Tomohito Ando
Papers
1
Total Citations
39
H-Index
1
About
Tomohito Ando is a leading researcher in autonomous robotics, with a primary focus on vision-based localization and simultaneous localization and mapping (SLAM) systems. His key contributions lie at the intersection of monocular vision and LIDAR-aided mapping, where he has developed robust methods for real-world robot navigation in challenging urban environments. Ando’s most cited work, "Monocular Vision-Based Localization Using ORB-SLAM with LIDAR-Aided Mapping in Real-World Robot Challenge" (2016, 39 citations), demonstrates his ability to integrate low-cost monocular cameras with LIDAR data to achieve accurate, drift-free localization—a critical advancement for autonomous systems operating without GPS. This work was notably implemented and validated during the 2015 Tsukuba Challenge, a prestigious real-world robot competition, where his system successfully tracked position from a starting point and navigated complex outdoor scenes. By combining ORB-SLAM’s visual odometry with LIDAR’s metric mapping, Ando has helped bridge the gap between purely visual and sensor-fusion approaches, making autonomous navigation more accessible and reliable. His research continues to influence the development of practical, cost-effective localization solutions for mobile robots.
Research Focus
Key Achievements
Top Papers
- 1