This paper presents an innovative visual odometry system for fast motion estimation of autonomous space exploration vehicles. In order to improve a vehicle position recovery, the use of accelerometers and gyros is usually supported by wheels odometry. The visual system can improve the reliability of the overall rover navigation system when used in conjunction with a classical odometry system, usually a ected by drift or sliding problems. The visual odometry system is based on arti cial vision and reconstructs the rover position through the analysis of sequences of images acquired by two stereo cameras. The proposed algorithm is based on stereo geometry and discrete optical ow computation. >From stereo geometry it is possible to locate the image points in the three dimensional environment, while from the optical ow the relative motion of the camera with respect to these points is computed. Moreover, in order to reduce the computational burden usually associated with the optical ow computation, it has been decided to rst search the images for features and then to compute the discrete optical ow only associated to them. The features detection and tracking is done by using the KLT algorithm. Tests made with low resolution cameras, showing encouraging results, are presented.
Fast Visual Odometry System for Planetary Exploration Rover based on Discrete Stereo Optical Flow
MASSARI, MAURO;
2011-01-01
Abstract
This paper presents an innovative visual odometry system for fast motion estimation of autonomous space exploration vehicles. In order to improve a vehicle position recovery, the use of accelerometers and gyros is usually supported by wheels odometry. The visual system can improve the reliability of the overall rover navigation system when used in conjunction with a classical odometry system, usually a ected by drift or sliding problems. The visual odometry system is based on arti cial vision and reconstructs the rover position through the analysis of sequences of images acquired by two stereo cameras. The proposed algorithm is based on stereo geometry and discrete optical ow computation. >From stereo geometry it is possible to locate the image points in the three dimensional environment, while from the optical ow the relative motion of the camera with respect to these points is computed. Moreover, in order to reduce the computational burden usually associated with the optical ow computation, it has been decided to rst search the images for features and then to compute the discrete optical ow only associated to them. The features detection and tracking is done by using the KLT algorithm. Tests made with low resolution cameras, showing encouraging results, are presented.File | Dimensione | Formato | |
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