Trajectory optimization and tracking control of free-flying space robots for capturing non-cooperative tumbling objects

This paper investigates the problem of capturing non-cooperative tumbling objects by free-flying space robots. To solve the two challenges of task constraints and base-manipulator coupling, a pseudospectral method based trajectory optimization and a reinforcement learning based tracking control are proposed for the free-flying space robots. Multiple constrains, including dynamics, field of view and obstacle avoidance, are considered in trajectory optimization. The adaptive segmented Radau pseudospectral method is used to discretize the energy-optimal trajectory problem into a nonlinear programming problem. By adaptively dividing the global time interval into multiple subintervals, higher-order interpolation polynomials are avoided. A reinforcement learning based parameter tuning method is proposed for the base controller to suppress the reaction torque caused by the manipulator. Numerical simulations and experiments on air-bearing testbed verify the effectiveness of our methods in terms of planning efficiency and tracking precision.