Abstract
This paper proposes an algorithm to detect the obstacles in outdoor unstructured environment with monocular vision. It makes use of motion cues in the video streams. Firstly, optical flow at feature points is calculated. Then rotation of the camera and FOE(focal of expansion) are evaluated separately. A non-linear optimization method is adopted to refine the rotation and FOE. Finally, we get inverse TTC(time to contact) with rotation and FOE and detect the obstacles in the scene. The algorithm doesn’t need any assumption that the ground is flat or partially flat as the conventional methods. So it is suitable for outdoor unstructured environment. Qualitative and quantitative experiment results show that our algorithm works well on different kinds of terrains.
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Shen, Y., Du, X., Liu, J. (2007). Monocular Vision Based Obstacle Detection for Robot Navigation in Unstructured Environment. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_84
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DOI: https://doi.org/10.1007/978-3-540-72383-7_84
Publisher Name: Springer, Berlin, Heidelberg
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