Multi-spacecraft Trajectory Optimization and Control using Genetic Algorithm Techniques


This paper presents an approach for multispacecraft trajectory planning, optimization and control. Maneuver planning as a global optimization problem is solved using Genetic Algorithms (GA). Methods were devised to reduce the dimensionality of the decision space, yet retain adequate generality of maneuver possibilities. A compact formulation based on thruster switching-times was used for generic point-to-point spacecraft maneuvers. Optimal control is implicitly satisfied by "bang-coast-bang" actuation schemes. Maneuver profiles, including Line-of-sight and orthogonal collision avoidance, were developed. A GA optimizer selects the optimal parameter set for each scenario. Simulation case studies were performed for 2, 3 and 5-spacecraft formation initialization tasks. Objective criteria used in the evaluation function included: endpoint errors; collision avoidance; path lengths; maneuvering times; fuel usage and equalization. In all cases, a nominal GA computed feasible trajectories. Objective criteria trade-offs were demonstrated by selective weighting. Ongoing work includes multi-objective optimization of multiple spacecraft trajectories using Niched-Pareto Genetic Algorithms.