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Autonomous shape model learning for object localization and recognition

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2 Author(s)
J. Modayil ; Dept. of Comput. Sci., Texas Univ., Austin, TX ; B. Kuipers

Mobile robots do not adequately represent the objects in their environment; this weakness hinders a robot's ability to utilize past experience. In this paper, we describe a simple and novel approach to create object shape models from range sensors. We propose an algorithm that defines angular constraints between multiple sensor scans of an object. These constraints are used to align the scans, creating a maximally coherent object shape model. We demonstrate the utility of this shape model, consisting of scans and poses, for both object recognition and localization. The results are accurate to within sensor precision

Published in:

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.

Date of Conference:

15-19 May 2006