Research On Trajectory Planning And Optimization Of The Working Arm Of Tunnel Anchor Rod Trolley

As a self-moving multifunctional tunnel support equipment that integrates drilling,grouting,bolt installation and other processes,tunnel anchor trolley has broad development space by virtue of its high degree of mechanization and its compatibility with drilling and blasting method.However,the complex geological condition engineering represented by Sichuan-Tibet Railway and the continuous development of social economy put forward higher requirements for the automation degree and construction efficiency of tunnel anchor trolley.Based on the Control System Development project of "Research on Performance Improvement and Intellectualization of Tunnel Anchoring Trolley" of China Railway Tunnel Bureau Group,this thesis studies the fast automatic positioning control of the working arm of MT11 Z intelligent anchoring trolley,aiming at the problems of low accuracy,poor stability and low efficiency of the working arm of manually operated anchoring trolley.The research contents and results are as follows:1.According to the overall structure and control scheme of MT11 Z intelligent anchor trolley,the structure of working arm and the process of three-station operation are analyzed,and the number of degrees of freedom required for automatic positioning is obtained.The automatic positioning scheme of the working arm is determined to provide a basis for the subsequent research of automatic positioning algorithm.2.In order to ensure the automatic positioning accuracy of the working arm,the kinematics analysis is carried out.The kinematic model of the working arm of the MT11 Z intelligent bolt trolley was established by the improved D-H method,and the forward kinematic analysis was carried out to determine the corresponding relationship between each joint variable and the expected anchoring position of the bit under the base coordinate system.The transformation relationship between the operating plane coordinate system and the truck base coordinate system was obtained by using the parameters of the anchoring point position guided manually twice,and the information of the anchoring point coordinate system in the construction drawing was converted into the expected bit pose matrix in the truck base coordinate system.Then,the inverse solution of the kinematics model was obtained by numerical iteration method according to the expected bit position in the base coordinate system.Finally,the joint variables required for automatic positioning were obtained according to the anchorage point position information in the construction drawings.The correctness of the forward kinematics solution is verified by MATLAB simulation,and the accuracy and solving efficiency of the numerical solution meet the requirements.3.In order to ensure the smooth motion of the working arm in the process of automatic positioning,cubic polynomial,quintic polynomial and cubic B-spline curve interpolation algorithm are respectively adopted to carry out joint space trajectory planning for the working arm in point position working conditions and continuous path working conditions.Simulation experiments are carried out for a target anchorage point position,and comparative analysis is made from multiple perspectives such as smoothness and continuity of the trajectory.The experimental results show that the quintic polynomial interpolation algorithm has the best effect under the point operation condition.In the continuous path working condition,the quintic polynomial interpolation algorithm can realize continuous acceleration at the beginning and end state,effectively slowing down the flexible impact of the working arm at the beginning and end of the motion state,while the cubic B-spline interpolation algorithm plans a more stable trajectory,and does not require the speed and acceleration of each intermediate path point,which has obvious advantages in the actual construction.4.In order to improve the automatic positioning efficiency of the working arm,the improved particle swarm optimization algorithm based on adaptive inertia weight and asymmetric learning factor is used.The maximum speed and maximum acceleration of the working arm are taken as constraints,and the minimum total motion time of the working arm under continuous path working conditions is taken as the optimization objective.The trajectory planned by cubic B-spline interpolation algorithm is optimized within the time constraint of each trajectory,in order to improve the automatic positioning efficiency of the working arm as much as possible under the premise of safe velocity and acceleration.Through the simulation experiment,the improved particle swarm optimization algorithm is proved to be superior to the ordinary particle swarm optimization algorithm in the optimization efficiency and optimization degree.In order to make all joints of the working arm reach each intermediate path point at the same time,the optimization time of each section of path is unified according to the maximum optimization time of each joint,and the final optimal trajectory is obtained.After optimization,the automatic positioning time of the working arm is reduced by 29.07% compared with that before optimization.