralized Lifelong Multi-agent Pathfinding via Planning and Learning](https://mlsanity.com/paper/2310.01207/) (2023)
- [Multi-Robot Coordination and Layout Design for Automated Warehousing](https://mlsanity.com/paper/2305.06436/) (2023)
- [Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding](https://mlsanity.com/paper/2308.11234/) (2023)
- [Guidance Graph Optimization for Lifelong Multi-Agent Path Finding](https://mlsanity.com/paper/2402.01446/) (2024)
- [Beyond Robustness: A Taxonomy of Approaches towards Resilient Multi-Robot Systems](https://mlsanity.com/paper/2109.12343/) (2021)
- [Multi-Goal Multi-Agent Pickup and Delivery](https://mlsanity.com/paper/2208.01223/) (2022)
- [Arbitrarily Scalable Environment Generators via Neural Cellular Automata](https://mlsanity.com/paper/2310.18622/) (2023)
- [Cooperative Multi-Agent Path Finding: Beyond Path Planning and Collision Avoidance](https://mlsanity.com/paper/2105.10993/) (2021)
- [Graph-Based Multi-Robot Path Finding and Planning](https://mlsanity.com/paper/2206.11319/) (2022)
- [DC-MRTA: Decentralized Multi-Robot Task Allocation and Navigation in Complex Environments](https://mlsanity.com/paper/2209.02865/) (2022)
- [Deploying Ten Thousand Robots: Scalable Imitation Learning for Lifelong Multi-Agent Path Finding](https://mlsanity.com/paper/2410.21415/) (2024)
- [Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks](https://mlsanity.com/paper/2110.08802/) (2021)
- [Solving Multi-Agent Safe Optimal Control with Distributed Epigraph Form MARL](https://mlsanity.com/paper/2504.15425/) (2025)
- [Optimal and Bounded-Suboptimal Multi-Goal Task Assignment and Path Finding](https://mlsanity.com/paper/2208.01222/) (2022)
- [Double-Deck Multi-Agent Pickup and Delivery: Multi-Robot Rearrangement in Large-Scale Warehouses](https://mlsanity.com/paper/2304.14309/) (2023)
- [Large-Scale Multirobot Coverage Path Planning on Grids With Path Deconfliction](https://mlsanity.com/paper/2411.01707/) (2024)
- [Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART)](https://mlsanity.com/paper/2503.04798/) (2025)
- [A Conflict-Based Search Framework for Multi-Objective Multi-Agent Path Finding](https://mlsanity.com/paper/2101.03805/) (2021)
- [Standby-Based Deadlock Avoidance Method for Multi-Agent Pickup and Delivery Tasks](https://mlsanity.com/paper/2201.06014/) (2022)
- [Improved Anonymous Multi-Agent Path Finding Algorithm](https://mlsanity.com/paper/2312.10572/) (2023)
- [Lightweight and Effective Preference Construction in PIBT for Large-Scale Multi-Agent Pathfinding](https://mlsanity.com/paper/2505.12623/) (2025)
- [Leveraging Experience in Lifelong Multi-Agent Pathfinding](https://mlsanity.com/paper/2202.04382/) (2022)
- [The Multi-Agent Pickup and Delivery Problem: MAPF, MARL and Its Warehouse Applications](https://mlsanity.com/paper/2203.07092/) (2022)
- [MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problem](https://mlsanity.com/paper/2404.19518/) (2024)
- [Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding](https://mlsanity.com/paper/2505.19219/) (2025)
- [Destination-to-Chutes Task Mapping Optimization for Multi-Robot Coordination in Robotic Sorting Systems](https://mlsanity.com/paper/2510.03472/) (2025)
- [Learning-guided Prioritized Planning for Lifelong Multi-Agent Path Finding in Warehouse Automation](https://mlsanity.com/paper/2603.23838/) (2026)
- [A Competitive Analysis of Online Multi-Agent Path Finding](https://mlsanity.com/paper/2106.11454/) (2021)
- [The Study of Highway for Lifelong Multi-Agent Path Finding](https://mlsanity.com/paper/2304.04217/) (2023)

## Abstract (arXiv)

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.