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- W2649884915 abstract "In this paper, action of wheeled type robot is determined from the obstacle configuration and the robot's self-state using a neural network (NN), and multiple moving obstacles avoided. In order to avoid obstacles with the minimum movement time, the design parameters of the NN are optimized by genetic algorithm (GA), using the data collected from several environments, in which each environment has a different obstacle configuration." @default.
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- W2649884915 date "2007-01-01" @default.
- W2649884915 modified "2023-09-25" @default.
- W2649884915 title "2A1-D05 Acquisition of Action for Wheeled Type Robots with Consideration to Multiple Moving Obstacles Avoidance" @default.
- W2649884915 doi "https://doi.org/10.1299/jsmermd.2007._2a1-d05_1" @default.
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