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Research On Trajectory Planning Of Multi-target Manipulator Based On Particle Swarm Optimization

Posted on:2021-04-21Degree:MasterType:Thesis
Country:ChinaCandidate:J C HeFull Text:PDF
GTID:2428330602488639Subject:engineering
Abstract/Summary:PDF Full Text Request
With the further development of control technology and manufacturing technology,industrial robots have become one of the indispensable manufacturing equipment in modern manufacturing.Industrial robots have further established their advantages in application fields with their high versatility,adaptability,durability and stability.Nowadays,robots no longer complete the specified tasks in order to achieve conventional motion and control,which puts forward higher requirements on the accuracy,efficiency and stability of their running process.Robot trajectory planning,as an important part of the research on robot control systems,has always been a research focus for researchers to improve robot performance.Based on the combination of particle swarm iterative algorithm and simulation,this paper conducts related research on robot trajectory planning.The main research contents include the following aspects:(1)This article takes the PUMA560 six-degree-of-freedom robot as the research object,analyzes the mechanical structure of the robot,uses the DH parameter method to establish an effective mathematical model of the mechanical arm;uses MATLAB software to establish a simulation model,and performs forward and inverse kinematics simulation experiment.(2)Based on the inverse kinematics process,based on the algebraic mechanism,an improved numerical calculation M program is used to solve the inverse solution,and the eight sets of inverse solution values that are closest to the current robot are obtained,and the solution process of the entire program is only 1.5 Seconds,and using the MATLAB software calculation results to verify the correctness of the M program calculation,the relative error can be controlled within 0.4%.(3)In the choice of linear interpolation method for the robot running trajectory curve,select a high-order polynomial curve to establish the robot running interpolation trajectory.Both the initial and the end can be specified,and the joint angle,joint angular velocity and joint angular acceleration at each point in the running process have continuous trajectories.The entire trajectory of the robot is continuous and smooth,to a certain extent,avoiding the impact and vibration.(4)The multi-objective optimal trajectory planning method of joint space is studied and analyzed.Based on multi-objective particle swarm optimization algorithm,multi-objective(time,energy consumption,pulsating shock)comprehensive optimization of the robot's running trajectory is realized under consideration of multiple constraints.The optimized results were processed by normalization method,and the optimized time performance index reached 7%,energy consumption performance index reached 40%,and pulsation impact performance index reached 44%.Optimization Results.(5)ADAMS / View is used to build a virtual model of robot.The trajectory curve after iterative optimization is introduced to carry out the kinematics simulation experiment on the robot.The post-processing module ADAMS / PostProcessor verifies the correctness of the iterative algorithm for multi-target trajectory planning under multiple constraints.
Keywords/Search Tags:Industrial robot, Trajectory planning, Multi-objective particle swarm optimization, Normalized
PDF Full Text Request
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