Surface and motion estimation from sparse range data

A system is presented for the simultaneous estimation of surface and motion parameters of a free-flying object in a telerobotics experiment. The system consists of two main components, a vision-based invariant-surface and motion estimator, and a Kalman filter. An algorithm for invariant surface and motion estimation from sparse multi-sensor range data is presented. Motion estimates from the vision module are input to a Kalman filter (KF) for tracking a 'free-flying' object in space. The predicted motion parameters from the KF are fed back to the vision module and serve as an initial guess in the search for optimal motion.< >