Shengyi Liu

China University of Mining and Technology

Papers

Total Citations

129

H-Index

About

Shengyi Liu is a robotics researcher whose work focuses on autonomous navigation, mobile robot design, and terrain-adaptive locomotion systems. His most significant contribution is in the development of autonomous navigation for mobile robots using SLAM algorithms under the Robot Operating System (ROS), addressing critical challenges in mapping accuracy and path planning efficiency for indoor environments. This work, published in 2022, has garnered 73 citations and demonstrates his expertise in sensor integration and real-time localization. Liu has also made notable advances in mechanical design, including an all-terrain wheel-legged hybrid robot (33 citations) that enhances obstacle-crossing capabilities through innovative locomotion, and an articulated tracked firefighting robot (23 citations) designed for operation in confined, hazardous spaces. His research bridges the gap between theoretical algorithms and practical robotic systems, with particular emphasis on robustness in complex environments. Liu's work on the wheel-legged robot showcases his ability to solve real-world mobility challenges, while his firefighting robot addresses critical safety applications. With a growing citation impact and a focus on deployable, adaptive robotic systems, Liu is establishing himself as a researcher who combines algorithmic innovation with practical engineering solutions for autonomous ground vehicles.