Papers
5
Total Citations
37
H-Index
3
About
Le Bao is a robotics researcher whose work focuses on intelligent control, sensor fusion, and localization for mobile robots and service platforms. His major contributions lie in developing adaptive control strategies for skid-steering mobile robots, particularly through online kinematic model parameter estimation and steering efficiency coefficient estimation, enabling robust motion control across varied terrains. Bao has also advanced indoor 3D localization by fusing ultra-wideband (UWB) sensors with barometric altimeters and inertial measurement units (IMUs), addressing challenges like multipath effects and occlusion. His most cited work, a 2021 paper on sliding mode controller design with fuzzy rules for a 4-DoF service robot, has garnered 23 citations, demonstrating its impact on the field. More recently, his 2025 paper "Geo-LSTM" introduces a geometry and temporal feature fusion algorithm for multi-sensor 3D localization, further pushing the boundaries of human-robot collaboration in dynamic environments. Bao’s research is notable for its practical focus on real-world deployment, combining theoretical rigor with sensor-driven solutions to enhance robot autonomy and interaction.
Research Focus
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