Speed-accuracy optimization for skill learning

Robot motor capability is crucial for skill learning because it determines how accurately and rapidly a robot can perform a skill to accomplish a task constrained by the spatial and temporal conditions. Due to the capability of robot motor, a robot may not be able to perform skills to satisfy both task spatial and temporal constraints. To determine the robot motor capability, this paper formulates the skill for accomplishing a task as an optimization problem subject to the spatial and temporal conditions of the task, and proposes to develop a speed-accuracy constraint suitable for the optimization problem. The proposed speed-accuracy constraint is derived from the kinematics, dynamics, and control of a robot motor system. By solving the optimization problem, a robot can perform the skill to achieve a task by its fastest speed without violating the spatial and temporal conditions of the task. Computer simulations were performed on a PUMA 560 robot to demonstrate a skill on a typical task to validate the proposed speed-accuracy optimization.