UPPER-BODY REACH POSTURE PREDICTION FOR ERGONOMIC EVALUATION MODELS

Abstract

Proper assessment of human reach posture is one of the essential functions for ergonomic workspace design and evaluation in computer-aided ergonomic evaluation models or any CAD system with a built-in man model. To predict reach posture, most existing models have been using heuristic methods, which provide only the range of feasible postures, not always ensuring the one that a person naturally takes. An analytic reach prediction algorithm was developed in this study by employing the inverse kinematics methods. Each upper limb is modelled as a four-link system, consisting of trunk, upper arm, lower arm, and hand, being regarded as a redundant manipulator with a total of eight degrees of freedom. Among several kinematic methods for solving human reach movement, the resolved motion method which is one of the redundant manipulator techniques in robotics was found to be effective. In this method, the joint range availability was used as a performance function to guarantee kinematic optimality and to simulate human reach closely. In addition, an approximate algorithm to generate the workspaces of human body was developed. Real reach postures taken from the subjects were analyzed by the motion analysis system and were statistically similar to those obtained from the prediction model.