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Self-Motion Optimization Algorithm of Redundant Manipulator Based on Cartesian Space

In order to meet the Cartesian space trajectory planning, the inverse kinematics calculation of the redundant manipulator has high real-time requirements, and to ensure that the redundant manipulator avoids obstacles while keeping the position and attitude of the end constant, According to the structural characteristics of the S-R-S configuration seven-degree-of-freedom redundant manipulator, the inverse kinematics solution of the redundant manipulator is calculated by the analytical solution method. In this method, the self-motion of the redundant manipulator is described by the redundant joint angle, and the self-motion of the manipulator is limited by the quadratic optimization of the redundant joint angle in the Cartesian space, avoiding the conventional algorithm only using the joint space key point planning The end pose caused by self-motion is prone to offset. In order to make the pose of the end of the manipulator in a stable and invariable pose, an index of "off-center degree" is defined to represent the degree of the joint's deviation from the center position, and this evaluation index is used to describe the optimal configuration of the redundant manipulator, so as to establish the self-motion optimization function. A particle swarm optimization algorithm with linearly decreasing inertia weight is used to find the optimal solution of the self-kinematic optimization function. Finally, it is verified on the simulation platform that the self-motion optimization of the redundant arm can be completed quickly and effectively.