A fast obstacle detection method based on optical flow

  • Nicola Ancona
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)


This paper presents a methodology, based on the estimation of the optical flow, to detect static obstacles during the motion of a mobile robot. The algorithm is based on a correlation scheme. At any time, we estimate the position of the focus of expansion and stabilize it by using the Kalman filter. We use the knowledge of the focus position of the flow field computed in the previous time to reduce the search space of corresponding patches and to predict the flow field in the successive one. Because of its intrinsic recursive aspect, the method can be seen as an on-off reflex which detects obstacles lying on the ground during the path of a mobile platform. No calibration procedure is required. The key aspect of the method is that we compute the optical flow only on one row of the image, that is relative to the ground plane.


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    Little J., Bulthoff H. and Poggio T.: Parallel Optical Flow Using Local Voting. IEEE 2nd International Conference in Computer Vision, 1988Google Scholar
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    Sandini G. and Tistarelli M.: Robust Obstacle Detection Using Optical Flow. IEEE Workshop on Robust Computer Vision, 1–3 October 1990, Seattle-USAGoogle Scholar
  3. [AN1]
    Ancona N.: A First Step Toward a Temporal Integration of Motion Parameters. IECON'91, October 28 1991, Kobe-JapanGoogle Scholar
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    Enkelmann W.: Obstacle Detection by Evaluation of Optical Flow Fields from Image Sequences. First European Conference on Computer Vision, April 1990, Antibes-FranceGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Nicola Ancona
    • 1
  1. 1.Tecnopolis CSATA Novus Ortus 70010 ValenzanoBariItaly

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