An optimal approach to anytime task and path planning for autonomous mobile robots in dynamic environments

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

The study of combined task and path planning has mainly focused on feasibility planning for high-dimensional, complex manipulation problems. Yet the integration of symbolic reasoning capabilities with geometric knowledge can address optimal planning in lower dimensional problems. This paper presents a dynamic, anytime task and path planning approach that enables mobile robots to autonomously adapt to changes in the environment. The planner consists of a path planning layer that adopts a multi-tree extension of the optimal Transition-based Rapidly-Exploring Random Tree algorithm to simultaneously find optimal paths for all movement actions. The corresponding path costs, derived from a cost space function, are incorporated into the symbolic representation of the problem to guide the task planning layer. Anytime planning provides continuous path quality improvements, which subsequently updates the high-level plan. Geometric knowledge of the environment is preserved to efficiently re-plan both at the task and path planning level. The planner is evaluated against existing methods for static planning problems, showing that it is able to find higher quality plans without compromising planning time. Simulated deployment of the planner in a partially-known environment demonstrates the effectiveness of the dynamic, anytime components.
Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems - 20th Annual Conference, TAROS 2019, Proceedings
Subtitle of host publication20th Annual Conference, TAROS 2019, London, UK, July 3–5, 2019, Proceedings, Part II
EditorsKaspar Althoefer, Jelizaveta Konstantinova, Ketao Zhang
Place of PublicationCham
Pages155-166
Number of pages12
DOIs
Publication statusPublished - 8 Aug 2019

Publication series

NameLecture Notes in Computer Science
Volume11650
ISSN (Print)0302-9743

Keywords

  • robotics
  • autonomous systems
  • task planning
  • path planning
  • combined task and motion planning
  • dynamic planning

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  • Cite this

    Wong, C., Yang, E., Yan, X-T., & Gu, D. (2019). An optimal approach to anytime task and path planning for autonomous mobile robots in dynamic environments. In K. Althoefer, J. Konstantinova, & K. Zhang (Eds.), Towards Autonomous Robotic Systems - 20th Annual Conference, TAROS 2019, Proceedings: 20th Annual Conference, TAROS 2019, London, UK, July 3–5, 2019, Proceedings, Part II (pp. 155-166). (Lecture Notes in Computer Science; Vol. 11650). Cham. https://doi.org/10.1007/978-3-030-25332-5_14