Real-time Safe Interval Path Planning

Devin Wild Thomas, Wheeler Ruml, Solomon Eyal Shimony

Research output: Contribution to journalConference articlepeer-review

Abstract

Navigation among dynamic obstacles is a fundamental task in robotics that has been modeled in various ways. In Safe Interval Path Planning, location is discretized to a grid, time is continuous, future trajectories of obstacles are assumed known, and planning takes place offline. In this work, we define the Real-time Safe Interval Path Planning problem setting, in which the agent plans online and must issue its next action within a strict time bound. Unlike in classical realtime heuristic search, the cost-to-go in Real-time Safe Interval Path Planning is a function of time rather than a scalar. We present several algorithms for this setting and prove that they learn admissible heuristics. Empirical evaluation shows that the new methods perform better than classical approaches under a variety of conditions.

Original languageEnglish
Pages (from-to)161-169
Number of pages9
JournalThe International Symposium on Combinatorial Search
Volume17
Issue number1
DOIs
StatePublished - 1 Jan 2024
Event17th International Symposium on Combinatorial Search, SoCS 2024 - Kananaskis, Canada
Duration: 6 Jun 20248 Jun 2024

ASJC Scopus subject areas

  • Computer Networks and Communications

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