Shared Control of Robot Based on Adaptive Network-based Fuzzy Inference System

Abstract

The teleoperating system has the shortcomings of the limited instruction set and low control efficiency, which cannot efficiently complete complex tasks. To solve this problem, this paper proposes a robot shared control method based on the adaptive network-based fuzzy inference system, which includes two parts: local fuzzy autonomous control and adaptive fuzzy neural network based shared control, in which shared control implementations combine the robot's direct control commands with autonomous control to ensure that the robot correctly executes the operator's intentions, and can respond to the external environment in a timely manner, so that the robot can adapt changes in the external environment and adjust the movement trajectory in Real-time. Compared with the fuzzy control method, the experimental results prove the feasibility and effectiveness of the proposed method.