Abstract
Obstacle avoidance is an essential capability of an autonomous robot. This paper presents a method that enables a mobile robot to locate obstacles in its field of view using two images of its surroundings. The method is based on the assumption that the robot is moving on a locally planar ground. Using a set of point features (corners) that have been matched between the two views using normalized cross-correlation, a robust estimate of the homography of the ground is computed. Knowledge of this homography permits us to compensate for the motion of the ground and to detect obstacles as areas in the image that appear nonstationary after the motion compensation. The resulting method does not require camera calibration, is applicable either to stereo pairs or to motion sequence images, does not rely on a dense disparity/flow field and circumvents the 3D reconstruction problem. Experimental results from the application of the method on real images indicate that it is both effective and robust.
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© 1997 Springer-Verlag Berlin Heidelberg
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Lourakis, M.I., Orphanoudakis, S.C. (1997). Visual detection of obstacles assuming a locally planar ground. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_258
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DOI: https://doi.org/10.1007/3-540-63931-4_258
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