A Piecewise Varying Coefficient Dual Criterion Optimization Method for Motion Planning of Manipulators With Insufficient Redundancy

In order to solve the insufficient redundancy problem and slow convergence in multiple end-effector tasks, a piecewise varying-gain dual-criterion optimization (PVDO) method is proposed for motion planning of insufficient redundant manipulators. To achieve this, the convergence coefficients are designed to be piecewise varying, and the end-effector task is divided into two phases. In the initial phase, only the end-effector position task is considered and the fixed coefficient convergence method is adopted, which can take into consideration both end-effector task and secondary task optimization. In the second phase, the end-effector position and orientation are taken into account concurrently, and time-varying coefficients are used for end-effector task. The convergence coefficients are time varying to enhance the convergence speed, particularly when the errors are small in the later phase of task planning. This can ensure the optimization of secondary tasks when the manipulator is insufficient-redundant, and accomplish the end-effector task planning in a relatively fast speed. Finally, experiments are conducted to demonstrate the effectiveness of the proposed PVDO method in obstacle avoidance and joint limits avoidance.