An Efficient and Accurate Inverse Kinematics for 7-DOF Redundant Manipulators Based on a Hybrid of Analytical and Numerical Method

This paper proposes an efficient and accuracy inverse kinematic algorithm for 7-DOF redundant manipulators with obstacles avoidance and singularities avoidance based on the hybrid of analytical and numerical method (IK-HAN). Specially, the paper focuses on how to solve the inverse kinematics problem accurately and efficiently for a novel configuration, i.e. SSRMS-type manipulator. First, the elbow orientation is introduced and the algebraic relationship between the elbow orientation and joint angles is derived. Second, the optimization algorithm is designed to find the optimal elbow orientation based on Particle Swarm Optimization. To improve the efficiency, the equivalent optimization model based on the azimuth angle is investigated. Third, optimal models are developed to avoid obstacles and singularities and improve manipulability in the constraint domain. Moreover, how to employ optimization resolution to solve the inverse kinematics problem is discussed. Finally, the validity of the algorithm is verified via kinematics simulations and the result illustrates that the algorithm performs well in accuracy, stability and efficiency.