Finite thrust spacecraft approaching trajectory planning based on genetic programming

Based on the genetic programming algorithm with the introduction of the basis function, this paper proposes a new way to deal with finite-thrust spacecraft trajectory optimization when approaching a non-cooperative object in the final approach phase. Thruster switch state is defined as the basis functions which respectively multiply by the switch state duration and then sum as the thruster state function. The thruster state function is converted into genetic programming tree structure. Fuel consumption is defined as the fitness function of genetic programming, and the constraint conditions of obstacle avoidance and approaching precision are induced into the fitness function in the form of penalty function. Genetic programming algorithm is used to obtain the optimal-fuel trajectory planning scheme by training all the possible combinations of thrusters switch state. The result is global optimal, and the thrusters switch frequency is not high. The trajectory planning result based on finite thrust of a spacecraft approaching non-cooperative object shows that the thruster is only opened and closed 5 times, greatly reducing the requirement for switching frequency. Approaching time is reduced by 30.09% compared with the Gauss pseudospectral method, and fuel consumption is reduced by 4.18%.