Towards long-term autonomy based on temporal planning

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

Abstract

This paper investigates the application of temporal planning to multiple robots in long-term missions, using the OPTIC and POPF temporal planners. We design a new planning domain, motivated by a realistic indoor-outdoor scenario. In particular, we investigate plan concurrency, makespan and plan generation time in the multi-robot problem and propose a schema which has been shown to improve plan quality while significantly reducing planning time for the multi-agent problem. Experiments are done in simulation using ROS and Gazebo, and demonstrated in missions with concurrent actions. The ROSPlan framework is also extended to work with multiple robots and used to integrate the planners in ROS. OPTIC provides the best overall solution considering the domain complexity and mission execution in the environment.

Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems
Subtitle of host publicationTAROS 2019
EditorsKaspar Althoefer, Jelizaveta Konstantinova, Ketao Zhang
PublisherSpringer
Pages143-154
Number of pages12
ISBN (Electronic)9783030253325
ISBN (Print)9783030253318
DOIs
Publication statusPublished - 17 Jul 2019
Event20th Towards Autonomous Robotic Systems Conference 2019 - London, United Kingdom
Duration: 3 Jul 20195 Jul 2019

Publication series

NameLecture Notes in Artificial Intelligence
Volume11650
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Towards Autonomous Robotic Systems Conference 2019
Abbreviated titleTAROS 2019
CountryUnited Kingdom
CityLondon
Period3/07/195/07/19

Keywords

  • Long-term autonomy
  • Multi-agent
  • Temporal-planning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Carreno, Y., Petrick, R. P. A., & Petillot, Y. (2019). Towards long-term autonomy based on temporal planning. In K. Althoefer, J. Konstantinova, & K. Zhang (Eds.), Towards Autonomous Robotic Systems: TAROS 2019 (pp. 143-154). (Lecture Notes in Artificial Intelligence; Vol. 11650). Springer. https://doi.org/10.1007/978-3-030-25332-5_13