Evaluation for Manual Precision Works Based on the Hand Tracking and Fuzzy Inference

Abstract

The hand movements during precision work are an important factor to evaluate ability and quality. However, it is not easy to evaluate worker’s skill objectively and teach the skill to beginners, because there are individual differences in hand movements. In order to improve the learning efficiency of precision work, we develop an evaluation system to evaluate worker’s skill. The system is composed of hand tracking and fuzzy inference. We employ MediaPipe as a hand tracking tool. The worker’s skills are evaluated by fuzzy inference based on hand movements data obtained by MediaPipe. In This study, we focus on soldering as a precision operation.