Research On Path Planning And Trajectory Optimization For Industrial Six-axis Manipulator

Several industries,including the military,social production,and healthcare,use industrial robots.Industrial manipulator play a significant role in the manufacturing sector as a type of industrial robot that can increase production efficiency and decrease labor input.Yet,as current technology has advanced,the performance standards for industrial manipulator have become more demanding.As a result,their operational precision and work efficiency must be continually enhanced to match the demands of contemporary production.Path planning and trajectory optimization can increase the industrial manipulator’s productivity,decrease its running time and distance,thereby lowering its energy consumption,prevent erroneous trajectories and pointless vibrations during movement,and enhance the accuracy and stability of the robotic arm’s movement.As a result,it is very important to do research on path planning and trajectory optimization of industrial manipulator.The industrial six-degree-of-freedom manipulator is used as the research object in this paper to examine the kinematic analysis,obstacle avoidance path planning,and time-jerk optimal trajectory planning of industrial manipulator.The main elements include:(1)A mathematical model corresponding to the kinematics of the robot manipulator was created using the modified DH parameter method.Its forward and inverse kinematic formulas were then developed and thoroughly examined using the Matlab Robotics Toolbox.It was ultimately determined that the model can accurately reflect the kinematic characteristics of the robot manipulator.Eventually,the Monte Carlo technique successfully resolves the working range of the manipulator.(2)Analysis is done on the manipulator ’s collision detection system.A cylindrical envelope box is chosen to enclose the robotic arm and a sphere envelope box to enclose the obstacle,respectively,based on the construction of the manipulator under study in this research and the unique circumstances of the obstacle.The concept of transformation superposition simplifies the collision model,and the manipulator ’s collision detection procedure is established.(3)For the blindness and unpredictability of the RRT algorithm in expansion,an upgraded RRT algorithm is provided.This algorithm may more effectively increase the effectiveness of path planning and reduce the path cost by introducing the goal gravitational factor and cost function,among other things.The RRT algorithm and RRT* algorithm are compared and examined in the Matlab simulation working environment of two separate barriers.The simulation studies demonstrate that the approach reduces the path length,running time,and number of sample sites in accordance,and it can efficiently materialize a collision-free working route from the beginning point to the target point,proving the efficacy of the enhanced RRT algorithm.(4)Within the restrictions of the pertinent kinematics of the manipulator,a multi-objective optimal trajectory planning of a manipulator is performed using an upgraded particle swarm method with time-impact as the optimization objective.To address the issues of local search and local optimality that frequently arise in the conventional particle swarm algorithm,an enhanced secondorder oscillating particle swarm algorithm is developed.The usage of the modified particle swarm method reduces the running time of the manipulator and produces a smoother joint variable curve,according to simulation studies that are finally carried out using Matlab.