Zhenze Liu

Jilin University, Jilin Medical University

Papers

12

Total Citations

78

H-Index

5

About

Zhenze Liu is a robotics and control systems researcher whose work spans two complementary domains: biped locomotion dynamics and intelligent robot learning. His foundational contributions emerged through rigorous investigation of passive dynamic walking, where he analyzed bifurcation, chaos, and stability in compass-gait and kneed biped robots — work that collectively drew nearly 50 citations across multiple studies from 2006 to 2009. These papers established energy-based control strategies, slope-invariance laws, and anti-phase synchronization schemes that advanced understanding of how robots can walk efficiently with minimal actuation. His 2009 work on adaptive compliant foot design with elastic energy storage demonstrated a particularly elegant biomimetic approach to reducing landing impact in humanoid locomotion. More recently, Liu has pivoted toward machine learning-driven robotics. His 2021 paper on reinforcement learning combined with dynamic movement primitives for obstacle avoidance — already accumulating 15 citations and his most-cited work — bridges classical motion generation frameworks with modern learning paradigms. His 2025 research on deep reinforcement learning with hindsight experience replay for dual-arm trajectory planning signals continued engagement with cutting-edge methods. Spanning nearly two decades, Liu's research consistently addresses the core challenge of making robots move reliably, safely, and intelligently in real-world environments.

Research Focus

Key Achievements

5
H-Index
12
Papers
78
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Reinforcement Learning with Dynamic Movement Primitives for Obstacle Avoidance
15 citations · 2021
📈 Most Prolific Year: 2009 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Jilin University, Jilin Medical University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago