Robust obstacle detection from stereoscopic image sequences using Kalman filtering

9Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

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. © Springer-Verlag Berlin Heidelberg 2001.

Cite

CITATION STYLE

APA

Suppes, A., Suhling, F., & Hötter, M. (2001). Robust obstacle detection from stereoscopic image sequences using Kalman filtering. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2191, 385–391. https://doi.org/10.1007/3-540-45404-7_51

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free