Algorithms for visual odometry in outdoor field environment
RA '07 Proceedings of the 13th IASTED International Conference on Robotics and Applications
Visual odometry with effective feature sampling for untextured outdoor environment
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Road approximation in Euclidean and υ-disparity space: a comparative study
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
Real-time motion detection based on SW/HW-codesign for walking rescue robots
Journal of Real-Time Image Processing
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In this paper, we present a stereovision algorithm for real-time 6DoF ego-motion estimation, which integrates image intensity information and 3D stereo data in the well-known Iterative Closest Point (ICP) scheme. The proposed method addresses a basic problem of standard ICP, i.e. its inability to perform the segmentation of data points and to deal with large displacements. Neither a-priori knowledge of the motion nor inputs from other sensors are required, while the only assumption is that the scene always contains visually distinctive features which can be tracked over subsequent stereo pairs. This generates what is usually called Visual Odometry. The paper details the various steps of the algorithm and presents the results of experimental tests performed with an allterrain mobile robot, proving the method to be as accurate as effective for autonomous navigation purposes.