Orbital Dynamic Effects on Fuel Use in Sampling-Based Plans for Proximity Operations

While proximity operation trajectory planners optimize for fuel cost, robotic sampling-based planners handle complex obstacle fields more robustly. This paper investigates the importance of orbital dynamics in proximity operation paths generated by rapidly exploring random tree for zero-gravity (RRTZ), a sampling-based planner. We leverage Newtonian mechanics to estimate fuel cost using the Clohessy–Wiltshire equations for varying inspector velocities and target proximity ranges. Path velocity and displacement from the space station in the radial direction and perpendicular to the orbital plane appreciably increase fuel cost. Slow inspector velocities lead to long correction periods associated with expensive displacement-based orbital drift corrections. Results indicate an optimal traversal speed for each RRTZ solution. Future work to integrate orbit drift corrections into sampling-based planning is planned.