Hardware Simulation of Relative Navigation Using Visual Sensor Information

Abstract

Precise relative navigation between an unmanned vehicle and a target, which could be a stationary or a second moving vehicle, is an important capability that has many possible applications including formation operation, as well as autonomous rendezvous and docking of either spacecraft or aircraft. A test bed setup is described where unmanned ground vehicles are used to simulate the physical motion of aerospace vehicles, and provide the attached sensor packages with realistic relative motion in both indoor and outdoor environments. Using an unmanned robotic ground vehicle, the visual servoing problem is investigated and simulated using actual hardware in real world test conditions. A simple camera is used to measure the relative position, orientation, and motion between the vehicle and the target. Color statistical pressure snake algorithms are employed to track a visual target within the camera images in real time. The effectiveness of the nonlinear visual servoing algorithm is demonstrated through experimental hardware tests.