A study toward cognitive action with environment recognition by a learning space robot

This paper addresses an experimental system simulating a free-flying space robot, which has been constructed to study autonomous space robots. The experimental system consists of a space robot model, a frictionless table system, a computer system, and a vision sensor system. The robot model is composed of two manipulators and a satellite vehicle, and can move freely on a two-dimensional planar table, without friction, using air-bearings. The robot model has successfully performed the automatic truss structure assembly, including many jobs, e.g., manipulator berthing, component manipulation, arm trajectory control collision avoidance, assembly using force control, etc. Moreover, even if the robot fails in a task planned in advance, the robot re-plans the task by using reinforcement learning, and obtains the task goal for basically kinematic problems. But, for a class of complicated dynamic problems, the computational periods and efforts are infeasible for on-line learning. Some approaches are proposed to accelerate the learning speed, which also give models of cognitive actions and approaches to so-called a frame problem. The experiment demonstrates the possibility of the autonomous construction and the usefulness of space robots.