A Model of Spray Tool and a Parameter Optimization Method for Spraying Path Planning

The digital camouflage spraying of special vehicles carried out by robots can greatly improve the spraying efficiency, spraying quality, and rapid adaptability to personalized patterns. The selection of spray tool and the accuracy of the adopted mathematical spray tool model has a great impact on the effectiveness of spray path planning and spraying quality. Since traditional conical spray tool models are not suitable for spraying rectangular digital camouflage, according to the characteristics of digital camouflage, the coating thickness cumulative distribution model of strip nozzle spray tool for 2 D plane spraying and 3 D surface spraying is derived, and its validity is verified by simulation. Based on the accumulation velocity model of the coating thickness(AVCT) on the curved surface and aiming at spraying path planning within the same surface and different surfaces, a path parameter optimization method based on coating uniformity evaluation of adjacent path overlapping area is proposed. Combined with the vehicle surface model, parameters such as path interval, spray tool angle and spray tool motion velocity can be calculated in real-time to ensure uniform coating. Based on the known local three-dimensional model of vehicle surface and the comprehensive spraying simulation, the validity of the purposed models: the coating thickness on the adjacent path area(CTAPA), the coating thickness on the intersection of two surfaces(CTITS), the coating thickness on the intersection of a plane and a surface(CTIPS), and the optimization method of path parameters are verified. The results show that compared with the traditional spray tool, the strip nozzle can better ensure the uniformity of the coating thickness of digital camouflage spray. Finally, according to a practical spraying experiment, the results prove that the proposed models not only are effective but also meet the practical industrial requirements and are of great practical value.