Trajectory Planning Algorithm And Simulation Of A 6R Articulated Manipulator

As an important branch in the robot family, industry robot is an important research and development orientation. The trajectory planning and its control have been paid enough attention by researchers in the world. In the group of robots, the articulated robot is cared by designer and user for its broad work range, flexible movement and compact structure.Based on modularization, design a 6 DOF manipulator AS-MRobot6R which can achieve a certain assignment. In this paper, the kinematics and dynamics of the manipulator are analyzed by means of Denavit-Hartenberg method, then the kinematical and dynamic model of the manipulator are established. After the inverse kinematics of robot being solved with the pointed path, the motion path in joints space was optimized according to improved RBF Netural Network which had been trained by Fuzzy C Means clustering and the general application of nearest and K means clustering during planning. This arithmetic make the fast convergence and mistake amalgamation come true and avoid the infection of the input order of the restricted point and the existence of the erratic swatch numerical value, and achieves the request of the project, all of this validates its effectiveness and feasibility.Making use of the virtual prototyping technology, the manipulator's model is founded in software ADAMS that developed for dynamics analysis of mechanical system. Furthermore, according to the planed path, the changes of the cinematic and dynamic indexes of the articulated manipulator in the course of moving are studied. The effectiveness and validity of this approach are proved by theoretical analysis and simulation results. It will help a lot in the robot teaching, designing, researching and selecting.This improved RBF netural network arithmetic has great application value and provides theoretic information for the trajectory planning of robot.