Research On Key Techniques Of Robotic Spray Painting Trajectory Optimization

Painting robot is a kind of important and advanced spray equipment. It is widely used in automotive manufacturing. The figure of a product and the tool parameters can strongly influence the quality of painting. In order to achieve the new spraying operation standards,new painting models and tool planning algorithms are active research for many years. This work is supported in part by the national natural science foundation program and in part by the high-tech research program of Jiangsu. The main work of this dissertation consists of four parts as follows:Firstly, due to the complex geometry of free-form surfaces, it is still a challenge to generate optimization trajectories of spray gun that satisfies paint uniformity requirements.And two methods of surface modeling are introduced. The triangular representation of a surface is introduced first. This paper discuss the construction of the flat patch adjacency graph (FPAG). Based on the FPAQ a merging algorithm is proposed to form big patches. Then another method of point cloud is discussed.The relative algorithms of point cloud slicing are deeply researched,including the determination of slicing thickness,the choice of slicing direction,the calculation of slicing date,the reconstruction of poly-lines etc.,so that the uniform slicing of point cloud is completed. The experimental results illustrate the feasibility andavailability of these algorithms.Secondly, two methods of tool path planning in spray forming processes are introduced. This paper proposes a tool path planning approach which optimizes the tool motion performance and the thickness uniformity. There are two steps in this approach. The first step partitions the part surface into flat patches based on the topology and normal directions.The second step determines the tool movement patterns and the sweeping directions for each flat patch. Based on the above twosteps, optimal tool paths can be calculated. Then another tool path planning method of point cloud is discussed. The point cloud data is obtained by scanning the surface of work piece, then slicing the point cloud data to estimate the normal vectors of the sampled points, so the tool path is formed through offsetting the distance between spray gun and work piece along the normal vectors. Experimental tests are carried out and the results validate the proposed approach.Thirdly, trajectory optimization of painting robot for3D solid is studied. A3D solid is divided into several patches by the evaluation function and trajectory optimization for each patch is performed. In order to satisfy the material uniformity requirements, optimization algorithms of the three different cases are developed to integrate the trajectories on the intersecting area of two patches. Tool trajectory for geometry-complicated parts are generated by partitioning them into individual surfaces,generating the trajectories for each partition, and then, interconnecting the trajectories from the different patches so as to minimize the overall path length. Three different solutions are presented to tool trajectory optimal integration problem.The first solution is based on genetic algorithms.The second one is based on ant colony optimization and the third one is based on particle swarm optimization. Experimental results demonstrate the effectiveness of the three methods and the quality of solutions that can be achieved.Finally, trajectory optimization of painting robot for surfaces is studied. Trajectory optimization of free-form surfaces is introduced firstly. Because the current paint deposition rate function is too complicated, the paint deposition rate function on a plane according to the experiment data is provided. The paint thickness function for free-form surfaces is also given. A multi-objective constraint optimization problem is formulated. An optimal tool trajectory with an optimal time and film quantity deviation is generated. And ideal point method is adopted here to calculate the values by iteration. Then the paint deposition rate function of electrostatic rotary bell applicator according to the experiment data is provided. The electrostatic spray painting experiment on automobile demonstrates the feasibility and availability of these optimization algorithms.