| In recent years,with the update of manufacturing technology around the world and the concept of smart manufacturing put forward one after another,the manufacturing industry has been blowing the horn of transformation to smart manufacturing.With the development of technology,there are more and more kinds of shaped workpieces,and the labor force for basic processing of shaped workpieces is gradually decreasing,and the demand for basic industries such as grinding and polishing for replacing manual processing of workpieces with robot processing is increasing.The research on robot technology in the production of shaped workpieces is becoming more and more important.There has been a lot of research on shaped workpiece production technology.In the area of workpiece surface slicing planning,scholars focus on using different methods to slice the surface,and neglect the problem of connectivity planning between slices after slicing.In the area of robot trajectory planning,there is still room for improvement for some algorithms to fall into local optimum,and at the same time,the problem of robot speed,acceleration,and jerk continuity is not considered in the optimization as a whole,and the resulting trajectory still has an impact.In this thesis,we study the problem of efficiency improvement in the production of shaped workpieces,and we intend to use the surface partitioning algorithm with the introduction of K-means clustering of curvature-distance factor,the improved fruit fly optimal algorithm,and the particle swarm time-optimal trajectory planning algorithm based on the improvement of local chaos strategy.Firstly,this thesis divides the problem into the shortest planning problem for complex surface slicing connected paths in the processing stroke and the time-optimal trajectory planning problem in the auxiliary stroke.The Non-Uniform Rational B-Spline（NURBS）method is used to construct the free surface,and the NURBS surface reconstruction is carried out on the selected complex surface of the workpiece.The surface is subdivided into slices,and the generalized travel quotient problem is combined with the connectivity path planning.The mathematical model is built based on graph theory,and the shortest connectivity path is used as the objective function.The time-optimal trajectory planning study is carried out for the six-axis robot in the auxiliary stroke.The 4-7-4 segmented polynomial is selected as the basis of trajectory planning to ensure the continuity of displacement,velocity,acceleration and jerk during the motion of each joint of the robot,so as to improve the stability of the robot arm operation.In the study of time-optimal planning for trajectory,in order to improve the situation that the particle swarm algorithm falls into the local optimal solution,this thesis divides the population cognitive term in the particle swarm algorithm into local population term.In order to improve the situation that the particle swarm algorithm falls into the local optimal solution,this thesis divides the population cognitive term in the particle swarm algorithm into local population term and global population term,introduces chaotic mapping to solve the local population term,and combines the particle swarm algorithm improved by local chaos strategy with 4-7-4 segmented polynomials for time-optimal trajectory planning under the given constraints on the basis of dynamic change of learning factor method.The simulation experiments show that it has good results in time and trajectory continuity,and the effectiveness of the improved particle swarm algorithm for trajectory planning is demonstrated with the help of algorithm comparison.Finally,the simulation machining environment of the shaped workpiece is built by Robot Studio platform,the grinding trajectory is programmed and simulated by Maching Power Pac.The feasibility of the solution was verified by the achievable rate and the simulated machining path,and the offline programming simulation of the shaped workpiece was realized. |
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