Robust Obstacle Detection from Stereoscopic Image Sequences Using Kalman Filtering

Authors:
Alexander Suppes;Frank Suhling;Michael Hötter
Affiliations:
-;-;-
Venue:
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
Year:
2001

Citing 5
Cited 1

Kalman filtering: theory and practice

Kalman filtering: theory and practice
Three-dimensional computer vision: a geometric viewpoint

Three-dimensional computer vision: a geometric viewpoint
Sensordatenfusion zur robusten und präzisen EKF Lokalisierung von mobilen Robotern

Autonome Mobile Systeme 1999, 15. Fachgespräch
Stereobasierte Videosensorik unter Verwendung einer stochastischen Zuverlässigkeitsanalyse

Mustererkennung 2000, 22. DAGM-Symposium
An Introduction to the Kalman Filter

An Introduction to the Kalman Filter

Comparison of stochastic filtering methods for 3D tracking

Pattern Recognition

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Abstract

In this paper a new approach for video based obstacle detection for a mobile robot is proposed, based on probabilistic evaluation of image data. Apart from the measurement data, also their uncertainties are taken into account. Evaluation is achieved using Kalman filter technique combining the results of video data processing and robot motion data. Obstacle detection is realised by computing obstacle probability and subsequent application of a threshold operator. The first experiments show remarkably stable obstacle detection.