Research On Kinematics Analysis And Trajectory Planning Method Of The Six DOF Robotic Arm

The robotic arm is a kind of automatic operation device that can imitate some action of human arms like grasping and moving objects or operating tools according to a fixed program. It can carry out heavy work instead of humans to realize mechanization and automation of production and can work in a harmful environment to protect the personal safety. So, it is widely used in machinery manufacturing, metallurgy, electronics, light industry and atomic energy sectors. Currently, the robotic arm has been brought to the attention of more and more departments. The kinematics analysis and trajectory planning are the main research direction of industrial robot control. An efficient and accurate inverse kinematics algorithm and a fast and smooth trajectory planning method have important significances for large-scale production of modern manufacturing and improving the working efficiency. Therefore, this article studied on the inverse kinematics and trajectory planning of manipulator respectively, and put forward an improved BP neural network algorithm to solve the inverse kinematics and an trajectory planning method based on the combination of different functions and an optimal time trajectory planning based on improved genetic algorithm.First, the paper introduces the representation of the robotic arm posture, models the manipulator with D-H method, analyses its forward kinematics and inverse kinematics problem. Take Dr. Robot H20 for example to simulate the forward kinematics and inverse kinematics modeling process. Secondly, in view of the problem that the inverse kinematics solving is complex, and the precision is not high, this paper puts forward an improved BP neural network method to solve the inverse kinematics problem. Compared with the BP network, the adjustment to the hidden layer excitation function makes the network convergence speed is faster and the error is smaller. It can solve the problem of inverse kinematics effectively. Then, we studied the path design problems about trajectory planning. In view of traditional trajectory planning method, proposed a new method that based on the combination of different frequency sine function and cosine function. This method has smaller velocity and acceleration, reduces the impact of the joint and mechanical wear. Finally, this paper proposes a time optimal trajectory planning method. An improved genetic algorithm was used to optimize the B spline function trajectory making the robotic arm get the shortest time to complete the given task within the joints constraint conditions. The result of simulation shows that the trajectory planning method not only shortens the operation time of the manipulator but also provides a smooth trajectory of each joint. It is conformed to the requirements of the movement.