Task-Oriented Motion Planning of a Space Manipulator under Multiple Constraints

During task execution by a space manipulator, many factors need to be considered, such as joint motion range, external environment interference, running speed and task time. Studying the motion planning strategy under multi-constraint conditions is important for optimizing the task flow of the manipulator and improving the planning autonomy. Aiming at this, this paper proposes a method based on a hierarchical task network which has the ability to connect non-adjacent nodes of topology when generating the best path; it also carries out the control simulation of traditional path planning of a manipulator for typical tasks and the latter two working conditions using an optimal task planning method. The results show that this method is effective for realizing the Cartesian spatial task planning of a manipulator under multiple constraints and has important on-orbit application significance for improving the continuous autonomy of task completion.