Near-Optimal Min-Sum Motion Planning for Two Square Robots in a Polygonal Environment

Pankaj K. Agarwal, Dan Halperin, Micha Sharir, Alex Steiger

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

Let W ⊂ R2 be a planar polygonal environment (i.e., a polygon potentially with holes) with a total of n vertices, and let A, B be two robots, each modeled as an axis-aligned unit square, that can translate inside W. Given source and target placements sA, tA, sB, tB ∈ W of A and B, respectively, the goal is to compute a collision-free motion plan π, i.e., a motion plan that continuously moves A from sA to tA and B from sB to tB so that A and B remain inside W and do not collide with each other during the motion. Furthermore, if such a plan exists, then we wish to return a plan that minimizes the sum of the lengths of the paths traversed by the robots. Given W, sA, tA, sB, tB and a parameter ε > 0, we present an (Equation presented)-approximation algorithm for this problem. We are not aware of any polynomial-time algorithm for this problem, nor do we know whether the problem is NP-Hard. Our result is the first polynomial-time (1 + ε)-approximation algorithm for an optimal motion-planning problem involving two robots moving in a polygonal environment.

Original languageEnglish
Pages4942-4962
Number of pages21
DOIs
StatePublished - 2024
Event35th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2024 - Alexandria, United States
Duration: 7 Jan 202410 Jan 2024

Conference

Conference35th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2024
Country/TerritoryUnited States
CityAlexandria
Period7/01/2410/01/24

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