Junyuan Lu

State Key Laboratory of Industrial Control Technology

Papers

Total Citations

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About

Junyuan Lu is a pioneering roboticist specializing in locomotion control and tactile perception for advanced robotic systems. His key research areas include model predictive control (MPC) for wheeled bipedal robots and tactile-based 3D surface reconstruction. Lu’s major contribution is the development of a novel MPC-based pose controller for wheeled bipedal robots (WBR), which leverages virtual model control to simplify leg dynamics while maintaining robust stability and tracking performance—a breakthrough that has garnered 36 citations since 2023. Equally innovative is his work on Tac2Structure, a tactile sensing framework that enables robots to reconstruct object surfaces through repeated touch alone, without relying on vision. This approach, cited 9 times, addresses critical challenges in occluded or low-visibility environments, demonstrating how touch can substitute for sight in robotic exploration. Lu’s research bridges the gap between theoretical control systems and practical sensorimotor skills, offering scalable solutions for real-world deployment. His achievements highlight a dual focus on dynamic balance and non-visual perception, positioning him as a rising leader in embodied AI and autonomous robotics.