Baoyi Su
Papers
1
Total Citations
1
H-Index
1
About
Baoyi Su is a researcher whose work centers on robotics, multi-sensor fusion, and state estimation in complex environments, with a particular focus on maze-solving robots. In their most-cited paper, "Research on State Estimation Algorithm of Maze Robot Based on Multi-Sensor Fusion in Complex Environment" (2023), Su addresses a critical challenge in autonomous navigation: improving the accuracy and efficiency of state information for robots operating in intricate, unpredictable settings. The proposed algorithm employs an adaptive weighted batch estimation technique to fuse data from multiple sensors, enhancing the robot's ability to estimate its position and orientation in real time. This contribution is significant for advancing the robustness of autonomous systems in constrained or dynamic environments, with potential applications in search-and-rescue, exploration, and industrial automation. While Su's work has garnered 1 citation to date, it represents a foundational step in optimizing sensor integration for maze navigation, offering a practical solution to a longstanding problem in robotics. Su's research underscores a commitment to bridging theoretical algorithms with real-world robotic performance, making it a valuable reference for students and researchers interested in sensor fusion, state estimation, and autonomous navigation in challenging terrains.
Research Focus
Key Achievements
Top Papers
- 1