Kinematics Analysis And Dynamics Simulation For Up-down Material Robot

In the modern industry, labor force is more and more in short supply, especially inheavy environment of the bad industrial production, therefore industrial automationhas become the focus. Manipulator is the key industrial automation of mechanicalequipment. The performance of the manipulator requires continuously improving workprecision and working rate, increasing the institutions of freedom, improving theuniversality and flexibility, and to reduce costs, controlling simple, safe and reliabletherefore, industrial robots research at the frontiers of manipulator.Based on the robot kinematics and dynamics research, using D-H method toestablish the six degrees of freedom manipulator kinematics model type, get thekinematics equations, and go on the inverse kinematics analysis, then analyzes theworking space of the manipulator, laid a foundation to establish the manipulatortrajectory planning.This chapter first introduced the dynamic method, using Lagrange equation toestablish dynamics equations of the manipulator, and get the potential energy andkinetic energy of the manipulator. Using the3D modeling software PRO/E to get themanipulator3D model, and import to the dynamic analysis software ADAMS, thenadd the sports constraint drive. In all joints, get the joint torque, angular velocity andangle acceleration curve. Using the virtual prototype technology on the dynamics ofthe manipulator to improve the design performance, reduce the computational cost andproduct development time purpose.Finally, this paper introduces the path of the description of the manipulatortrajectory, and discussed the manipulator trajectory path optimization algorithm, thenuses it as the center, straight line to the inverse kinematics manipulator transformbackward and expanded to ADAMS dynamics simulation. The former is the importantprerequisite of optimization algorithm is proposed, and the latter can get the result ofoptimization algorithm necessary validation and evaluation. The simulation results show that the optimization algorithm in the guarantee time optimal, under the premiseof has good dynamic performance.