Papers
39
Total Citations
624
H-Index
14
About
Nakju Lett Doh is a robotics researcher whose work spans mobile robot navigation, localization, path planning, and human-robot interaction. With a career spanning over two decades, he has made significant contributions to foundational challenges in autonomous mobile systems, accumulating hundreds of citations across his most influential publications. Doh's early work addressed the persistent challenge of odometry error in mobile robots, producing widely cited studies on accurate relative localization (58 and 44 citations) that demonstrated how systematic error modeling could dramatically improve navigation precision. His path planning research has been equally impactful — his spline-based RRT planner for non-holonomic robots (2013, 100 citations) stands as his most recognized contribution, offering practical motion planning solutions for real-world robotic systems. He further extended this work to coverage path planning (42 citations) and vacuum robot navigation, bridging theoretical algorithms with consumer robotics applications. Beyond navigation, Doh has pioneered human-robot interfaces using electrooculogram (EOG) signals, enabling eye-motion-based control of mobile robots — a notably inventive direction with accessibility implications. His later work on visual localization in large-scale indoor environments reflects a continued evolution toward vision-based, robust autonomy. Across these diverse threads, Doh's research consistently emphasizes practical reliability and real-world deployability.
Research Focus
Key Achievements
Top Papers
- 1Spline-Based RRT Path Planner for Non-Holonomic Robots100 citations · 2013
- 2Accurate relative localization using odometry58 citations · 2004
- 3Relative localization using path odometry information44 citations · 2006
- 4Online complete coverage path planning using two-way proximity search42 citations · 2017
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- 6VPass: Algorithmic compass using vanishing points in indoor environments28 citations · 2009
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