Design of flying robot painting system for Indian railway passenger coaches

S, Vishal

doi:10.1016/j.matpr.2020.07.147

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…Based on this, a thickness distribution model was established, and simulations verified the effectiveness of the trajectory optimization method for a spray‐painting manipulator. Vishal (2020) solved the problem of UAV spray‐painting of a railway passenger coach and noted that the trajectory refers to the path of the spray gun, which depends on input parameters such as coach surface geometry, type of spray gun, paint type, spray shape, required paint thickness, rate of paint discharge, viscosity and density of the paint, and spray‐painting time. Fang et al (2020) adopted the minimum moving time of the grinding robot as the optimization objective, then used the ant colony algorithm to solve the path planning problem of a wall‐climbing grinding robot, taking reduced no‐load walking robot, necessary grinding surface quality, and working safety of the robot as constraints.…”

Section: Related Workmentioning

confidence: 99%

Research on path generation and stability control method for UAV‐based intelligent spray painting of ships

Cai

Zhou

Liu

et al. 2021

Journal of Field Robotics

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This paper presents an intelligent path planning method with multiple constraints to solve the problem of instability of unmanned aerial vehicle (UAV) intelligent spray painting (UAV‐ISP) systems for spray painting the outer panels of ships. Spray‐painting path planning is realized using the multiobjective particle swarm algorithm and ant colony algorithm. In addition, a stability control method for the UAV based on the linear active disturbance rejection control (LADRC) algorithm is proposed and controlled by Mission Planner ground station software to solve the stability control problem of UAVs during spray painting. Through the above two key technologies, the painting quality of the UAV‐ISP system is guaranteed. First, a three‐dimensional (3D) model of the ship was obtained in a 3D modeling environment. Then the paint paths were optimized using the multiobjective particle swarm algorithm. The optimized path planning results were then combined using the ant colony algorithm to obtain the final spray painting path. Force analysis of the UAV during spray painting was carried out using the Newton–Euler equation and catenary theory, and a mathematical model of the UAV spray‐painting system with multiload coupling was established. Finally, a stability control system for the spray‐painting UAV based on LADRC was designed. The experimental and simulation results show that the proposed painting path is accurate, the spray‐painting UAV has good stability, and the spray‐painting quality of the UAV‐ISP system meets the standards for the outer panels of ships.

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Section: Related Workmentioning

confidence: 99%

Research on path generation and stability control method for UAV‐based intelligent spray painting of ships

Cai

Zhou

Liu

et al. 2021

Journal of Field Robotics

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“…30 A new trajectory optimization method was proposed specifically for spray painting applications for simple spray paths environments by adjusting spray height, paint gun velocity, and distance between adjacent trajectories to improve paint coating thickness for a uniform finish. [31][32][33][34][35] Software such as Robot Studio can be used in a virtual environment to guide painting applications, and studies have shown its feasibility in industrial applications.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

Jakkula

Sethuramalingam

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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In this investigative study, the Taguchi design (L9) of experiments with TOPSIS multi-objective optimization is used for the robot nanopainting. The optimization objective is to maximize the film glue individually and minimize the surface blemishes and film thickness by varying the IRB 1410 robot painting parameters, such as the robot speed, pressure, and distance. The multi-wall carbon nanotube is infused into the paint materials using the ultrasonication process, and the mechanical properties are analysed with a comparison to regular paint materials. The virtual robot cycle time analysis is carried out for three different robot pathway patterns, namely linear, zig-zag, and circular. It is then compared with real-time experimental robot nanopaint on cold rolled close annealing steel materials. The obtained results show that surface roughness and thickness are minimized by 54% and 33.4%, respectively, using the robot nano spray coating when compared with regular spray coating. The film adhesive of robot Nano spray coating is maximized by 2.8% more than normal spray coating. A fuzzy logic expert system model is used to evaluate the surface finish characteristics of the nanopaint surface with low prediction error and with 89.2% confidence level. Heat transfer analysis of the robot nano-coated substrate is compared with that of the robot normal-coated substrate.

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Enhanced Coating Layer Resistance to Corrosion and UV Degradation with Robotic Nanospray Painting

Jakkula

Sethuramalingam²

2023

Arab J Sci Eng

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Design of flying robot painting system for Indian railway passenger coaches

Cited by 5 publications

References 2 publications

Research on path generation and stability control method for UAV‐based intelligent spray painting of ships

Research on path generation and stability control method for UAV‐based intelligent spray painting of ships

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

Enhanced Coating Layer Resistance to Corrosion and UV Degradation with Robotic Nanospray Painting

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