Papers
12
Total Citations
205
H-Index
9
About
Shuji Oishi is a robotics researcher whose work spans mobile robot navigation, agricultural automation, and human-robot interaction. His research has made notable contributions to how robots perceive, map, and operate within complex real-world environments, from greenhouse horticulture to large-scale outdoor settings. Oishi's most-cited contribution — a 2019 study on thermal comfort measurement using thermal-depth imaging (45 citations) — exemplifies his innovative fusion of sensing modalities for robotic monitoring. This thread continues through his work on thermal point clouds for human pose estimation and lifestyle support robots. In agricultural robotics, he has developed mobile systems capable of person-following, greenhouse mapping, and robust 3D semantic understanding to support harvest operations amid growing labor shortages, with these papers accumulating over 50 citations combined. His expertise in localization and mapping is equally impressive, spanning SeqSLAM-based navigation, ND voxel localization with RGB-D cameras, and large-scale 3D outdoor mapping. More recently, his tightly-coupled LiDAR-IMU-wheel odometry system with neural kinematic learning demonstrates continued innovation in robust robot localization under challenging conditions. Across his body of work, Oishi consistently bridges perception, mapping, and human-aware behavior — advancing robots capable of operating meaningfully alongside people in everyday environments.
Research Focus
Key Achievements
Top Papers
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- 4SeqSLAM++: View-based robot localization and navigation20 citations · 2018
- 5Large-scale 3D outdoor mapping and on-line localization using 3D-2D matching18 citations · 2017
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- 9Toward a robotic attendant adaptively behaving according to human state9 citations · 2016
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