Path Searching of Robot Manipulator Using Reinforcement Learning-Reduction of Searched Configuration Space Using SOM and Multistage Learning-
Seiji Aoyagi and Kenji Hiraoka
Department of Mechanical Engineering, Faculty of Engineering Science, Kansai University, 3-3-35 Yamate-cho, Suita, Osaka 564-8680, Japan
-  R. S. Sutton and A. G. Barto (translated by S. Mikami and M. Minagawa), “Reinforcement Learning,” Morikita Publishing Co., Ltd., Tokyo, 2000.
-  E. W. Dijkstra, “A Note on Two Problems in Connexion with Graphs,” Numerische Mathematik, Vol.1, No.1, pp. 269-271, 1959.
-  E. Hart, N. J. Nilsson, and B. Raphael, “A Formal Basis for the Heuristic Determination of Minimum Cost Paths,” IEEE Transactions on Systems Science and Cybernetics, Vol.4, No.2, pp. 100-108, 1968.
-  J. C. Latombe, “Robot Motion Planning,” Kluwer Academic Publisher, Norwell, MA, 1991.
-  J. Kuffner and S. M. Lavalle, “RRT-Connect: An Efficient Approach to Single-Query Path Planning,” in Proc. IEEE Int. Conf. Robotics and Automation (ICRA 2000), pp. 995-1001, 2000.
-  A. Wolf, H. B. Brown, R. Casciola, A. Costa, M. Shwerin, E. Shamas, and H. Choset, “A Mobile Hyper Redundant Mechanism for Search and Rescue Tasks,” in Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS 2003), pp. 2889-2895, 2003.
-  K. Osuka, “Search in Narrow Space by Snake-Like Robots –Introduction of Research in DDT: Snake-Like Robot Group–,” J. of the Robotics Society of Japan, Vol.22, No.5, pp. 554-557, 2004.
-  S. Aoyagi, K. Tashiro, M. Minami, and M. Takano, “Development of Redundant Robot Simulator for Avoiding Arbitrary Obstacles Based on Semi-Analytical Method of Solving Inverse Kinematics,” in Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS 2007), pp. 3497-3502, 2007.
-  H. Gomi and M. Kawato, “Equilibrium-Point Control Hypothesis Examined by Measured Arm Stiffness During Multijoint Movement,” Science, Vol.272, No.5, pp. 117-120, 1996.
-  J. Morimoto and K. Doya, “Acquisition of Stand-up Behavior by a 3-link-2-joint Robot using Hierarchical Reinforcement Learning,” J. of the Robotics Society of Japan, Vol.19, No.5, pp. 574-579, 2001.
-  M. Nunobiki, K. Okuda, and S. Maeda, “Reinforcement Learning of Multi-Link Robot with Fuzzy ART Neural Networks for State-Space Segmentation,” J. of the Japan Society for Precision Engineering, Vol.71, No.1, pp. 141-145, 2005.
-  H. Kimura, T. Yamashita, and S. Kobayashi, “Reinforcement Learning of Walking Behavior for a Four-legged robot,” Trans. of the Institute of Electrical Engineers of Japan, Vol.122-C, No.3, pp. 330-337, 2002.
-  K. Ito, F. Matsuno, and A. Gofuku, “A Study of Reinforcement Learning for Redundant Robots –New Framework of Reinforcement Learning that Utilizes Body Image–,” J. of the Robotics Society of Japan, Vol.22, No.5, pp. 672-689, 2004.
-  H. Iwasaki and N. Sueda, “A System of Autonomous State Space Construction with the Self-Organizing Map in Reinforcement Learning,” in Proc. The 19th Annual Conf. of the Japanese Society for Artificial Intelligence, pp. 1-4, 2005.
-  H. Tokutaka and K. Fujimura, “Application of Self-Organizing Maps,” Kaibundo Publishing Co., Ltd., Tokyo, 1999.
-  K. Hiraoka, M. Suzuki, and S. Aoyagi, “Path Search of Redundant Manipulator for Obstacle Avoidance by Reinforcement Learning – Reduction of C-Space by Two Stage Learning Using Reference Trajectories and DP Matching,” in Proc. 26th Annual Conf. of the Robotics Society of Japan, CD-ROM no.1N3-08, 2008.
-  D. Baba, S. Uchida, and H. Sakoe, “A Predictive DP Matching Algorithm for On-line Character Recognition,” in Proc. Meeting on Image Recognition and Understanding (MIRU2007), pp. 1159-1164, 2007.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.
Copyright© 2010 by Fuji Technology Press Ltd. and Japan Society of Mechanical Engineers. All right reserved.