QUT ePrints

Choosing landmarks for risky planning

Murphy, Elizabeth, Corke, Peter, & Newman, Paul (2011) Choosing landmarks for risky planning. In Amato, Nancy M. (Ed.) Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Hilton San Francisco, San Francisco, CA, pp. 3868-3873.

View at publisher

Abstract

This work examines the effect of landmark placement on the efficiency and accuracy of risk-bounded searches over probabilistic costmaps for mobile robot path planning. In previous work, risk-bounded searches were shown to offer in excess of 70% efficiency increases over normal heuristic search methods. The technique relies on precomputing distance estimates to landmarks which are then used to produce probability distributions over exact heuristics for use in heuristic searches such as A* and D*. The location and number of these landmarks therefore influence greatly the efficiency of the search and the quality of the risk bounds. Here four new methods of selecting landmarks for risk based search are evaluated. Results are shown which demonstrate that landmark selection needs to take into account the centrality of the landmark, and that diminishing rewards are obtained from using large numbers of landmarks.

Impact and interest:

1 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

36 since deposited on 20 Nov 2011
15 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 47058
Item Type: Conference Paper
Keywords: Accuracy, Approximation Methods, Gaussian Distribution, Path Planning, Planning, Probabilistic Logic, Probability Distribution
DOI: 10.1109/IROS.2011.6048833
ISBN: 9781612844541
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2011 IEEE. All rights reserved.
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 20 Nov 2011 23:38
Last Modified: 30 Aug 2012 19:22

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page