Binghou Geng
Papers
2
Total Citations
31
H-Index
2
About
Binghou Geng is a robotics researcher specializing in the locomotion and control of quadruped robots, with a focus on enabling these machines to navigate complex, unstructured outdoor environments. His work bridges probabilistic modeling and optimal control to enhance robotic autonomy. Geng’s most-cited paper, “Leg State Estimation for Quadruped Robot by Using Probabilistic Model With Proprioceptive Feedback” (2024, 28 citations), addresses a critical challenge: robustly detecting leg phase transitions without relying on external sensors. By leveraging proprioceptive feedback, he advances the ability of legged robots to explore terrains as animals do, a key step toward field-ready autonomy. His second notable work, “Optimal Control of Quadruped Robot Using HQP-Based Virtual Model Control” (2023, 3 citations), introduces a hierarchical quadratic programming framework for optimal foot force distribution, combining virtual model control with acceleration-adaptive stiffness. This approach improves stability and efficiency in dynamic locomotion. Geng’s contributions are impactful for researchers in robotics and control systems, offering practical solutions for real-world legged robot deployment.
Research Focus
Key Achievements
Top Papers
- 1
- 2Optimal Control of Quadruped Robot Using HQP-Based Virtual Model Control3 citations · 2023