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Multi-Robot Motion Planning for Unit Discs with Revolving Areas

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

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Author Details

Pankaj K. Agarwal
  • Duke University, Durham NC, USA
Tzvika Geft
  • Tel Aviv University, Israel
Dan Halperin
  • Tel Aviv University, Israel
Erin Taylor
  • Duke University, Durham, NC, USA

Funding

Work by Pankaj K. Agarwal and Erin Taylor is supported by IIS-1814493, CCF-2007556, and CCF-2223870. Work by Dan Halperin and Tzvika Geft has been supported in part by the Israel Science Foundation (grant no. 1736/19), by NSF/US-Israel-BSF (grant no. 2019754), by the Israel Ministry of Science and Technology (grant no. 103129), by the Blavatnik Computer Science Research Fund, and by the Yandex Machine Learning Initiative for Machine Learning at Tel Aviv University.

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Pankaj K. Agarwal, Tzvika Geft, Dan Halperin, and Erin Taylor. Multi-Robot Motion Planning for Unit Discs with Revolving Areas. In 33rd International Symposium on Algorithms and Computation (ISAAC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 248, pp. 35:1-35:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.ISAAC.2022.35

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 n log log n)-approximation algorithm for this problem.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Theory of computation → Design and analysis of algorithms
Keywords
  • motion planning
  • optimal motion planning
  • approximation
  • complexity
  • NP-hardness

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References

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