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About

Jun Gong is a researcher specializing in robotic spray painting, with a core focus on tool trajectory optimization for complex curved surfaces. His work addresses critical challenges in automotive manufacturing, particularly the need for uniform coating thickness and efficient path planning on non-planar geometries. Gong’s most influential paper, “Tool Trajectory Optimization of Spray Painting Robot for ManyTimes Spray Painting” (2014, 16 citations), introduces a novel method for optimizing spray gun paths in multi-pass applications, directly improving coating quality and production efficiency. He has also developed trajectory models for conical and spherical surfaces, deriving three-dimensional coating growth rate models from experimental data to enhance precision on high-curvature parts. His 2015 paper on arc spray gun models further advances the field by incorporating fluid dynamics into trajectory planning for natural quadric surfaces. While his citation counts are modest, Gong’s contributions are foundational for researchers and engineers working on automated painting systems, offering practical solutions that bridge theoretical modeling and industrial application. His work remains a key reference for those seeking to optimize robotic spray painting for complex, free-form surfaces.