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About

Caijiang Lu is a robotics researcher whose work spans industrial automation, soft robotics, and intelligent control systems. His key research areas include multi-joint industrial robots for additive manufacturing, de-icing and power line inspection robots, and novel artificial muscles. Lu’s major contributions include developing a postprocessing and path optimization method that addresses nonlinear error in multi-joint industrial robots for 3D printing of complex freeform surfaces—his most cited work with 12 citations. He has also pioneered negative-pressure artificial muscles with fiber constraints and pre-stretched soft skin, achieving high-performance actuation while addressing the challenge of unpredictable skin wrinkles. His dynamic modeling approach for soft pneumatic robotic arms, integrating geometric nonlinearity and visco-hyperelasticity, represents a significant theoretical advancement. Lu’s impact is demonstrated through his publications in 2020–2024, including work on fuzzy PID control for de-icing robot speed optimization and deep learning-based obstacle detection for power transmission lines. His notable achievements include developing a passively stretchable vacuum-powered artificial muscle with variable stiffness skin, and an insulation skin wrapping robot for overhead distribution lines—practical solutions addressing real-world infrastructure challenges.