Robot learning schemes that trade motion accuracy for command simplification

This study was inspired by the human motor control system in its ability to accommodate a wide variety of motions. By contrast, the biologically inspi red robot learning controller usually encounters huge learning space proble ms in many practical applications. A hypothesis for the superiority of the human motor control system is that it may have simplified the motion comman d at the expense of motion accuracy. This tradeoff provides an insight into how fast and simple control can be achieved when a robot task does not dem and high accuracy. Two motion command simplification schemes are proposed i n this paper based on the equilibrium-point hypothesis for human motion con trol. Investigation into the tradeoff between motion accuracy and command s implification reported in this paper was conducted using robot manipulators to generate signatures. Signature generation involves fast handwriting, an d handwriting is a human skill acquired via practice. Because humans learn how to sign their names after they learn how to write, in the second learni ng process, they somehow learn to trade motion accuracy for motion speed an d command simplicity, since signatures are simplified forms of original han dwriting. Experiments are reported that demonstrate the effectiveness of th e proposed schemes. (C) 2000 Elsevier Science B.V. All rights reserved.