A memristor cross array-based robot control system and method. Said system comprises a sensor group, an input sensing signal modulator, a neuromorphic circuit, an output control signal modulator, an output device, an external supervision module, and a training controller; the control of a robot is executed by the neuromorphic circuit, and the main part thereof is a memristor cross array having a fully-connected neural network structure. Both a differential amplification circuit and a multiplexing switch in the neuromorphic circuit are connected to the memristor cross array, an input signal vector is multiplied by a weight matrix stored in the memristor cross array, and the product is processed by the differential amplification circuit to obtain one or more analog output signals. The control system uses a memristor neuromorphic circuit to reduce power consumption of the existing robot control systems during execution of a neural network operation, and directly uses memristors to simulate weights in a biological neural network, effectively reducing the complexity, and increasing the response speed.
MEMRISTOR CROSS ARRAY-BASED ROBOT CONTROL SYSTEM AND METHOD