Research On Position Optimization Of Industrial Robot Base Based On Specific Tasks

Nowadays,the industrial robot technology is developing rapidly and its application field is more extensive than before.In most practical applications,the position of robot base remains unchanged.And once the position is inappropriate,the trajectory of the robot will be affected,which result in inefficient operation and singularity,even potential danger.The initial placement of robot base has a great influence on the performance of the work,so it is significant to choose a better base position when robot is executing a task.The relative position between the robot and the task is obtained finally by using the corresponding optimization algorithm,which will reduce the tedious positioning operation,make the industrial robot placement easier and more intelligent,and play a guiding role in the layout of the robot workstation.In this thesis,the optimization algorithm is applied in the industrial robot base placement problem.When a specific task given,robot kinematics and dynamics performance indexes are analyzed,and a single performance index is taken as the optimization target,with genetic algorithm and nonlinear programming algorithm combined to find an optimal position of industrial robot base,to make the performance of the work improved greatly.Firstly,the kinematics model of series robot is established,the inverse kinematics is calculated based on the screw theory.Meanwhile,based on that,the trajectory planning is studied,and the polynomial interpolation,orientation and position interpolation of three kinds of common trajectories are obtained.Secondly,the performance evaluation indexes of the robot are studied and calculated as optimization target,including kinematic flexibility,dynamic manipulability,time,energy and other important indexes,and a single performance index is taken as the optimization target,at the same time,the influence of different base position on the performance index is analyzed.Finally,a specific task and objective function is set up,and the nonlinear programming genetic algorithm is selected to find the best relative position between the base and the task with a single objective,with which several better locations or regions are given to make the study more practical.