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Proceedings Paper

Object classification for obstacle avoidance
Author(s): Uwe Regensburger; Volker Graefe
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Paper Abstract

Object recognition is necessary for any mobile robot operating autonomously in the real world. This paper discusses an object classifier based on a 2-D object model. Obstacle candidates are tracked and analyzed false alarms generated by the object detector are recognized and rejected. The methods have been implemented on a multi-processor system and tested in real-world experiments. They work reliably under favorable conditions but sometimes problems occur e. g. when objects contain many features (edges) or move in front of structured background.

Paper Details

Date Published: 1 March 1991
PDF: 8 pages
Proc. SPIE 1388, Mobile Robots V, (1 March 1991); doi: 10.1117/12.25460
Show Author Affiliations
Uwe Regensburger, Univ. der Bundeswehr Muenchen (Germany)
Volker Graefe, Univ. der Bundeswehr Muenchen (Germany)

Published in SPIE Proceedings Vol. 1388:
Mobile Robots V
Wendell H. Chun; William J. Wolfe, Editor(s)

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