Coordinate transformation learning of hand position feedback controller by using change of hand position error norm

Author

Oyama, Eimei ; Tachi, Susumu

Author_Institution

Mech. Eng. Lab., Tsukuba Sci. City, Ibaraki, Japan

Volume

5

fYear

1998

fDate

28 Oct-1 Nov 1998

Firstpage

2358

Abstract

We need to solve the inverse kinematics problem, i.e., the coordinate transformation from the visual coordinates to the joint angle vector coordinates. In human motion control, the learning function of the hand position error feedback controller in human inverse kinematics solver is important. This paper proposes a novel model of the coordinate transformation learning of the human visual feedback controller, which uses the change of the joint angle vector and the corresponding change of the square of the hand position error norm

Keywords

backpropagation; biocontrol; feedback; feedforward neural nets; inverse problems; kinematics; least squares approximations; motion control; physiological models; position control; RMS error; backpropagation; coordinate transformation learning; discrete time first order model; feedforward controller; hand position error norm change; hand position feedback controller; human inverse kinematics solver; human motion control; human visual feedback controller; hybrid controller; inverse kinematics problem; joint angle vector coordinates; learning model; least squares minimisation; motor learning; neural nets; tracking control system; visual coordinates; Adaptive control; Biological system modeling; Control systems; Error correction; Fingers; Humans; Inverse problems; Kinematics; Pediatrics; Thumb;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE

Conference_Location

Hong Kong

ISSN

1094-687X

Print_ISBN

0-7803-5164-9

Type

conf

DOI

10.1109/IEMBS.1998.744776

Filename

744776