Trajectory Optimization of an Industrial Robot Using Teaching–Learning-Based Optimization

摘要: In this work, a teaching–learning-based optimization technique is applied to control the industrial robot arm trajectory based on an inverse kinematics solution with energy consumption minimization. The problem considers the minimization of energy consumption during the process sequence of six degrees of freedom industrial robot. The assessment of energy criteria includes the computational modeling of the movement of the robotic arm. The considered technique is compared and validated on the industrial robot ABB IRB 1410 for trajectory optimization.