Perception-Constrained Robot Manipulator Planning for Satellite Servicing

Abstract

Satellite servicing is a rapidly developing industry which requires a number advances in semi- and fully-automated space robotics to unlock many key servicing capabilities. One upcoming mission example is the NASA Restore-L Robotic Servicing spacecraft, which is equipped with two 7-joint robotic manipulators used to capture a satellite and perform a complex series of refueling tasks, including swapping between various end-effector tools stored on board. In this scenario, planning of the manipulator motions must account for a number of constraints, such as collision avoidance and the potential need for uninterrupted visual tracking of objects or of the end-effector. Such complex constraints in a cluttered environment, such as the interface between two spacecraft, are time-consuming to incorporate into hand-designed trajectories. Thus, in this work we present a software tool which uses robot motion planning and path refinement algorithms for automated, real-time computation of near-optimal, collision-free trajectories which satisfy the aforementioned perception constraints. The tool is built on the ROS MoveIt! framework, which can simulate and visualize trajectories as well as seamlessly switch between motion planning and refinement algorithms depending on task requirements. Additionally, we performed experimental campaigns to benchmark a number of available algorithms for performance in handling such perception constraints. Although the framework is applied to a mock-up of Restore-L satellite servicer in this paper, the tool can be applied to any fixed-base manipulator planning scenario with a similar class of constraints.