Authors: A.G. Buddhika P. Jayasekara, Keigo Watanabe, Maki K. Habib, Kiyotaka Izumi
Addresses: Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, 1 Honjomachi, Saga 840-8502, Japan. ' Department of Intelligent Mechanical Systems, Graduate School of Natural Science and Technology, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan. ' Mechanical Engineering Department, School of Sciences and Engineering, The American University in Cairo, 113, Kasr El Eini St., P.O. Box 2511, Cairo 11511, Egypt. ' Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, 1 Honjomachi, Saga 840-8502, Japan
Abstract: This paper proposes a method for learning and controlling an industrial robot manipulator through Fuzzy Voice Commands (FVCs) guided by visual motor coordination. Supervised Self-Organising Map (SSOM) is proposed to implement the visual motor coordination. The FVCs are used to control the robot manipulator toward a goal. Visual evaluation process is adapted by the supervision of the human coach. The learned system is capable of navigating the robot manipulator to a point in 3D working space as instructed by the voice commands. The proposed idea is demonstrated with a PA-10 industrial manipulator.
Keywords: FVCs; fuzzy voice commands; visual motor coordination; SSOM; supervised self-organising maps; robot control; robot learning; industrial manipulators; industrial robots.
International Journal of Mechatronics and Manufacturing Systems, 2010 Vol.3 No.3/4, pp.244 - 260
Published online: 10 May 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article