Emmanuel Tang
Papers
6
Total Citations
37
H-Index
4
About
Emmanuel Tang is a robotics researcher whose work sits at the intersection of bio-inspired aerial systems, sensing, and human-robot collaboration. His primary research areas include aerial robotics, simultaneous localization and mapping (SLAM), and hybrid kinematics modeling for specialized unmanned aerial vehicles (UAVs). Tang’s most significant contributions involve the development of the Flydar system—a passive scanning flying LiDAR that uses a single laser and the natural rotation of a nature-inspired airframe to achieve omnidirectional scanning for SLAM. He has also pioneered hybrid kinematics-force models for water-jetting aerial robots, drawing inspiration from the archerfish’s hunting mechanics to enable precise fluid ejection and force estimation. His work on magnetometer-based high angular rate estimation during gyro saturation addresses critical challenges in SLAM for rotating platforms. With over 37 citations across his most-cited papers, Tang’s research has practical implications for search and rescue, as demonstrated in his work on human-robot collaboration systems. His latest innovation, the Collapsible Airfoil Single Actuator ROtor-Craft (CASARO), explores soft robotics for rotary-wing flight, further showcasing his commitment to pushing the boundaries of aerial robot design and control.
Research Focus
Key Achievements
Top Papers
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