An Adaptive Artificial Potential Function (AAPF) methodology for rapid path-planning of spacecraft autonomous proximity operations (POs) is developed and compared to the Artificial Potential Function (APF). The AAPF method permits attractive potential with time dependent weights which are defined by an adaptive update law. The developed methodology enables POs with increased performance (e.g., with respect to fuel and/or time) and reduce teleoperation in an evolving environment. Two applications were simulated to demonstrate the performance of AAPF: performing orbital maneuvers and performing attitude maneuvers. Finally, a "Monte Carlo" type simulation was performed for both applications to show convergence and performance characteristics.
This paper addresses a new concept of autonomous guidance for close proximity operations in space. A potential function is developed with the intent that a minimum occurs at a desired relative position. A control law is then used to account for the dynamic effects and ensure the path generated is obstacle free. CW maneuvers are used to traverse solutions provided from the guidance algorithm. Trajectories are shown for a variety of situations in which a completely autonomous spacecraft can rendezvous with a cooperative satellite in an unspecified amount of time. A comparison is made between the new algorithm and traditional APFG methods by examining the total impulse thrusts and time of flight. It is shown that the new algorithm is more fuel efficient and has a shorter time of flight than traditional APFG methods.
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