Jingzhao Li
Papers
2
Total Citations
11
H-Index
2
About
Jingzhao Li is a robotics researcher whose work focuses on the intersection of locomotion stability and industrial automation, particularly for challenging environments like bipedal walking and deep-mine transport. His most impactful contribution, "Optimization-based gait planning and control for biped robots utilizing the optimal allowable ZMP variation region" (2018, 6 citations), introduces a novel method that balances walking stability with energy efficiency. By optimizing the Zero Moment Point (ZMP) variation region, Li’s approach enables biped robots to adapt their gait to uneven terrain without sacrificing stability—a critical step toward practical humanoid robots. More recently, Li has tackled the harsh conditions of underground mining with "Dynamic Inclination Identification Methods for Mine-Use Monorail Crane Transport Robots Under Dual Operating Conditions" (2024, 5 citations). This work improves the accuracy of dynamic tilt sensing on curved rails, directly enhancing the safety and reliability of autonomous transport in deep mines. Li’s research elegantly bridges theoretical optimization with real-world constraints, demonstrating a clear commitment to deploying robots in physically demanding, safety-critical settings. His dual focus on legged locomotion and industrial robotics marks him as a versatile engineer advancing both fields.
Research Focus
Key Achievements
Top Papers
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- 2