Joint Angle Path Optimization for Robotic Arms Considering Energy Consumption Based on Genetic Algorithms

This paper presents a study on optimizing the joint angle path of a six-degree-of-freedom robotic arm, considering energy consumption, using a genetic algorithm. Initially, a mathematical model of the arm's motion is developed based on its structure, employing D-H parameters to construct transformation matrices and establish a forward kinematics model. The primary objective is to minimize the end-effector position error. Subsequently, the model is extended to account for energy consumption. The genetic algorithm is employed to determine the optimal joint angles, resulting in values of (129.9785, −129.9785, 32.0883, −84.4207, −32.2705, −21.8219) with a minimal end-effector error of $0. 0 0 0 2 9 0 1 3\ \text{mm}$. Considering the given joint inertia and average angular velocity, the optimal joint angle path, within an allowable error range of 200 mm, is found to be (47.796625, −47.79669262, 4.78158476, −90, 0) with an energy consumption of ${5. 1 1 2 5\ \mathrm{J}}$.