A software prototype for autonomous 3D scanning of uncooperatively rotating orbital debris using a point cloud sensor is designed and tested. The software successfully generated 3D models under conditions that simulate some on-orbit orbit challenges including relative motion between observer and target, inconsistent target visibility and a target with more than one plane of symmetry. The model scanning software performed well against an irregular object with one plane of symmetry but was weak against objects with 2 planes of symmetry.
The suitability of point cloud sensors and algorithms for space is examined. Terrestrial Graph SLAM is adapted for an uncooperatively rotating orbital debris scanning scenario. A joint EKF attitude estimate and shape similiarity loop closure heuristic for orbital debris is derived and experimentally tested. The binary Extended Fast Point Feature Histogram (EFPFH) is defined and analyzed as a binary quantization of the floating point EFPFH. Both the binary and floating point EPFH are experimentally tested and compared as part of the joint loop closure heuristic.
|Commitee:||Doostan, Alireza, Jones, Brandon|
|School:||University of Colorado at Boulder|
|School Location:||United States -- Colorado|
|Source:||MAI 53/02M(E), Masters Abstracts International|
|Subjects:||Aerospace engineering, Robotics, Computer science|
|Keywords:||3D scanning, Explicit loop closure heuristic, Graph slam, Model generation, Orbital debris, Point clouds|
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