Path Planning of Elbow Joint Robot Based on Neural Network in Dynamic Unknown Environment

The path planning problem of elbow joint robot has always attracted much attention. Some people use the A*algorithm to solve the problem of path planning. Based on the above algorithm research, this paper proposed the use of Neural Network models to solve the path planning of joint robot. By improving the algorithm, the path of the original model is optimized and accelerated. The stability of the system is verified through Lyapunov stability. Finally, add obstacles during the driving of elbow joint robot. The joint robot can avoid obstacles and form the most path in the driving course.