Recognition and Performance of Human Task with 9-eye Stereo Vision and Data Gloves

Abstract

This paper presents a novel method of constructing a human task model by attention point (AP) analysis. The AP analysis consists of two steps. At the first step, it broadly observes human task, constructs rough human task model and finds APs which require detailed analysis. Then at the second step, by applying time-consuming analysis on APs in the same human task, it can enhance the human task model. This human task model is highly abstracted and is able to change the degree of abstraction adapting to the environment so as to be applicable in a different environment. We describe this method and its implementation using data gloves and a stereo vision system. We also show an experimental result in which a real robot observed a human task and performed the same human task successfully in a different environment using this model.