Neuromorphic sensing and control for robotic manipulator-position, force and impact control

Summary form only given. The authors discuss a neural-network (NN)-based robotic motion control system, the neuromorphic control system, employing the neural servo controller (NSC). The NSC uses the NN including time delay elements in the hidden layer so as to learn the dynamics without information about accelerations. Simulations of both position and force control are carried out with consideration of nonlinear collision phenomena. The proposed approach is shown to be particularly valuable in sensing and recognition of collision phenomena employing proximity sensors, and in control of nonlinear systems with unknown parameters. A Hertz-type model with energy loss parameter was adopted to express the impact force. It was also shown that, since the NSC can sense conditions, the NSC can achieve nonlinear feedback both in position control mode and in force control mode to avoid the influence of collisions