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Adaptive Humanoid Robot Arm Motion Generation by Evolved Neural Controllers

In this paper, we present a new method for humanoid robot arm motion planning satisfying multiple constraints. In our method, the humanoid robot arm motion generation is formulated as an optimization problem. Four different constraints, which cover a wide range of humanoid robot tasks, are considered: minimum time, minimum distance, robot hand acceleration and constant joint angular velocity. Results show that arm motions have different characteristics. In order to further verify the performance of humanoid robot arm motions, they are transferred in humanoid robot mobile platform.