Analysis Of The Anytime MAPF Solvers Based On The Combination Of Conflict-Based Search (CBS) and Focal Search (FS)

TL;DR

This paper analyzes and compares different anytime MAPF algorithms based on Conflict-Based Search (CBS) combined with Focal Search (FS), highlighting their performance differences and potential benefits in various scenarios.

Contribution

It provides a comprehensive analysis of the performance of CBS variants using Focal Search at different levels, including a new version applying FS on both levels, and compares their effectiveness.

Findings

Using FS on both levels of CBS can be beneficial in many setups.

The behavior of the new double-FS CBS variant differs significantly from Anytime BCBS.

Head-to-head comparison shows advantages of the double-FS approach in diverse scenarios.

Abstract

Conflict-Based Search (CBS) is a widely used algorithm for solving multi-agent pathfinding (MAPF) problems optimally. The core idea of CBS is to run hierarchical search, when, on the high level the tree of solutions candidates is explored, and on the low-level an individual planning for a specific agent (subject to certain constraints) is carried out. To trade-off optimality for running time different variants of bounded sub-optimal CBS were designed, which alter both high- and low-level search routines of CBS. Moreover, anytime variant of CBS does exist that applies Focal Search (FS) to the high-level of CBS - Anytime BCBS. However, no comprehensive analysis of how well this algorithm performs compared to the naive one, when we simply re-invoke CBS with the decreased sub-optimality bound, was present. This work aims at filling this gap. Moreover, we present and evaluate another anytime version of CBS that uses FS on both levels of CBS. Empirically, we show that its behavior is principally different from the one demonstrated by Anytime BCBS. Finally, we compare both algorithms head-to-head and show that using Focal Search on both levels of CBS can be beneficial in a wide range of setups.