Li-Hao Zhang
Papers
1
Total Citations
27
H-Index
1
About
Li-Hao Zhang is a researcher focused on mobile robotics and inertial navigation systems, with a particular emphasis on improving attitude estimation for portable robots. His most-cited work, "Attitude Estimation Algorithm of Portable Mobile Robot Based on Complementary Filter" (2021), addresses critical challenges in robot navigation: the drift and noise inherent in gyroscopes and accelerometers, as well as the high computational cost of traditional methods like extended Kalman filters (EKF) and particle filters (PF). Zhang’s key contribution lies in developing a complementary filtering algorithm that integrates data from an Inertial Measurement Unit (IMU) to achieve accurate, efficient attitude estimation with reduced computational overhead. This work has garnered 27 citations, reflecting its practical relevance to researchers and engineers seeking lightweight, real-time solutions for mobile robot localization. By offering a simpler yet effective alternative to complex filters, Zhang’s research supports the advancement of autonomous systems in resource-constrained environments. His contributions are particularly valuable for students and practitioners working on portable robots, where balancing accuracy and computational efficiency is paramount.
Research Focus
Key Achievements
Top Papers
- 1