Chee How Tan
Papers
6
Total Citations
47
H-Index
4
About
Chee How Tan is a pioneering researcher in aerial robotics, specializing in the design optimization and autonomous navigation of innovative flying systems. His work centers on developing novel sensing and localization methods for challenging environments, particularly deep hazardous tunnels and GPS-denied spaces. Tan's major contributions include the creation of the Flydar system—a passive scanning flying lidar that uses a single laser and the robot's own rotating dynamics for omnidirectional scanning, enabling robust simultaneous localization and mapping (SLAM). He also advanced sparse sensing array optimization for extended aerial robot navigation, achieving 21 citations for his foundational work in this area. His research on magnetometer-based high angular rate estimation during gyro saturation has further enhanced SLAM reliability, garnering 10 citations. Beyond hardware, Tan has codified expert knowledge into efficient design guidelines and principles for innovative aerial robots, with multiple publications from 2021-2022. His work bridges theory and practice, offering reusable frameworks that empower novice designers. With a growing citation record and a focus on nature-inspired, efficient aerial systems, Tan is shaping the future of autonomous robot navigation in extreme environments.
Research Focus
Key Achievements
Top Papers
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- 4Efficient Design Guidelines for Innovative Aerial Robot Design5 citations · 2022
- 5Aerial Robot Design Principles in Creative Idea Generation and Evolution3 citations · 2022
- 6Efficient Design Principles for Designing Innovative Aerial Robots2 citations · 2021