Identification of open and closed kinematic chains with application to biomechanics and robotics

Abstract

The main objective in this thesis is to develop methods that automatically generate kinematic models for biological and robotic systems. The motivation comes from our study of individuals with quadriplegia and the need to design aids such as robots and teletheses that can be controlled by head and neck movements. It is necessary, then, to develop mathematical models for head and neck movements. The objective, however, is not to accurately describe the anatomical and physiological details of the head-neck system but rather to capture the essence of the possible movements. The general problem presented here is similar to that encountered in the calibration of machines and robots. Except that we have no starting (nominal) model and most importantly the joint motions in biological systems often cannot be directly measured. Two methods for the identification of the kinematics are presented. They both require the subject to move his/her head and neck in three-dimensional space while measuring the position and orientation of the head. The first method requires the elimination of the displacement variables that cannot be measured while the second method attempts to estimate the changes in these variables. Several theoretical results have been established pertaining to identification and the number of parameters required to describe the kinematic model. Special cases in which the kinematic identification can or cannot be performed have been identified. These methods have been tested using a planar two-revolute joint system. The model parameters obtained, in this case, agree with the actual parameters to within 5%. We have also applied these methods to study the kinematics of head-neck movements and the potential use of kinematic models in the design of rehabilitation aids.