Papers
30
Total Citations
556
H-Index
14
About
Takuji Kubota is a pioneering researcher whose work spans two transformative domains: neural network-based visual servoing for robotic manipulators and bio-inspired robotic systems for planetary and subsurface exploration. In the early 1990s, Kubota made foundational contributions to visual control of robotics, developing self-organizing neural network frameworks that directly integrated visual feedback into manipulator control loops — work that has collectively garnered over 100 citations and remains influential in robot vision research. From the late 1990s onward, Kubota turned his attention to space robotics, addressing challenges such as capturing tumbling satellites with autonomous manipulators (46 citations) and developing lightweight planetary rovers. Perhaps most distinctively, he pioneered a sustained research program in bio-inspired subsurface exploration robots, drawing inspiration from earthworm peristaltic locomotion to design excavation systems capable of burrowing through lunar soil. This innovative work, spanning studies of mole-type drillers, screw robots, peristaltic crawlers, and even sub-seafloor excavators, demonstrates exceptional creativity and long-term vision. With contributions ranging from fundamental robotics theory to applied planetary science instrumentation, Kubota's research profile reflects a rare breadth of impact across both terrestrial robotics and space exploration engineering.
Research Focus
Key Achievements
Top Papers
- 1Visual control of robotic manipulator based on neural networks63 citations · 1992
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- 4Self-organizing visual servo system based on neural networks41 citations · 1992
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- 7Micro Planetary Rover Micro 526 citations · 1999
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- 9Curved excavation by a sub-seafloor excavation robot24 citations · 2017
- 10Study on Mole-Typed Deep Driller Robot for Subsurface Exploration23 citations · 2006