Papers
2
Total Citations
13
H-Index
2
About
Aoki Takanose is a robotics researcher whose work focuses on advancing autonomous navigation for mobile robots and legged systems. His key research areas include sensor fusion, localization, and state estimation, with particular emphasis on integrating GNSS, IMU, LiDAR, and leg odometry. Takanose’s major contributions include developing a GNSS/IMU localization system that uses time-series optimization with road gradient constraints, enabling accurate vehicle navigation even when wheel speed sensors are unavailable—a solution that has garnered 10 citations since 2023. More recently, he introduced tightly-coupled LiDAR-IMU-leg odometry, which incorporates online learned leg kinematics and foot tactile information to maintain robust performance in featureless environments and on deformable terrains. This work, published in 2025, has already attracted 3 citations, demonstrating its relevance to the field. Takanose’s research addresses critical challenges in autonomous navigation, from wheeled robots to legged platforms, and his innovative use of online learning for kinematics modeling represents a notable achievement. His work is particularly impactful for researchers developing robots that must operate reliably in unstructured or sensor-limited environments.
Research Focus
Key Achievements
Top Papers
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