Multiple Joint Robotic Kinematics And Trajectory Planning And Simulation Research

As the industrial robot is so widely used in the field of welding, transport, stacking, and spraying,etc. The application of industrial robots is become more widely. As there are very strict requirements on robot posture during the use, and the requirements can’t be met through the way of teach. Therefore, we have to solve the inverse kinematics problem of robot, and on the basis of that not only the trajectory tracking will be done, but also multiple solutions will be optimized. Eventually teach function will be replaced, so that the intelligent level of the robot will be improved and that will achieve the off-line programming.For the algorithm of inverse kinematics solution of the of 6R robots which can’t meet PIEPER criterion calculation, its process is complex, or can’t work out the inverse kinematics equations. In order to solve this problem, an inverse kinematics algorithm with high accuracy based on Multiple Population continuous genetic algorithms was proposed. Multiple Population algorithms will improve the convergence precision and avoid algorithm trapping in local minimum. Continuous genetic algorithms will accelerate the convergence rate. Optimizing all of the inverse kinematics solution, then a global optimum solution was got. And planning joint angle trajectory of the robot, we can get an optimal robot continuous movement angle-time relationship. Experiment on Panasonic TA1400 robot, it verified that the proposed algorithm calculating the inverse kinematics solution is not limited by geometric structure, and the exact degree of the end position error is 2 decimals. So this algorithm can be used in high precision trajectory tracking. The main research of this paper is as follows:1) To introduce the situation of inverse kinematics calculate, optimization of multiple inverse kinematics, trajectory planning of joint space and the current research status of 3D modeling and simulation at home and abroad. Introduced the significance and the background of the research. Study the way of showing the spatial position and kinematics problem of multiple joint robotic. That laid a good foundation for subsequent general geometry calculating the robots inverse kinematics.2) A brief introduction to the principle of genetic algorithm. As the slow convergence speed and convergence precision of the algorithm is not high, to put forward multiple population genetic algorithm. For the inverse kinematics solution of general geometric 6R robots, using the basic genetic algorithm and the improved algorithm to calculate then will get a improved algorithm whose convergence speed and convergence precision are increase a lot. And that can be applied to engineering practice. At the same time, that will lay a good foundation on the multiple solution optimizations and the joint angle planning.3) To study multiple solutions problem of the robot inverse kinematics. Analysis the lineation of robot, to optimize the multiple inverse solution and get a unique engineering solution.Making line interpolation, parabolic interpolation, polynomial interpolation and spline interpolation for the optimized solution within the joint angle, and then analysis superiority-inferiority. And on the basis of these results, reference the length of Cartesian space trajectory, so that lay a good foundation for the trajectory tracking.4) To verify the effects of various interpolation results on the precision of trajectory tracking. Programing MATLAB for all trajectory planning, and simulate all trajectory planed angle, speed, acceleration and jerk, to check if they are sequential and finally get the best planning method. And compile robot 3D virtual simulation software.Do simulation study on the inverse kinematics solution and the optimized solution.The paper mainly studied the inverse kinematics solution of the of 6R robots which didn’t meet the PIEPER criterion,optimization inverse kinematics,joint angle space interpolation, and get a suitable algorithm for robot lineation. With the Robotic toolbox of MATLAB, the model mentioned above is proved. Finally, in this paper, all geometric linkage models of the robot were built by CATIA.A three-dimensional robot simulation software was developed based on the Open GL graphics technology and visual studio language and MFC technology of the 3D-CAD systems. The simulation system can be used to simulate and validate the robot trajectory planning and inverse kinematics, etc.