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This paper proposes a novel three dimensional (3 D) velocity estimation method by using differential flow techniques for the dynamic path planning of Autonomous Ground Vehicles ( AGV) in a cluttered environment. We provide a frame work for the computation of dense and non rigid 3 D flow vectors from the range data, obtained from the time-of-flight camera. Combined Lucas/Kanade and Horn/schunck approach is used to estimate the velocity of the dynamic obstacles. The trajectory of the dynamic obstacle is predicted from the direction of the 3 D flow field and the estimated velocity. By experiments, the utility of the approach is demonstrated with the results.

Motion Detection and Velocity Estimation for Obstacle Avoidance using 3D Point Clouds