MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-goal Sequencing and Path Finding
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Abstract (arXiv)
In multi-agent applications such as surveillance and logistics, fleets of mobile agents are often expected to coordinate and safely visit a large number of goal locations as efficiently as possible. The multi-agent planning problem in these applications involves allocating and sequencing goals for each agent while simultaneously producing conflict-free paths for the agents. In this article, we introduce a new algorithm called MS* which computes an optimal solution for this multi-agent problem by fusing and advancing state of the art solvers for multi-agent path finding (MAPF) and multiple travelling salesman problem (mTSP). MS* leverages our prior subdimensional expansion approach for MAPF and embeds the mTSP solvers to optimally allocate and sequence goals for agents. Numerical results show that our new algorithm can solve the multi-agent problem with 20 agents and 50 goals in a minute of CPU time on a standard laptop.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 7 of its 27 references that are in the map. First posted on arXiv 18 Mar 2021.
Builds on
7 of 27 references.
References · 7
- 2019Multi-Agent Pathfinding: Definitions, Variants, and Benchmarkscited by 197
- 2016Optimal Target Assignment and Path Finding for Teams of Agentscited by 24
- 2020Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Orderingcited by 12
- 2019An Optimal Algorithm to Solve the Combined Task Allocation and Path Finding Problemcited by 9
- 2021Subdimensional Expansion for Multi-objective Multi-agent Path Findingcited by 9
- 2021S^*: A Heuristic Information-Based Approximation Framework for Multi-Goal Path Findingcited by 2
- 2015Generalized multiple depot traveling salesmen problem - polyhedral study and exact algorithmcited by 1
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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 3.
8 papers.
- 2024Large-Scale Multirobot Coverage Path Planning on Grids With Path Deconflictioncited by 5
- 2022Standby-Based Deadlock Avoidance Method for Multi-Agent Pickup and Delivery Taskscited by 4
- 2024iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learningcited by 4
- 2023Solving Multi-Agent Target Assignment and Path Finding with a Single Constraint Treecited by 3
- 2024MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problemcited by 3
- 2021Multi-objective Conflict-based Search Using Safe-interval Path Planningcited by 1
- 2021Subdimensional Expansion Using Attention-Based Learning For Multi-Agent Path Findingcited by 0
- 2023DMS*: Minimizing Makespan for Multi-Agent Combinatorial Path Findingcited by 0
- 2024Large-Scale Multirobot Coverage Path Planning on Grids With Path Deconfliction3 Nov 2024
- 2024iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learning1 May 2024
- 2024MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problem30 Apr 2024
- 2023DMS*: Minimizing Makespan for Multi-Agent Combinatorial Path Finding11 Dec 2023
- 2023Solving Multi-Agent Target Assignment and Path Finding with a Single Constraint Tree2 Jul 2023
- 2022Standby-Based Deadlock Avoidance Method for Multi-Agent Pickup and Delivery Tasks16 Jan 2022
- 2021Subdimensional Expansion Using Attention-Based Learning For Multi-Agent Path Finding29 Sep 2021
- 2021Multi-objective Conflict-based Search Using Safe-interval Path Planning2 Aug 2021