Neuromorphic sensing and control-impact control of robotic manipulator

A new approach for impact control of a robotic manipulator by a neural network (NN)-based controller is presented. Collisions are very quick phenomena and have strong nonlinearity. Therefore, it is difficult to sense collisions and to control a robotic manipulator undergoing collisions. The proposed approach has robustness against the impact force. It also has capabilities for sensing and perception of collisions by using a proximity sensor. In this case, the NN-based controller can use a nonlinear feedback in approaching the object to avoid impact. The NN-based control acquires these capabilities of its own accord.<
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