Dr Nick Hawes

Reader in Autonomous Intelligent Robotics

School of Computer Science
University of Birmingham
Edgbaston, Birmingham, B15 2TT
United Kingdom

Email: n.a.hawes@cs.bham.ac.uk
Twitter: @hawesie
Phone: +44 (0) 121 41 43739
Office: 133 (first floor, back right)
Office Hours: Mon 12:00, Tues 11:00 (term-time only)
Availability: Doodle MeetMe
[kunze2014icra] Lars Kunze, Keerthi Kumar Doreswamy and Nick Hawes. Using Qualitative Spatial Relations for Indirect Object Search. In IEEE International Conference on Robotics and Automation (ICRA). May 2014. [pdf] [bib]
Abstract.

Finding objects in human environments requires autonomous mobile robots to reason about potential object locations and to plan to perceive them accordingly. By using information about the 3D structure of the environment, knowledge about landmark objects and their spatial relationship to the sought object, search can be improved by directing the robot towards the most likely object locations.

In this paper we have designed, implemented and evaluated an approach for searching for objects on the basis of Qualitative Spatial Relations (QSRs) such as left-of and in-front-of. On the basis of QSRs between landmarks and the sought object we generate metric poses of potential object locations using an extended version of the ternary point calculus and employ this information for view planning. Preliminary results show that search methods based on QSRs are faster and more reliable than methods not considering them.

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