Simultaneous localization and planning on multiple map hypotheses

Morris, Timothy, Dayoub, Feras, Corke, Peter, & Upcroft, Ben (2014) Simultaneous localization and planning on multiple map hypotheses. In Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), IEEE, Chicago, The United States of America, pp. 4531-4536.

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Abstract

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

Impact and interest:

1 citations in Scopus
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1 citations in Web of Science®

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ID Code: 75193
Item Type: Conference Paper
Refereed: Yes
Funders: ARC
Keywords: Navigation, Planning, Robot sensing systems, Switches, Trajectory, Unvertainty
DOI: 10.1109/IROS.2014.6943204
ISBN: 978-1-4799-6934-0/14
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: ©2014 IEEE
Deposited On: 25 Aug 2014 01:44
Last Modified: 25 Nov 2014 11:15

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