Research On Key Technologies Of Grab Robot Control System Based On Trajectory Tracking Control Algorithm

With the development of society and technological progress,crawling robots have been widely used in various fields due to their powerful functions.However,in the context of the rapid advancement of industrial automation,the control precision requirements of grab robots are increasing,and traditional control technologies are difficult to meet the Accuracy requirements,accurate end-track tracking control technology has become the core key to solving the problem.Therefore,the research on the key technologies of the grab robot,especially the trajectory tracking control technology,is beneficial to improve the production and living standards of human beings,and has important strategic significance and application value.In this paper,the six-degree-of-freedom manipulator is used as the research platform.The trajectory tracking control technology and the visual grasping technology at the end of the manipulator are combined.The research work on theoretical derivation,simulation analysis and experimental verification is carried out around the key technologies of the grasping robot control system.Firstly,a set of grab robot control system combined with vision technology is designed based on the existing robot mechanical body.A hardware platform based on TwinCAT3 controller and a software platform based on robot end grab control strategy are built.The key techniques of the binocular vision system are introduced to the principle analysis and method.Secondly,the kinematics model of the grab robot is established based on the spin theory.Combined with the geometric method and the Paden-Kahan subproblem,a new inverse algorithm is proposed to realize the exact solution of the inverse kinematics model of the robot.In addition,the dynamic model of the grab robot is established based on the Lagrange equation and the spin theory.The accuracy of the mathematical model is verified by the simulation experiments based on Mathematica and ADAMS software,which provides the theoretical basis and model information for the subsequent trajectory tracking control algorithm.Then,a robust PD control strategy based on fuzzy self-tuning is proposed for the robotic arm system with high nonlinearity and strong coupling.The fuzzy controller is introduced to replace the parameter tuning process of traditional PD control,in order to realize the online self-adjustment of PD parameters.Then a robust adaptive compensator is designed to combine the robust algorithm with the adaptive algorithm to compensate for the uncertainty of the system.The theoretical derivation and MATLAB numerical simulation verify that the trajectory tracking error of this control strategy converges faster,improves the robustness and learning ability of the system,and has the feasibility of being applied to the complex mechanical arm control system.Finally,the simulation platform of the crawling robot system is designed based on MATLAB and ADAMS software.The trajectory tracking control algorithm of the robot are simulated and analyzed in this platform.Then the control algorithm is applied to the actual grab robot control system.The effectiveness and feasibility of the control algorithm and the end-fetching strategy are verified by the robot's end positioning experiment and vision-based target grabbing experiments.