Chengjie Gu

Nanjing University of Science and Technology

Papers

Total Citations

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About

Chengjie Gu is a rising researcher in the field of legged robotics, with a focus on state estimation and multi-sensor fusion for autonomous locomotion. His work addresses critical challenges in robot localization, particularly for complex platforms like legged and wheeled-quadruped robots operating in unstructured environments. Gu’s major contributions include the development of **LLIO (LiDAR-Kinematic-Inertial Odometry)**, a robust framework that integrates ground contact constraints with an iterated extended Kalman filter to overcome IMU estimation failures and improve localization accuracy. He also proposed a **multimode proprioceptive state estimation** system for wheeled-quadruped robots, combining motor encoders and IMU data to enable reliable long-distance navigation without relying on non-slipping stance leg assumptions. Though early in his career, his work has already garnered citations, signaling its relevance to advancing robust autonomy in legged systems. Gu’s research is particularly notable for addressing real-world constraints such as slippage and sensor noise, making his contributions valuable for practical deployment in field robotics.