Inverse Kinematics Solution of Rescue Robotic Arm Based on BP Neural Network

To solve the problem of the complexity and danger of natural disaster rescue, a rescue robotic arm with high load to weight ratio was proposed, and a three-dimensional model was established. The forward and inverse kinematics models of the multi-degree-of-freedom mechanical arm were established through the Denavit-Hartenberg method, and the simulation model of the rescue robotic arm was established by using the MATLAB robot toolbox to verify the correctness of the forward and inverse kinematics models. A 10-input, 5-output, 3-layer BP neural network was used to predict the inverse kinematics, and the 4 group kinematics inverse solution was screened to obtain the only accurate inverse solution, which lays a foundation for the realization of the subsequent trajectory planning of the robotic arm.