Research On Trajectory Planning Method Of Hot Riveting Robot For Auto Parts Manufacturing

Our country is a big manufacturing country,and the automobile manufacturing industry is an important industry in our country’s manufacturing industry.Use industrial robots to realize the intelligent manufacturing of auto parts plays an extremely important role in the rapid advancement of our country’s transformation from a large manufacturing country to a manufacturing power.The parts that need to be assembled in automobiles have the characteristics of various types,large quantities and complex processes.Meanwhile,the production line of parts and components has high rhythm requirements.For example,the riveting operation of parts requires not only accurate positioning of the riveting points,but also reasonable planning of the movement of the riveting robot track,then improve the efficiency of parts production lines.Therefore,in order to realize the stable and efficient riveting operation of the robot,it is necessary to study the time-optimized trajectory planning of the riveting robot.Focusing on the need of robots to replace workers for safe,efficient and stable riveting operations in the production line of auto parts water tank brackets,this paper designs a set of hot riveting robot system,and completes the design of the robot end riveting execution structure and the rivet automatic feeding mechanism;electrical key Hardware selection;robot trajectory planning.Among them,in the trajectory planning method of the robot,an improved adaptive genetic algorithm is proposed as the trajectory planning algorithm of the riveting robot,aiming at the problems of prematurity and local optimal solution existing in the traditional algorithm.The simulation experiment is carried out through MATLAB and RobotStudio software,and a debugging platform is built for verification.Firstly,the quintic polynomial interpolation method is used to obtain the motion trajectory of the robot,and the trajectory optimization problem under multiple constraints is further studied.Finally,considering the nonlinear characteristics of trajectory optimization,the crossover and mutation operators are improved.The optimal adaptive genetic algorithm obtains the appropriate motion trajectory.The main research and work are as follows:(1)The riveting robot system framework is designed based on the hot riveting robot project of Hunan HeTun Electromechanical Equipment Co.,Ltd,which introduces the mechanical part of the system,mainly including the robot body,end riveting actuator,feeding and detection.Then,according to the functional requirements of the system,such as automatic feeding,automatic riveting,riveting pressure and displacement detection,rivet temperature detection,etc.,the structure design and device selection of its main hardware are carried out,and the electrical topology of the system is drawn.(2)Analyze the kinematics modeling of the riveting robot,establish the kinematic model and coordinate system of the riveting robot based on the DH parameter method,analyze the target pose of the riveting point through forward and inverse kinematics,and use the analytical method to obtain the inverse of the joint angle of the robot.Solution:In the robot joint space,the quintic polynomial interpolation method is used to study the motion trajectory planning of the robot,and the kinematic constraints of the robot’s six axes are considered,and the trajectory curve is simulated by MATLAB.(3)For the riveting robot time optimal trajectory planning problem,an improved adaptive genetic algorithm is used for trajectory planning.The fixed or linear crossover probability and mutation probability in the genetic algorithm are not suitable for nonlinear trajectory optimization problems,so the sine function is introduced to improve it as a nonlinear crossover and mutation operator,and the crossover and mutation probability are adjusted according to the characteristics of the individual population.The search ability of the algorithm can be used to obtain the motion trajectory with the optimal time performance that satisfies the constraints.Compared with the experimental data of the reference,the improved algorithm in this paper has significantly improved the running time of the robot joints.Finally,combined with the key pass nodes of the riveting robot and the operational constraints of the robot,the trajectory running time of the six joints of the robot is simulated,which can meet the requirements of the Project production cycle time requirements.