Object classification for obstacle avoidance

Uwe Regensburger; Volker Graefe

doi:10.1117/12.25460

1 March 1991 Object classification for obstacle avoidance

Uwe Regensburger, Volker Graefe

Proceedings Volume 1388, Mobile Robots V; (1991) https://doi.org/10.1117/12.25460
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

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.

Citation Download Citation

Uwe Regensburger and Volker Graefe "Object classification for obstacle avoidance", Proc. SPIE 1388, Mobile Robots V, (1 March 1991); https://doi.org/10.1117/12.25460

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