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It is quite difficult that chaotic neural dynamics in higher dimension is applied to robots with multiple (but finite) degree of freedom (DOF). Inspired by the fact that fewer muscles are controlled by a larger number of neurons, a simple coding method enables higher dimensional neural pattern to be translated into lower dimensional motion parameters. Although only three typical gestures are embedded into the neural network, the robot shows complex motions when chaotic neural dynamics emerges. By means of this point, a simple control algorithm was proposed to solve an ill-posed problem, which means that the existence of solution cannot be guaranteed or certain solution cannot be guaranteed. Furthermore, experiments on hardware implementation indicate that the arm robot can find light source with rough and uncertain information successfully using the algorithm.