Research On Trajectory Planning Technology Of Coal Cleaning Robot For Freight Train Cars

After the coal is transported by rail to the destination and unloaded,there is still more coal remaining on the surface of the car,which cannot meet the requirements of environmental protection and also causes a waste of energy.As an important equipment for coal carriage cleaning and recovery,the coal cleaning robot has the advantages of high automation,low regional dust,reduced personnel and increased safety.Trajectory planning plays an important role in improving the working efficiency and reducing the energy consumption of cleaning robot.In this thesis,a freight train car cleaning robot is studied and a time-energy multi-objective optimization function is established.In the range of kinematic and dynamic constraints,the improved Harris hawks algorithm is used to solve the optimal trajectory.Finally,the effectiveness of the proposed algorithm is verified through experiments.The main research contents of this thesis are as follows:(1)Based on the analysis of the transformation relationship between the robot coordinate system and the DH modeling method,the DH coordinate system of the robot is established by using the improved DH method.The kinematics model of the robot is deduced and verified.Lagrange method is used to establish dynamic model and calculate joint forces.The Monte Carlo method is used to calculate and analyze the working space,and the parameters of the cleaning robot meet the requirements of the cleaning work.(2)In order to select an appropriate interpolation method for the trajectory interpolation of the cleaning robot,the joint space trajectory interpolation method is selected by analyzing the working trajectory characteristics of the cleaning robot.The joint curve characteristics and trajectory fitting errors of the cleaning robot are studied by the joint space interpolation method based on several working conditions in the working trajectory.The results show that the joint motion curves of quintic B-spline interpolation are continuous and smooth,and the trajectory fitting accuracy is high.Therefore,the quintic B-spline interpolation is selected for the trajectory interpolation which can be optimized later.(3)The time and energy optimal objective function of the cleaning robot is established,and the trajectory optimization is carried out by using the improved harris hawks algorithm.The results show that in the three working conditions,compared with before optimization,the time and energy optimization based on IHHO improves the most,and the convergence also has advantages compared with other algorithms.The curves of each joint with the optimal time and energy are smooth and continuous,and all meet the constraint conditions,which verifies the superiority of the proposed algorithm.(4)A cleaning robot experiment platform is built to verify the effect of the proposed algorithm.In the experiment,the performance optimization before optimization,the performance optimization based on harris hawks and the performance optimization of the proposed method under three working conditions were compared respectively.The results show that,compared with the other two methods,the proposed algorithm can improve the time and energy under the three working conditions.The joint curves obtain by the experiment and simulation after optimization have a high fitting degree,indicating that the cleaning robot can complete the low-energy operation under the joint running time obtained by simulation when the time and energy are optimal in three working conditions,and reach the optimal state of time and energy.Finally,the optimization effect of the proposed algorithm is verified.