Incremental approach for trajectory generation of spray painting robot

Abstract

Purpose This paper aims to present a new offline robot programming approach for automated trajectory generation on free-form surfaces targeted toward spray painting application. Design/methodology/approach In this paper, an incremental trajectory generation approach is developed where new paint passes are generated based on paint deposited on the surface as a result of previous paint passes. The trajectory is generated on real surfaces where optimal velocity is calculated using genetic algorithm considering parameters such as surface model, spray gun model, paint distribution model and task constraints. Findings The developed approach was implemented on various surfaces for different paint distribution patterns, and the simulation results reveal that the approach is flexible and efficient to handle variety in part geometry and paint distribution. From experimental validation and analysis of results thus obtained, the developed approach is highly promising compared to the existing methods. Research limitations/implications The approach assumes that the computer-aided design (CAD) model of the surface is available and is limited to surjective surfaces in a structured environment where the spray gun characteristics and process parameters are known beforehand. Practical implications The problem of programming a robot manually is overcome by automatically generating a sub-optimal trajectory which can be easily transferred to an industrial robot for spray painting the surface. Originality/value This paper discusses a new approach for automated trajectory generation from CAD model. The experimental validation of the developed approach is successfully performed on a highly curved test surface, and obtained results are in agreement with the simulation results.