Research On Motion Planning Of Dual Redundant DOF Robot Based On Improved RRT Algorithm

With the continuous improvement of automation and intelligence in the production process of modern industry,robots play an increasingly important role in industrial production.Now researchers hope to get higher efficiency,safer working process and more flexible adaptability in the middle of robot research.Therefore,the optimization of robot trajectory and the application of dual robots are the focus of this paper,which has a certain practical significance.In this paper,the redundant industrial robot is taken as the research object,which mainly focuses on the path planning,trajectory optimization and coordinated movement of the two robots in the obstacle environment.The main purpose of the research is to provide a safe and effective robot motion planning scheme,as well as a more effective two machine cooperation scheme in the face of tasks that one arm is not competent for.In order to achieve these goals,the main contents of this paper are as follows:Firstly,the kinematics model of the robot is established.Firstly,the description method of robot’s position and pose in kinematics and the relationship between coordinate system are introduced.Secondly,taking iiwa14 as an example,this paper uses the D-H modeling method to build the forward kinematics content of the robot,and uses the numerical method to build the inverse kinematics content of the robot.Secondly,the improved fast search random tree algorithm is used to plan the path of the robot,and a safe and feasible path is obtained.Firstly,this paper introduces the algorithm of fast search random tree,and makes a simple analysis of its improved algorithm.Based on the fast search random tree algorithm,the GM RRT algorithm is proposed.Using the algorithm in random sampling points,the growth of new nodes and some improvements related to path optimization as innovation points.The new algorithm is simulated and displayed intuitively in the two-dimensional working environment,and then,combined with the characteristics of the robot model selected in this paper,the path planning in the robot joint space rather than the working space is determined.Finally,the simulation experiment of robot path planning in the environment with obstacles shows the feasibility of the improved algorithm.Thirdly,using the improved fast search random tree algorithm to get the joint path points in the path planning of the robot,adding the time parameters,and carrying out the compliance processing,finally using the intelligent optimization algorithm to optimize the robot trajectory.At first,the B-spline curve is selected to simulate the path of the manipulator,and the high-order differentiable trajectory curve is obtained to prepare for trajectory optimization.Then,particle swarm optimization is used to optimize the fitting trajectory.In this way,the work efficiency and stable work balance of the robot can be guaranteed as much as possible.Finally,the path points obtained in the previous chapter are used as the main data to optimize the robot trajectory.Finally,aiming at the efficiency advantage of the industrial robot in the production,the coordinated control of the dual redundant DOF Manipulator is analyzed.Firstly,numerical Monte Carlo method is used to calculate and display the workspace of the double manipulator,and then collision detection is carried out for the possible mutual collision in the work of the double manipulator.Finally,the kinematic constraints of the dual redundant DOF robot are analyzed.In order to verify the feasibility of the scheme,a simulation experiment is carried out for the handling of the dual redundant DOF robot.