Time-optimal Trajectory Planning Of Six-joint Industrial Robot Based On An Adaptive Genetic Algorithm

As a major branch of the robotics industry,the development and application of industrial robots has been receiving much concerns all the time.With the development of the society and increasingly material demands,the operation quality and efficiency of industrial robots is drawing much concerns too.As a result,time-optimal trajectory planning becomes a very popular research among scholars.In this paper,PUMA560 robot is taken as the object of study and its kinematic model is established.On the basis of the above,a quintic polynomial is used to plan the moving trajectory of all joints of robot.In addition,an adaptive genetic algorithm(AGA)is applied to this study to optimize the motion time of each joint,so that the robot can complete scheduled tasks in shorter time.At first,the background and significance of this task as well as the development status and application prospect of industrial robots technology are introduced.Besides,some problems about trajectory planning are simply expounded.In addition,some research achievements with respect to this task made by the experts and scholars at home and abroad in recent years are investigated,reviewed and analyzed.The description method of the spatial point and coordinate transformation is expounded simply on the basis of theoretical knowledge about robotic kinematics.Furthermore,PUMA560 robot is taken as the object and its kinematic model is established.Then the variables of each joint are used to represent the pose of robot end-effector.Besides,robot inverse kinematics is analyzed and calculated.Based on the theory research of trajectory planning,linear interpolation and circular interpolation in Cartesian space are introduced while the quintic polynomial and transition interpolation with parabola in joint space are analyzed.In addition,simulation of robot trajectory planning in both Cartesian and joint space is carried out by means of MATLAB.At last,the mechanism of genetic algorithm and the impacts of the genetic operators on evolutionary process are analyzed.On the basis of above,AGA is applied to the research to optimize the moving trajectory of robotic joints.In addition,simulation of the moving trajectory of each joint of PUMA560 robot is carried out,and the results show that the method this paper proposed can preferably realize time-optimal trajectory planning.Meanwhile,this method can assure the smoothnessof angle position,velocity and acceleration curve of each joint,so as to ensure that the robot can accomplish its work in a stable and efficient way.