Research On Trajectory Planning Of Six-axis Joint Manipulator Based On Time Optimization

With the increasing importance of industrial robots in intelligent manufacturing,in the face of the upgrading of manufacturing needs,people have higher requirements for the performance of robots.Not only are robots required to complete tasks accurately,they are required to ensure work under the premise of quality,shorten the working time of the robot and improve the working efficiency.Therefore,the thesis takes six-axis joint manipulator as the research object,and proposes a trajectory planning algorithm based on genetic algorithm with time optimization as the optimization target.The specific work and research results of the dissertation are as follows:(1)The kinematics modeling,analysis and simulation of the manipulator are studied.The mathematical model of the manipulator is established using the DH parameter method,and the kinematic equation is calculated.The inverse kinematic equation of the manipulator is solved by the combination of geometric method and algebra method.Unique solution is determined by using rule of "shortest travel".Then,the kinematics is simulated and analyzed by MATLAB to verify the correctness of the kinematics equations,and pave the way for subsequent trajectory planning.(2)The trajectory planning and curve approximation algorithms of the manipulator in Cartesian space and joint space are studied.In the cartesian space trajectory planning,the linear and circular interpolation algorithms are discussed,and the quaternion method is used for attitude interpolation.The polynomial curve interpolation and parabolic interpolation algorithms in joint space are discussed.For the above algorithms,there are disadvantages of curve swing.This thesis uses a method of cubic uniform B-spline curve approximation to irregular curves for trajectory planning.The algorithm is simple to calculate,has the advantages of continuous derivatives,local support,etc.,and makes the planning trajectory more smooth and controllable.Simulation is performed using MATLAB software to verify the feasibility of the cubic uniform B-spline algorithm is presented.(3)The applications of particle swarm algorithm and genetic algorithm in robot manipulator trajectory planning are compared and analyzed.Genetic algorithm has the advantages of multi-point search,strong adaptability,and good robustness.This thesis uses the piecewise processing characteristics of cubic B-spline curve to propose a time-optimal trajectory planning method based on improved genetic algorithm.The fitness function is designed to be combined with the penalty function,and the sine function is used to improve the standard genetic crossover probability and mutation probability to make it non-linearly change with the fitness function,which improves the convergence speed of the algorithm and the angular velocity in kinematics constrained by parameters such as angular acceleration,and trajectory planning using an improved genetic algorithm,the working time was shortened by 29.77%,which effectively improved the working efficiency of the manipulator.(4)We set up a six-axis joint manipulator control system experimental platform.Experiments were performed on the algorithms before and after optimization,and the experimental data were analyzed and fitted.The experiments proved the effectiveness of the proposed algorithm.