Autonomous Rendezvous Controller Design Using 3D Depth Data

Space is starting to become a very crowded place especially in low earth orbit (LEO). Current projections are showing that without active debris removal (ADR) missions manned and unmanned operations in LEO will become in danger of collision. While research is being done on removal techniques of debris, most are piloted or sent after only one target. This thesis presents the application of the two controllers to be used on a nonlinear active satellite system to rendezvous with a certain target that can be identified from a depth map acquired from the Microsoft Xbox Kinect. The Kinect is comparable to other Light Detection and Ranging (LiDAR) devices that are currently used in space flight operations. The two types of controllers that are compared are a state feedback controller and a fuzzy logic controller. The fuzzy logic controller was chosen due the way the rules can mimic a pilot's experience, while the state feedback controller is chosen because it creates a controller that is lyapunov stable for each state. Initial conditions are provided to the controller at first in order to ensure each controller works in a variety of start points. Then using image processing algorithms used in flight and in the Open Source Computer Vision Library (OpenCV), we then use the Kinect to identify a target and obtain its distance reading from the depth map. Simulations show that both controllers work well for rendezvous with the target location and showed the benefits of using both controllers.