A Metaheuristic Optimization Approach to Solve Inverse Kinematics of Mobile Dual-Arm Robots

This work presents an approach to solving the inverse kinematics of mobile dual-arm robots based on metaheuristic optimization algorithms. First, a kinematic analysis of a mobile dual-arm robot is presented. Second, an objective function is formulated based on the forward kinematics equations. The kinematic analysis does not require using any Jacobian matrix nor its estimation; for this reason, the proposed approach does not suffer from singularities, which is a common problem with conventional inverse kinematics algorithms. Moreover, the proposed method solves cooperative manipulation tasks, especially in the case of coordinated manipulation. Simulation and real-world experiments were performed to verify the proposal's effectiveness under coordinated inverse kinematics and trajectory tracking tasks. The experimental setup considered a mobile dual-arm system based on the KUKA (R) Youbot (R) robot. The solution of the inverse kinematics showed precise and accurate results. Although the proposed approach focuses on coordinated manipulation, it can be implemented to solve non-coordinated tasks.