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.
-  Y. Yamada, H. Konosu, T. Morizono, and Y. Umetani, “Proposal of Skill-Assist: A System of Assisting Human Workers by Reflecting Their Skills in Positioning Tasks,” Proceedings of IEEE International Conference of System, Man, and Cybernetics, Tokyo, Japan, pp. IV-11, 1999.
-  H. Konosu, Y. Yamada, T. Morizono, and Y. Umetani, “Skill-Assist: Helping Human Workers with Automobile Modular Component Assembly,” Proceedings of SAE 2002 World Congress, Detroit, pp. 1-6, March 4-7, 2002.
-  BSR/T15.1, “Draft Standard for Trial Use for Intelligent Assist Devices - Personnel Safety Requirements,” Robotic Industries Association, March 15, 2002.
-  U. Laible, T. Burger, and G. Pritschow, “A fail-safe dual channel robot control for surgery applications,” Safety Science, Vol.42, No.8, pp. 423-436, 2004.
-  D. L. Hamilton, J. K. Bennett, and I. D. Walker, “Parallel Fault-Tolerant Robot Control,” Proceedings of the SPIE Conference on Cooperative Intelligent Robotics in Space III, pp. 251-261, Boston 1992.
-  J. E. Colgate, M. Peshkin, and S. H. Klostermeyer, “Intelligent Assist Devices in Industrial Applications: A Review,” Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, pp. 2516-2521, October, 2003.
-  E. Faulring and J. Colgate, “Run-Time Three-Dimensional Blend-Path Generation for Cobot Constraint Surfaces,” Proceedings of 2002 ASME International Mechanical Engineering Congress & Exposition, New Orleans, pp. 1-8, November 17-22, 2002.
-  R. Shraft, C. Meyer, C. Parlitz, and E. Helms, “PowerMate - A Safe and Intuitive Robot Assistant for Handing and Assembly Tasks,” Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, pp. 4085-4090, April, 2005.
-  Y. Yamada, T. Morizono, Y. Umetani, and H. Konosu, “Warning : To Err Is Human Working Toward a Dependable Skill-Assist with a Method for Preventing Accidents Caused by Human Error,” IEEE Robotics and Automation Magazine, Vol.11, No.2, pp. 34-45, 2004.
-  “IEC 61025 Technical Committee, IEC 61025, Fault tree analysis (FTA),” IEC, 2006.
-  “IEC 60812 Technical Committee, IEC 60812, Analysis Techniques for System Reliability - Procedure for Failure Mode and Effects Analysis (FMEA),” IEC, 2006.
-  M. Sakai, T. Shirai, and M. Mukaidono, “A Construction Method of Fail-Safe Interlocking Module Based on Separation Between Safety-Related Parts and Non-Safety-Related Parts,” Proceedings of 4th International Conference on Engineering Design and Automation, Orlando, USA, p. 966, 2000.
-  M. Kato et al., “LSI Implementation and Safety Verification of Window Comparator Used in Fail-Safe Multiple Valued Logic Operations,” IEICE Transactions on Electron, Vol.E76-C, No.3, 1993.
-  Y. Wu and T. S. Huang, “Vision-Based Gesture Recognition: A Review Lecture Notes in Computer Science,” Springer, German, pp. 103-115, 1999.
-  A. Wilson and A. Bobick, “Parametric Hidden Markov Models for Gesture Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.21, No.9, pp. 884-900, 1999.
-  M. Hasanuzzaman, V. Ampornaramveth, T. Zhang, M. A. Bhuiyan, Y. Shirai, and H. Ueno, “Real Time Vision Based Gesture Recognition for Human-Robot Interaction,” Proceedings of the 2004 IEEE International Conference on Robotics and Biomimetics, pp. 379-384, Shenyang, China, 2004.
-  T. Kirishima, K. Sato, and K. Chihara, “Real-Time Gesture Recognition by Learningand Selective Control of Visual Interest Points,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.27, No.3, pp. 351-364, 2005.
-  ISO Technical Committee 199, ISO13855, “Safety of Machinery - Positioning of Protective Equipment with Respect to the Approach Speeds of Parts of the Human Body,” ISO, 2002.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.