Replanning for Situated Robots

Michael Cashmore, Andrew Ian Coles, Bence Cserna, Erez Karpas, Daniele Magazzeni, Wheeler Ruml

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

16 Citations (Scopus)
63 Downloads (Pure)

Abstract

Planning enables intelligent agents, such as robots, to act so as to achieve their long term goals. To make the planning process tractable, a relatively low fidelity model of the world is often used, which sometimes leads to the need to replan. The typical view of replanning is that the robot is given the current state, the goal, and possibly some data from the previous planning process. However, for robots (or teams of robots) that exist in continuous physical space, act concurrently, have deadlines, or must otherwise consider durative actions, things are not so simple. In this paper, we address the problem of replanning for situated robots. Relying on previous work on situated temporal planning, we frame the replanning problem as a situated temporal planning problem, where currently executing actions are handled via Timed Initial Literals (TILs), under the assumption that actions cannot be interrupted. We then relax this assumption, and address situated replanning with interruptible actions. We bridge the gap between the low-level model of the robot and the high-level model used for planning by the novel notion of a bail out action generator, which relies on the low-level model to generate highlevel actions that describe possible ways to interrupt currently executing actions. Because actions can be interrupted at different times during their execution, we also propose a novel algorithm to handle temporal planning with time-dependent durations.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling (ICAPS)
PublisherAAAI Press
Number of pages9
Publication statusPublished - 11 Jul 2019

Keywords

  • Temporal Planning
  • Autonomous intelligent agent

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