Computing position and orientation of free-flying polyhedron from 3D data

A robotic vision system for grasping a free-flying polyhedron in space has been developed using stereo vision and laser range finders. Real-time motion estimation and sensor fusion is achieved by using prior knowledge of the object. A maximum likelihood parameter estimation is developed for rotational symmetric polyhedrons, and the 3D transformations for fusing many different sensors into one coordinate frame are given. The minimization is solved using the sequential quadratic programming technique, which has proved to be a robust and efficient method. Included are simulation results performed on the hardware that will be used in the ROTEX space robot technology experiment