Shenghao Zhang
Papers
9
Total Citations
94
H-Index
5
About
Shenghao Zhang is a robotics researcher whose work sits at the intersection of legged locomotion, autonomous control, and human-robot interaction. His research has made meaningful contributions to the design and control of quadruped and bipedal robots, with a particular focus on enabling agile, adaptive, and reliable movement across challenging real-world environments. Zhang's most influential work centers on wheeled-legged robotics, exemplified by the development of "Max," a quadruped robot engineered for multimodal locomotion that combines the energy efficiency of wheels with the versatility of legs — a paper that has already attracted 34 citations since 2023. His broader portfolio addresses key challenges in quadruped locomotion, including terrain-adaptive gait planning, collision-free target tracking with disturbance rejection, and quadratic programming-based locomotion generation, collectively reflecting a systematic effort to push robots toward robust real-world deployment. Beyond locomotion, Zhang has explored human-robot interaction through attention-oriented action recognition frameworks and investigated bio-inspired skill transfer from biological dogs to robotic platforms. His work on collective robotic construction further demonstrates an interdisciplinary range. With over 90 cumulative citations and several papers spanning design, learning, and control, Zhang is emerging as a versatile and productive voice in modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1Max: A Wheeled-Legged Quadruped Robot for Multimodal Agile Locomotion34 citations · 2023
- 2Attention-Oriented Action Recognition for Real- Time Human-Robot Interaction16 citations · 2021
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