Intelligent LIDAR scanning region selection for satellite pose estimation

This paper proposes a method to select a near-optimal laser scanning area on a target body that will result in the best registration accuracy. The method is based on constraint analysis and employs a sensitivity index which is used as a registration accuracy predictor. It is shown that point cloud configurations with higher values of this index return more accurate pose estimates than unstable configurations with lower index values. Iterative Closest Point (ICP) registration tests are conducted on four satellite geometries using synthetic range data. The proposed method can be used to increase the accuracy of ICP registration and to reduce registration processing time.