Baiqiang Yao
Papers
1
Total Citations
3
H-Index
1
About
Baiqiang Yao’s research lies at the intersection of robotics, dynamic balance control, and human-robot interaction, with a particular focus on low-speed, compliant motion. His most cited work, “Robot Zero-Moment Control Algorithm Based on Parameter Identification of Low-Speed Dynamic Balance” (2022), introduces a novel zero-moment control torque compensation technique that enables robots to move in compliance with external forces. By compensating for gravity and friction, Yao’s algorithm allows robots to overcome small inertial forces, using the principle of torque balance to achieve intuitive, zero-moment dragging—a critical advancement for safe, collaborative robotics. Though early in his career, with this paper garnering 3 citations, Yao’s contribution addresses a fundamental challenge in physical human-robot interaction: making heavy industrial robots feel lightweight and responsive. His work is particularly relevant for applications requiring precise, low-speed manipulation, such as assembly or medical robotics. Yao’s approach, grounded in parameter identification and dynamic modeling, offers a practical pathway toward more intuitive robot programming and safer human-robot collaboration, marking him as a promising voice in the field of compliant robotic control.
Research Focus
Key Achievements
Top Papers
- 1