From the 1 of 6 linked papers with an AI index.
6 papers
KING: Embodiment-Aware Kinematic Graph Neural Network for Unified Motion Representation of Legged and Wheeled Robots
Taku Okawara, Aoki Takanose, Kenji Koide +2
Kinematic models provide reliable motion constraints for odometry estimation in featureless environments, where exteroceptive sensing degrades and IMU integration drifts. Learning-…
Image-to-Point Cloud Registration Made Easy with Rectified Flow-based LiDAR Upsampling
Reon Tabata, Kenji Koide, Shuji Oishi +4
The paper presents a method that converts a sparse LiDAR scan into a dense intensity image using conditional rectified flow, matches it to a camera image, and estimates the 6‑DoF p…
Towards the Automation in the Space Station: Feasibility Study and Ground Tests of a Multi-Limbed Intra-Vehicular Robot
Seiko Piotr Yamaguchi, Kentaro Uno, Yasumaru Fujii +4
This paper presents a feasibility study, including simulations and prototype tests, on the autonomous operation of a multi-limbed intra-vehicular robot (mobile manipulator), shortl…
3D Mapping Using a Lightweight and Low-Power Monocular Camera Embedded inside a Gripper of Limbed Climbing Robots
Taku Okawara, Ryo Nishibe, Mao Kasano +2
Limbed climbing robots are designed to explore challenging vertical walls, such as the skylights of the Moon and Mars. In such robots, the primary role of a hand-eye camera is to a…
Tightly-Coupled LiDAR-IMU-Leg Odometry with Online Learned Leg Kinematics Incorporating Foot Tactile Information
Taku Okawara, Kenji Koide, Aoki Takanose +4
In this letter, we present tightly coupled LiDAR-IMU-leg odometry, which is robust to challenging conditions such as featureless environments and deformable terrains. We developed…
Tightly-Coupled LiDAR-IMU-Wheel Odometry with an Online Neural Kinematic Model Learning via Factor Graph Optimization
Taku Okawara, Kenji Koide, Shuji Oishi +4
Environments lacking geometric features (e.g., tunnels and long straight corridors) are challenging for LiDAR-based odometry algorithms because LiDAR point clouds degenerate in suc…