Papers
16
Total Citations
199
H-Index
9
About
Haruo Takemura is a robotics and human-robot interaction researcher whose work spans mobile robot navigation, drone teleoperation, imitation learning, and 3D environment perception. With a career bridging foundational sensing techniques and cutting-edge machine learning, Takemura has made sustained contributions to how robots perceive, navigate, and interact with complex real-world environments. His early research established robust methods for robot self-localization using omnidirectional imaging and 3D geometric models, laying groundwork for intelligent mobile systems. His 2006 paper on integrated 2D-3D interfaces for mobile robot control, now with 30 citations, exemplifies his commitment to intuitive human-robot collaboration. This thread continued prominently in drone teleoperation, where his work on adaptive view management and gesture-based human-drone interaction—collectively accumulating over 50 citations—addressed critical challenges of navigation in occluded, three-dimensional structures. More recently, Takemura has embraced transformer-based imitation learning, contributing notable papers such as Bi-ACT and ILBiT, which apply bilateral control principles to enable dexterous robotic manipulation. His 2016 hybrid flying-walking robot for bridge inspection further demonstrates his versatility across applied robotics. Across more than two decades, Takemura's research reflects a consistent vision: making robots more capable, perceptive, and accessible to human operators.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3A hybrid flying and walking robot for steel bridge inspection24 citations · 2016
- 4Adaptive View Management for Drone Teleoperation in Complex 3D Structures19 citations · 2017
- 5Human-Drone Interaction: Using Pointing Gesture to Define a Target Object18 citations · 2020
- 6
- 7Memory‐based self‐localization using omnidirectional images17 citations · 2003
- 8
- 9MMM-classification of 3D range data13 citations · 2009
- 10