Yingliang Bai

Beijing Academy of Artificial Intelligence

Papers

Total Citations

H-Index

About

Yingliang Bai is a robotics researcher whose work centers on the dynamic modeling and control of novel, self-balancing mechanisms. His most notable contribution is the development of a dynamic model for a self-balancing cubical robot capable of balancing on its edge—a challenging and unconventional problem in robotics. In his 2017 paper, Bai derived the robot’s equations of motion using both the Lagrangian and Kane methods, providing a rigorous foundation for control design. This work, which has garnered 4 citations, addresses a unique niche in mobile robotics, pushing the boundaries of how non-traditional robot morphologies can achieve stability. Bai’s research is particularly relevant for students and engineers interested in advanced dynamics, nonlinear control, and the design of agile, reconfigurable robots. His focus on precise mathematical modeling offers a valuable framework for tackling complex balancing tasks, making his contributions a stepping stone for future innovations in autonomous, self-righting, or multi-modal robotic systems.