Research On The Trajectory Optimization Of Robotic Arm Based On Intermediate Point Obstacle Avoidance Algorithm

In the face of complex and dangerous scenes such as biochemical detection,disaster relief,interstellar exploration,and anti-terrorism,it is an important trend for robot to complete specific operation tasks instead of human.As an important branch of robot,robotic arm plays an increasingly important role.However,the control of the robotic arm still relies on artificial teaching mode,which restricts the work efficiency of the manipulator.How to get rid of the artificial teaching model and complete the trajectory planning independently and autonomously according to the environmental information is the key problem that needs to be solved urgently.In this dissertation,we select a six degree of freedom manipulator as prototype.Focusing on its working space trajectory planning and obstacle avoidance problem,we build the kinematics model,and put forward a new type of intermediate point obstacle avoidance algorithm(IPOA).The algorithm can automatically plan the path for manipulator,avoid obstacles effectively,and maintain high efficiency.IPOA algorithm uses a new collision detection strategy and fitness function.It uses genetic algorithm to optimize the intermediate point parameters and plan the ideal trajectory between the start point and the target point,so as to achieve the safe and efficient operation of the robotic arm.First of all,the kinematics modeling of the manipulator is done in this paper.The derivation of forward kinematics and inverse kinematics is completed.To ensure the accuracy and correctness of the model,the inverse solution is verified under the simulation condition.Next,the trajectory planning of joint space and Cartesian coordinate space is carried out,and the working space of the manipulator is analyzed through Monte Carlo method.Then,we use IPOA algorithm to achieve trajectory planning in the process of obstacle avoidance.The intermediate point parameters are optimized by genetic algorithm to minimize the joint space variations and end motion trajectory.Finally,the reliability,effectiveness and superiority of the IPOA algorithm are verified by experiments.The research results of this paper can provide reference for the autonomous motion planning of the manipulator in complex unknown environment.