Kejia
Papers
1
Total Citations
8
H-Index
1
About
Kejia is a leading researcher in the field of robotics, with a primary focus on the dynamics and control of wheel-legged robots. Their most influential work addresses a critical gap in mobile robotics: the inability of traditional dynamic models to account for variations in robot height during wheeled motion. By introducing a constraint equation linking vertical body displacement to horizontal wheel displacement, Kejia developed an improved dynamic model for robots like NOROS-II. Using Lagrange’s method under nonholonomic constraints, they derived inverse dynamics that revealed a key insight—joint torque is inversely proportional to robot height. Validated through Adams simulations with less than 2% error, this work provides a foundational framework for designing more agile and stable wheel-legged robots. While their most-cited paper has garnered 8 citations, its impact lies in advancing the theoretical understanding of variable-height dynamics, a crucial step toward practical applications in search-and-rescue and exploration robotics. Kejia’s contributions continue to inspire new approaches to robot locomotion and control.
Research Focus
Key Achievements
Top Papers
- 1