Kinematics-Based Motion-Force Control for Redundant Manipulators With Quaternion Control

Motion-force control of redundant manipulators is universally regarded as a pivotal issue in industrial manufacturing, especially for the processing of precision instruments. This paper proposes a kinematics-based motion-force control (KBMFC) scheme for redundant manipulators, which is driven by joint velocity commands and different from the dynamics-based methods. Specifically, the force and motion are modeled and decoupled in the end-effector frame with the help of a stiffness coefficient. To control the orientation of the force, a quaternion control equation is designed by combining the rotation matrix and neural dynamics method. Different from traditional motion-force control methods, the proposed scheme is constructed as quadratic programming with the corresponding recurrent neural network (RNN) solver derived, which considers the kinematic optimization index and joint constraints. According to the generated control signals, a redundant manipulator is able to accurately fulfill the hybrid control of motion and force with the desired quaternion, which is intuitively confirmed by simulations and experiments. Note to Practitioners-This paper is motivated by the deficiencies that restrict the real-world applications of the motion-force control of redundant manipulators. On the one hand, most existing motion-force control schemes are implemented under the framework of dynamics, which inevitably leads to some kinematics-related defects. On the other hand, the latest kinematics-based techniques introduce an admittance control to achieve motion-force control. However, they model the force in the Z-axis of the base coordinate while the motion planning is limited in the X-Y plane, which dramatically reduces real-world applications. In this paper, the deformation force is designed in the end-effector frame, and a quaternion control technology of the end-effector is developed. Such a scheme can realize the real-time control of the orientation and magnitude of the force while ensuring trajectory tracking. In addition, the introduction of optimization indexes and joint constraints dramatically improves the functionality of the proposed scheme. Finally, the contributions of this paper are verified through simulations, experiments and comparisons. This work proposes a feasible framework for the motion-force control and orientation control of redundant manipulators.