Research On Measurement Trajectory Planning Method Of Self-Driven AACMM

Automatic on-line measurement technology is an important quality control method in intelligent manufacturing.Manual joint arm measuring machine needs manpower to drag measurement,measurement force can not control,measurement posture and measurement path can not be repeated and other problems are not conducive to the subsequent error compensation,so the topic of self-driven joint arm coordinate measuring machine is proposed.Trajectory planning is an essential step to realize automatic measurement.Different trajectory planning methods will affect the measurement accuracy and efficiency.Based on the beneficial results of manipulator and AACMM,this paper carries out the research on the measurement trajectory planning of the self-driven AACMM.Firstly,the forward kinematics model was established according to the structure parameters of the self-driven AACMM,and the correctness of the model was verified.The structure analysis of the measuring machine shows that there is no closed solution,so the inverse kinematics is solved by numerical method,and the inverse kinematics model is verified.On the premise of knowing the rotation range of the joint,the working space range of the measuring machine is solved,and the error source of the measuring machine is analyzed,which lays a foundation for the subsequent trajectory planning.Secondly,a hybrid trajectory planning method combining joint space and Cartesian space was proposed based on the existing research on trajectory planning of manipulator,joint arm measuring machine and combined with the measurement requirements of selfdriven AACMM.The single point measurement process is divided into positioning process,measurement process and rollback process.S acceleration and deceleration planning is adopted in the joint space for the positioning process and the rollback process,and uniform linear interpolation motion is carried out in the Cartesian space for the measurement process.In order to ensure that all joints of the measuring machine start and stop at the same time,synchronous planning of multiple joints is required.In this paper,the standard ball is taken as the measurement object.After the hybrid trajectory planning is completed,particle swarm optimization algorithm is used to optimize the trajectory with time-impact as the optimization objective.Then,simulation analysis is carried out on the Matlab Robotics Toolbox platform for the optimized trajectory.The hybrid trajectory planning method was verified by using virtual prototype technology.The rigid-flexible coupling model of the measuring machine was built by combining Adams and Ansys software,and the collision parameters with the standard ball were set up to simulate the measurement of the sphere.The comparison between joint space trajectory planning and hybrid trajectory planning shows that the hybrid trajectory planning has higher measurement accuracy for specific points.The standard ball is simulated by using the mixed trajectory before and after the optimization of particle swarm optimization algorithm.According to the optimized trajectory,the probe speed of the measuring machine is more stable and the ball measurement accuracy is higher.Finally,the self-driven AACMM prototype is built,and the results of hybrid trajectory planning are imported into the upper computer for specific point measurement experiment and standard ball measurement experiment respectively.The experiment proves that the hybrid trajectory planning method and optimization algorithm proposed in this paper are feasible and effective.Figure[49] Table[21] Reference[85]...