Collaborative Task Assignment, Sequencing and Multi-agent Path-finding

TL;DR

This paper introduces CBS-TS, an optimal algorithm for collaborative multi-agent task assignment and pathfinding that efficiently combines task sequencing with collision-free path planning, outperforming baseline methods in success rate and optimality.

Contribution

We propose CBS-TS, a novel algorithm that integrates MILP-based task sequencing with conflict-based pathfinding, improving efficiency and optimality in multi-agent task assignment problems.

Findings

CBS-TS outperforms baseline CBSS in success rates

CBS-TS achieves consistently optimal solutions

The method effectively balances task sequencing and collision avoidance

Abstract

In this article, we address the problem of collaborative task assignment, sequencing, and multi-agent pathfinding (TSPF), where a team of agents must visit a set of task locations without collisions while minimizing flowtime. TSPF incorporates agent-task compatibility constraints and ensures that all tasks are completed. We propose a Conflict-Based Search with Task Sequencing (CBS-TS), an optimal and complete algorithm that alternates between finding new task sequences and resolving conflicts in the paths of current sequences. CBS-TS uses a mixed-integer linear program (MILP) to optimize task sequencing and employs Conflict-Based Search (CBS) with Multi-Label A* (MLA*) for collision-free path planning within a search forest. By invoking MILP for the next-best sequence only when needed, CBS-TS efficiently limits the search space, enhancing computational efficiency while maintaining optimality. We compare the performance of our CBS-TS against Conflict-based Steiner Search (CBSS), a baseline method that, with minor modifications, can address the TSPF problem. Experimental results demonstrate that CBS-TS outperforms CBSS in most testing scenarios, achieving higher success rates and consistently optimal solutions, whereas CBSS achieves near-optimal solutions in some cases. The supplementary video is available at https://youtu.be/QT8BYgvefmU.