Papers
33
Total Citations
570
H-Index
10
About
Huan Tan is a robotics researcher whose career spans more than three decades, with expertise spanning robot trajectory planning, imitation learning, human-robot collaboration, and autonomous systems. Beginning with foundational work in the late 1980s, Tan made early contributions to optimal motion planning, developing discrete trajectory planners for robotic manipulators that optimized for minimum time and energy while respecting realistic physical constraints — work that garnered over 80 citations across two landmark papers. His research evolved to encompass machine learning for robotics, with notable contributions to Dynamic Movement Primitives extended for obstacle avoidance and computational frameworks integrating human demonstration with robotic self-exploration. These efforts in imitation learning reflect Tan's sustained commitment to making robots more adaptable and intuitive collaborators. His work on human pose detection for safe human-robot interaction and vision-based surgical instrument handling further demonstrates his applied focus on real-world deployment. Tan's most cited work — a 2020 comprehensive survey on robots during the COVID-19 pandemic, accumulating 262 citations — cemented his relevance in contemporary robotics discourse, highlighting autonomous systems as critical infrastructure during global crises. Collectively, his portfolio reflects a researcher who bridges theoretical rigor with practical innovation across robotics' most pressing challenges.
Research Focus
Key Achievements
Top Papers
- 1Robots Under COVID-19 Pandemic: A Comprehensive Survey262 citations · 2020
- 2
- 3
- 4A discrete trajectory planner for robotic arms with six degrees of freedom23 citations · 1989
- 5Towards safe robot-human collaboration systems using human pose detection19 citations · 2015
- 6Robotic Handling of Surgical Instruments in a Cluttered Tray18 citations · 2015
- 7
- 8
- 9Robots Learn Writing12 citations · 2012
- 10