Gait Motion Planning for a Six Legged Robot Based on the Associatron
Tomo Ishikawa*, Koji Makino**, Junya Imani*,
and Yasuhiro Ohyama*
*Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan
**Graduate School of Medicine and Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
This research addresses a gait motion planning problem for a six-legged robot walking on an irregular field. In this proposal, we used a simplified neural network model called an Associatron that recalls total motion patterns sequentially frompartial information. The Associatron is used here because it is more effective and adaptable than conventional methods. Using the proposed method, the robot is expected to walk in unknown fields. After verifying planning using an Open Dynamics Engine (ODE) by using simulations, we found that memorized patterns are recalled from developed patterns. We then conducted experiments using a real developed robot. Experiment results show that, when using the proposed planning method, the robot selects suitable gait motion patterns in the presence of an obstacle.
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