An Assessment of 3D Tracking Systems and Lidar Data for RPO Simulation
This thesis aimed to develop a rendezvous and proximity operation simulation to be tested with physical sensors and hardware, in order to assess the fidelity and performance of low-cost off-the-shelf systems for a hardware-in-the-loop testbed. With the push towards complex autonomous rendezvous missions, a low barrier to entry spacecraft simulator platform allows researchers to test and validate robotics systems, sensors, and algorithms for space applications, without investing in multimillion dollar equipment. This thesis conducted drone flights that followed a representative rendezvous trajectory while collecting lidar data of a target spacecraft model with a lidar sensor affixed to the drone. A relative orbital motion simulation tool was developed to create trajectories of varying orbits and initial conditions, and a representative trajectory was selected for use in drone flights. Two 3D tracking systems, OptiTrack and Vive, were assessed during these flights. OptiTrack is a high-cost state-of-the-art motion capture system that performs pose estimation by tracking reflective markers on a target in the tracking area. Vive is a lower-cost tracking system whose base stations emit lasers for its tracker to detect. Data collection by two lidar types was also assessed during these flights: real lidar data from a physical sensor, and virtual lidar data from a virtual sensor in a virtual environment. Drone flights were therefore performed in these four configurations of tracking system and lidar type, to directly compare the performance of higher-cost configurations with lower-cost configurations. The errors between the tracked drone position time history and the target position time history were analyzed, and the low-cost Vive and real lidar configuration was demonstrated to provide comparable error to the OptiTrack and real lidar configuration because of the dominance of the drone controller error over the tracking system error. In addition, lidar data of a target satellite model was collected by real and virtual lidar sensors during these flights, and point clouds were successfully generated. The resulting point clouds were compared by visualizing the data and noting the characteristics of real lidar data and its error, and how it compared to idealized virtual lidar data of a virtual target satellite model. The resulting real-world data characteristics were found to be modellable which can then be used for more robust simulation development within virtual reality. These results demonstrated that low-cost and open-source hardware and software provide satisfactory results for simulating this kind of spacecraft mission and capturing useful and usable data.