Trajectory Optimization of Electrostatic Spray Painting Robots on Curved Surface

Abstract

Abstract:In this paper, a new practical electrostatic rotating bell (ESRB) cumulative rate model of painting is derived, and an experimental study on painting is carried out. First, the experimental method is used to obtain the radial thickness profile function of the spatial paint distribution of static spray. Then, a spatial trajectory-planning scheme for a spray-painting robot based on a rectangular model is presented. This method designs the spatial path of the spray-painting robot by using the cuboid model method after the optimal value is taken as the width d of the overlapping area of the two spray-painting strokes in the plane. The experimental results illustrate that the paint thickness basically meets the requirements, and the experimental results verify the effectiveness of the trajectory optimization method.

Area-Coverage Planning for Spray-based Surface Disinfection with a Mobile Manipulator

“…A similar deposition model is presented by Chen et al. [28] , where they consider a rectangular model for spatial paths for spray painting. Chen and Zhao [29] developed a deposition rate function on a plane according to experimental data, which they then used for multi-objective constraint optimization to determine the tool trajectory based on the requirement that the deposition is uniform.…”

“…The rate of deposition of the spray liquid on a surface perpendicular to the direction of the spray at a distance can be modeled as a Gaussian distribution with a standard deviation and zero mean. [27] , [28] , [34] , [96] The deposition rate at the center of the circular cross-section is . The parameters , , and can be determined experimentally.…”

Grasping Control of a UVMS Based on Fusion Visual Image Enhancement

“…At present, the optimal control methods of onshore industrial manipulator are relatively mature. In the next step, in order to obtain better underwater grasping effect and efficiency, we plan to use these methods in the acquisition of the underwater manipulator [28][29][30].…”

Optimized Combination of Spray Painting Trajectory on 3D Entities

“…Particle swarm optimization (PSO) is easy to implement and there is no need to adjust a lot of parameters compared with other optimization algorithms. Also, it does not need gradient information, which is an effective tool to solve the optimal combination [17][18][19]. In the algorithm, each individual is a particle, and each particle represents a potential solution.…”