Pose Determination and Tracking for Autonomous Satellite Capture

This paper presents a concept and initial results of testing a vision system for satellite proximity operations. The system uses natural features on the satellite surfaces and does not require any artificial markers or targets for its operation. The system computes motion of unknown objects, and using object models computes their positions and orientations (pose), and tracks them in images sequences. The system processes images from stereo cameras to compute 3D data. Motion of an unknown object is computed using projective vision. Initial pose of the object is acquired using an approach based on Geometric Probing. The pose is tracked using a fast version of an Iterative Closest Point algorithm. Selected modules of the system have been characterised in a representative environment; the other are undergoing systematic sets of experiments.

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