Skill-Assist Safety and Intelligence Technology
Suwoong Lee* and Yoji Yamada**
*Department of Bio-System Engineering, Graduate School of Science and Engineering, Yamagata University, 419 Building No.8, 4-3-16 Jonan, Yonezawa, Yamagata 992-8510, Japan
**Mechano-Informatics and Systems, Department of Mechanical Science and Engineering, Graduate School of Engineering, Nagoya University, 303 Building No.2 North, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
Skill-Assist for automobile manufacturing enables operators to move heavy component modules to target sites, playing a valuable role on production lines. Skill-Assist has high-powered actuators and operates in physical contact with users, so safety is a top priority. This paper describes safety technology developed for and implemented in Skill-Assist at the National Institute of Advanced Industrial Science and Technology, Japan (Skill-Assist@AIST). Risk was assessed for main causes of potentially hazardous events, which were projected to result from abnormal command signals generated by the controller, human error, and unauthorized access. In this paper, we focus on safety measures against abnormal command signals and human error, and introduce current safety technology for Skill-Assist@AIST. Highly reliable control includes a dual-channel controller and fail-safe fault-detection hardware (FSFDH) for ensuring functional safety through command signal monitoring. A reaching-gesture recognition (RGR) algorithm based on laser range sensor data and a hidden Markov model (HMM) predictively detect operator error that outlies predefined safe reaching.
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