Inverse Kinematics Study for Intelligent Agriculture Robot Development via Differential Evolution Algorithm

摘要

Robots with intelligent moving and manipulating ability are able to improve productivity of agriculture work. We prototyped a mobile robot equipped with reductant manipulator (7-DOF). Here, for controlling the manipulator precisely, we investigate the inverse kinematics (IK) issue of the manipulator. A novel IK solving method by adopting an improved differential evolution algorithm has been validated. Also, random change crossover is employed to restrict the tendency of falling into local optimization when we use the algorithm. In parallel, considering the position and posture errors, boundary processing has been redesigned for avoiding joint limits. Thereafter, we obtain the global optimal IK solutions. Simulation tests have been carried out using the numerical model of the redundant arm. By testing accuracy and stability of the arm, we verify the feasibility and efficiency of the proposed approach.