Partial Order Temporal Plan Merging for Mobile Robot Tasks

Lenka Mudrova, Bruno Lacerda, Nick Hawes

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

3 Citations (Scopus)
57 Downloads (Pure)

Abstract

For many mobile service robot applications, planning problems are based on deciding how and when to navigate to certain locations and execute certain tasks. Typically, many of these tasks are independent from one another, and the main objective is to obtain plans that efficiently take into account where these tasks can be executed and when execution is allowed. In this paper, we present
an approach, based on merging of partial order plans with durative actions, that can quickly and effectively generate a plan for a set of independent goals. This plan exploits some of the synergies of the plans for each single task, such as common locations where certain actions should be executed. We evaluate our approach in benchmarking domains, comparing it with state-of-the-art planners and showing how it provides a good trade-off between the approach of sequencing the plans for each task (which is fast but produces poor results), and
the approach of planning for a conjunction of all the goals (which is slow but produces good results).
Original languageEnglish
Title of host publicationProceedings of 22nd European Conference on Artificial Intelligence (ECAI 2016)
PublisherIOS Press
Pages1537-1545
Number of pages9
DOIs
Publication statusPublished - Sept 2016
Event22nd European Conference on Artificial Intelligence (ECAI 2016) - The Hague, Netherlands
Duration: 29 Aug 20162 Sept 2016

Publication series

Name Frontiers in Artificial Intelligence and Applications
PublisherIOP
Volume285

Conference

Conference22nd European Conference on Artificial Intelligence (ECAI 2016)
Country/TerritoryNetherlands
CityThe Hague
Period29/08/162/09/16

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