Aiming at the inverse kinematic problem of 8-DOF redundant robotic manipulator system which was used for automatic fiber placement,a kind of algorithm was proposed for obtaining its self-motion manifolds and optimizing inverse kinematics.Firstly,position sub-manifolds and orientation sub-manifolds were defined based on the idea that position and orientation of end-effector could be decoupled,and position and orientation sub-manifolds in the form of parameterized formulations were both obtained by geometric methods.Then,according to the joint constraints and actual laying process,position sub-manifolds and orientation sub-manifolds were simulated for given end-effector posture,several inverse kinematic solutions from the manifolds were used to obtain the end-effector posture matrix by positive kinematics,which was consistent with the given posture matrix,so the correctness of self-motion manifolds calculation process was proved.Finally,based on the calculation of self-motion manifolds,a global inverse kinematic optimal objective function was proposed based on the parameterized self-motion formulation considering two aspects of manipulator moving smoothness and total joints motion variation.The aircraft tail was taken as the object of study and one of the laying paths was simulated to get the optimal inverse kinematic curves of self-motion variables and robotic manipulator joint angles.The simulation results were compared with a multi-objective optimization algorithm.The results indicate that the total variation of joints motion is decreased by 11.25%for the same laying path.The algorithm is valid for obtaining the self-motion manifolds and searching optimal solutions for each joint and self-motion variable based on the global optimal objective function,the proposed algorithm is also fit for the inverse kinematic problem of other redundant robotic systems in which position and orientation are decoupled.
关键词
冗余铺放机器人/八自由度/几何法/位姿分离/自运动流形/逆解优化
Key words
redundant fiber placement robot/8-DOF/geometry method/decouple of position and orientation/self-motion manifold/inverse kinematic optimization