Autonomous path planning solution for industrial robot manipulator using backpropagation algorithm

Abstract

Here, we propose an autonomous path planning solution using backpropagation algorithm. The mechanism of movement used by humans in controlling their arms is analyzed and then applied to control a robot manipulator. Autonomous path planning solution is a numerical method. The model of industrial robot manipulator used in this article is a KUKA KR 210 R2700 EXTRA robot. In order to show the performance of the autonomous path planning solution, an experiment validation of path tracking is provided. Experiment validation consists of implementation of the autonomous path planning solution and the control of physical robot. The process of converging to target solution is provided. The mean absolute error of position for tool center point is also analyzed. Comparison between autonomous path planning solution and the numerical methods based on Newton-Raphson algorithm is provided to demonstrate the efficiency and accuracy of the autonomous path planning solution.

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

“…The Runge-Kutta method output perfectly matches with actual velocities. PeiJiang et al [112] used a backpropagation algorithm for the path planning solution in the autonomous robot. The path solution is presented by the numerical method.…”