Six Dimensional Trajectory Solver for Autonomous Proximity Operations
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH
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Many future space mission will require that proximity operations be accomplished reliably, precisely and efficiently without a pilot in the loop. This thesis examines one element of an autonomous proximity operations controller, the trajectory planner. The trajectory planner uses a modified gradient search to find a locally optimal trajectory from the initial state to the target state that does not violate any of the mission constraints. The mission constraints are defined as the maximum time of flight for the operation, the maximum closing velocity allowed, and the obstacles in close proximity to the chase and target craft. The obstacles in this space are not assumed to be stationary therefore, the planner must be able to develop a solution that, although not guaranteed globally optimal, meets all mission constraints in real time. This will enable the autonomous controller to avoid obstacles moving rapidly with respect to it and to correct for failed actuators. The Clohessy-Wiltshire equations for relative position and quaternions for relative attitude are used to define a state space relationship solver the initial state and the final state as a function of time. The trajectory between then uses these equations to find the minimum fuel solution to the problem of maneuvering to a target position and attitude while evading moving obstacles. Example results and simulations are included for various initial conditions and maneuvering constraints. The trajectory planner algorithm can find a trajectory from any initial state to any final state which satisfies the input constraints and uses minimum fuel.
- Spacecraft Trajectories and Reentry