Junheng Li

University of Southern California

Papers

7

Total Citations

85

H-Index

3

About

Junheng Li is a robotics researcher specializing in legged locomotion, whole-body control, and humanoid robotics, with a particular focus on developing advanced control frameworks that push the boundaries of dynamic robot movement. His most influential contribution, a force-and-moment-based Model Predictive Control (MPC) framework for bipedal robots, has garnered over 48 citations and established a compelling approach to achieving highly dynamic locomotion using simplified rigid body dynamics across 10-DoF systems. This work has become a foundational reference for researchers tackling the complexity of bipedal motion planning and control. Beyond bipedal systems, Li has made significant strides in wheel-legged robot control, proposing pose optimization and quadratic programming-based force control strategies that enable robots to navigate challenging terrains and high obstacles with remarkable agility. More recently, his research has expanded into humanoid loco-manipulation — the synchronized coordination of locomotion and manipulation — including contributions to the open-source HECTOR humanoid platform and kinodynamic pose optimization for pushing heavy objects. With a growing citation record across multiple robotic platforms and control paradigms, Li represents an emerging voice in the effort to make versatile, dynamic robots a practical reality.

Research Focus

Key Achievements

3
H-Index
7
Papers
85
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Force-and-moment-based Model Predictive Control for Achieving Highly Dynamic Locomotion on Bipedal Robots
48 citations · 2021
📈 Most Prolific Year: 2021 (4 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Southern California

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago