Kashyap Hegde Kota

Accurate spacecraft position and orientation detection is essential for vital space operations such as rendezvous, docking, tracking, and determining the motion of uncooperative satellites. Ongoing research in this area aims to develop an intelligent system that combines neural networks with traditional estimation algorithms to operate under adversarial lighting conditions and at high speeds. However, most existing approaches involve using frame-based cameras, which notably struggle in space due to the extreme contrast and high-speed characteristics found in space. The proposed research project addresses this gap by introducing event-based vision to counteract the adverse lighting effects and provide microsecond timing precision. This approach attempts to enhance spacecraft position and orientation estimation by enabling neural networks to understand event data streams and estimate the position and orientation of the spacecraft with extreme precision which improves vital space operations.