Research On Key Technologies Of Industrial Robot Oriented To Assembly Process

The long-term goal of "2035" puts forward "promoting new industrialization and accelerating the construction of a manufacturing power and a quality power".As a powerful tool to promote the transformation and upgrading of manufacturing industry,industrial robots play an irreplaceable role in China’s accelerated transformation from a manufacturing power to a manufacturing power.In the assembly work that plays an important role in the whole manufacturing system,assembly by industrial robots can effectively improve the manufacturing quality of products,reduce production costs and improve assembly efficiency.However,when traditional industrial robots are assembling,their motion trajectories are poor in stationarity and smoothness.And the service life is shortened due to mechanical shock and vibration.At the same time,when the robot faces the assembly scene,there are still problems such as inaccurate robot calibration,low precision and unclear target positioning and identification.These factors restrict the quality and efficiency of industrial robot assembly and also affect the transformation and upgrading of modern manufacturing industry.In view of the above problems,this paper has carried out the research work on the key technologies of industrial robots oriented to assembly process,optimized the assembly trajectory,accurately obtained and reached the expected position,and improved the identification and positioning accuracy of assembly targets.Finally,a simulation and practical experimental platform was built to complete the test of the above methods.The main research contents of this paper are as follows:The kinematics model of industrial robot is established and solved,and the basic theory of industrial camera calibration principle is expounded.Taking AUBO-i5 robot as the industrial robot model used in the experiment,the linkage coordinate system and the forward and inverse kinematics model of the industrial robot are established,and the kinematics model of the robot is solved,and its correctness is verified in MATLAB.The workspace is solved by Monte Carlo method and local point distribution extraction method in Coppelia Sim.The principle of camera imaging,the transformation between coordinate systems and the distortion principle in camera calibration are introduced in detail,which makes theoretical preparations for further improvement of camera calibration methods in the following chapters.A trajectory optimization method based on improved multi-objective grey wolf algorithm is proposed,and the simulation analysis is carried out in the motion trajectory oriented to assembly process.Firstly,several interpolation function planning methods in Cartesian space and joint space are introduced.In view of the fact that traditional trajectory planning methods can not meet the needs of practical application,modern intelligent swarm optimization algorithm is adopted to optimize the trajectory of robots.At the same time,the problems of insufficient population diversity,premature convergence and falling into local optimal trap in multi-objective gray wolf algorithm are improved,and time-impact is taken as the optimization objective function,taking into account the balance and coordination of the two.Ensure that the impact of the robot is as small as possible when the assembly trajectory time is shortened,so as to prolong the service life of the robot.The simulation experiment is carried out in MATLAB.The experimental results show that the improved multi-objective grey wolf algorithm can shorten the running time of the robot terminal while ensuring the normal and stable operation of the robot,and effectively improve the impact and improve the working efficiency of the robot.Aiming at the problems of inaccurate robot calibration,low precision and unclear target positioning and identification in the assembly scene,an improved camera calibration method of Zhang Zhengyou is proposed,which improves the calibration accuracy and accuracy.The nine-point calibration method is selected to complete the hand-eye calibration,so that the robot can reach the desired position accurately.The assembly target is identified and located through image preprocessing and shape-based template matching method.The proposed trajectory optimization method,calibration method and target workpiece identification and positioning method are verified by experiments,and the assembly scene is studied to simplify the assembly model,and a compliant assembly strategy using force sensors is proposed.The Coppelia Sim simulation platform was built for experiment,and the simulation experiment obtained superior trajectory planning effect and assembly results.Finally,the research results were migrated to the actual assembly experiment platform,and the effectiveness and feasibility of the method proposed in this paper were further proved by the actual experiment.