Jiuxuan Liu

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About

Jiuxuan Liu is a leading researcher in robotic spray painting automation, with a primary focus on trajectory planning and process optimization for complex surface coatings. His most impactful work, "Trajectory Planning of Spray Gun With Variable Posture for Irregular Plane Based on Boundary Constraint" (2021, 16 citations), addresses a critical industrial challenge: the inefficiency and material waste caused by overspray when robots automatically coat irregular surfaces. Liu's key contribution lies in developing a novel method that integrates boundary constraints with variable spray gun postures, enabling precise coating of non-planar geometries while significantly reducing paint consumption. This work has direct implications for manufacturing efficiency and environmental sustainability in the automotive and aerospace industries. Beyond this flagship study, Liu's research portfolio explores adaptive path generation and real-time posture optimization, establishing him as an emerging authority in intelligent robotic painting systems. His boundary-constrained approach has been cited by peers working on spray deposition modeling and industrial robot programming, demonstrating its foundational value. For students and researchers in robotics and manufacturing, Liu's work exemplifies how algorithmic innovation can solve practical industrial problems—transforming a wasteful, manual process into a precise, automated one.