Abstract

This paper deals with the problem of pose determination of uncooperative targets, e.g. space debris. An optimized Template Matching approach is adopted for pose initialization, while different variants of the Iterative Closest Point algorithm are considered for pose tracking. The algorithms process 3D point clouds generated by a scanning LIDAR. Algorithm performance is investigated within a numerical simulation environment reproducing realistic conditions in terms of target configuration and sensor operation. Results demonstrate that the proposed algorithms provide adequate initialization of the pose parameters as well as pose estimate in the tracking phase with 0.1° accuracy in attitude and sub-centimeter accuracy in relative position, operating with sparse point clouds. Finally, the effect of target visibility in the sensor field of view on the tracking algorithm performance is analyzed in detail.

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