Computing motion parameters from sparse multisensor range data for telerobotics
Baba C. Vemuri, G. Skofteland · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
Computing object motion from time-varying multi-sensor data and fusing this data into a coherent map of the object and/or its environment are important problems in robotics. In this paper, we present a new algorithm for motion estimation from sparse range data acquired from multiple sensors namely, a stereo camera system and an array of laser range finders. The motion estimates from this algorithm are input to a Kalman filter based state estimator for continuosly tracking a free-flying object in space under zero-gravity conditions.