Research And Implementation Of Delta Robot Time Optimal Trajectory Planning Algorithm Based On NURBS

In the fields of packaging,medicine and food it is necessary to repeatedly perform a large number of gripping and handling actions.Parallel robots have good dynamic performance,small size,high precision,and simple control.They are widely used in the above industries.In order to realize the smooth and high-speed movement of the parallel robot and give full play to the performance characteristics of its high-speed motion,it is necessary to plan its trajectory in the working environment to achieve the optimal trajectory of the robot.This paper focuses on the parallel robot interpolation algorithm and the optimal trajectory.It studies a time-optimal trajectory optimization algorithm using NURBS,and verifies the performance of the algorithm in a three-dimensional environment.Firstly,the Delta parallel robot was modeled.The structure of the parallel robot was simplified to obtain a simplified model.On this basis,the kinematics equations of the parallel robot were derived,the kinematic position and speed of the parallel robot were analyzed,and then the robot space singularity and working space range were studied.It is verified that there is no singularity in the parallel robot in the required workspace;secondly,introduces a class of motion-free forward-looking trajectory planning algorithms.First,a kind of algorithms performed in joint space is described.In the joint space,the excellent characteristics of polynomial fitting can be used to complete the trajectory planning calculation,but the polynomial fitting does not have a straight line segment,resulting in a slower robot movement speed.On this basis,T is introduced.Two types of linear programming algorithms,type T and type S.Then due to the joint space Trajectory planning does not strictly control the shape of the trajectory in Cartesian space,and a kind of algorithms for Cartesian space are introduced,including two kinds of trajectory planning algorithms: straight line and arc;thirdly,because parallel robots must not only ensure smooth trajectories,but also ensure that task completion time is as short as possible,based on the above requirements,a motion forward trajectory planning algorithm was studied.The algorithm is divided into two steps:offline trajectory optimization and online real-time tracking.The offline trajectory optimization uses an improved genetic algorithm,combined with interpolation To supplement the actual process,the initial population generation method was improved to make the initial population more uniform,and adaptivecrossover and mutation processes were added.To further improve the performance of the genetic algorithm,the optimization curve is finally obtained through the above method.Online real-time tracking is to use the NURBS interpolation algorithm to realize the optimized curve interpolation process,so that the entire optimal trajectory planning algorithm is completed in Cartesian space;finally,this paper builds a set of parallel robot motion control platform and a set of parallel robots 3D simulation environment,and the motion forward time optimal trajectory planning algorithmt is applied to the 3D simulation environment,which further verifies the reliability of the algorithm.The experimental results show that the time-optimal trajectory planning algorithm can give full play to the performance of parallel robots,meet the requirements of the parallel robots for smooth,high-speed,and accurate calculation indexes,and can be applied in actual industrial environments.