Papers
2
Total Citations
10
H-Index
1
About
Yulun Zhuang is a robotics researcher specializing in the control and optimization of dynamic legged and wheeled-bipedal systems. His work centers on two key challenges: achieving precise, energy-efficient locomotion and enabling complex maneuvers like jumping for underactuated robots. Zhuang’s most cited paper, “Height Control and Optimal Torque Planning for Jumping With Wheeled-Bipedal Robots” (2021, 9 citations), addresses the difficulties of nonlinear estimation and instantaneous impact during jumps, proposing a torque planning method that optimizes energy consumption for accurate height control. More recently, in “Kinodynamic Model Predictive Control for Energy Efficient Locomotion of Legged Robots with Parallel Elasticity” (2025), he introduces a hierarchical MPC framework that leverages unidirectional parallel springs to significantly improve energy efficiency in dynamic walking. This work demonstrates his ability to bridge theoretical control methods with practical hardware constraints. With a growing citation record and a focus on pushing the boundaries of agile, efficient robot locomotion, Zhuang is establishing himself as an emerging voice in the field of dynamic robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2