Multi-robot motion planning for unit discs with revolving areas

Pankaj K. Agarwal, Tzvika Geft, Dan Halperin, Erin Taylor*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We study the problem of motion planning for a collection of n labeled unit disc robots in a polygonal environment. We assume that the robots have revolving areas around their start and final positions: that each start and each final is contained in a radius 2 disc lying in the free space, not necessarily concentric with the start or final position, which is free from other start or final positions. This assumption allows a weakly-monotone motion plan, in which robots move according to an ordering as follows: during the turn of a robot R in the ordering, it moves fully from its start to final position, while other robots do not leave their revolving areas. As R passes through a revolving area, a robot R that is inside this area may move within the revolving area to avoid a collision. Notwithstanding the existence of a motion plan, we show that minimizing the total traveled distance in this setting, specifically even when the motion plan is restricted to be weakly-monotone, is APX-hard, ruling out any polynomial-time (1+ε)-approximation algorithm. On the positive side, we present the first constant-factor approximation algorithm for computing a feasible weakly-monotone motion plan. The total distance traveled by the robots is within an O(1) factor of that of the optimal motion plan, which need not be weakly monotone. Our algorithm extends to an online setting in which the polygonal environment is fixed but the initial and final positions of robots are specified in an online manner. Finally, we observe that the overhead in the overall cost that we add while editing the paths to avoid robot-robot collision can vary significantly depending on the ordering we chose. Finding the best ordering in this respect is known to be NP-hard, and we provide a polynomial time O(log⁡nlog⁡log⁡n)-approximation algorithm for this problem.

Original languageEnglish
Article number102019
JournalComputational Geometry: Theory and Applications
Volume114
DOIs
StatePublished - Oct 2023

Funding

FundersFunder number
Blavatnik Computer Science Research Fund
US-Israel-BSF2019754
Yandex Machine Learning Initiative for Machine Learning
National Science Foundation
Israel Science Foundation1736/19
Tel Aviv University
Ministry of Science and Technology, Israel103129

    Keywords

    • Computational geometry
    • Motion planning

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