39 citations · 42 across the 6 of their papers we have counts for
6 papers
GLIM: 3D Range-Inertial Localization and Mapping with GPU-Accelerated Scan Matching Factors
Kenji Koide, Masashi Yokozuka, Shuji Oishi +1
This article presents GLIM, a 3D range-inertial localization and mapping framework with GPU-accelerated scan matching factors. The odometry estimation module of GLIM employs a comb…
MegaParticles: Range-based 6-DoF Monte Carlo Localization with GPU-Accelerated Stein Particle Filter
Kenji Koide, Shuji Oishi, Masashi Yokozuka +1
This paper presents a 6-DoF range-based Monte Carlo localization method with a GPU-accelerated Stein particle filter. To update a massive amount of particles, we propose a Gauss-Ne…
Tightly Coupled Range Inertial Localization on a 3D Prior Map Based on Sliding Window Factor Graph Optimization
Kenji Koide, Shuji Oishi, Masashi Yokozuka +1
This paper presents a range inertial localization algorithm for a 3D prior map. The proposed algorithm tightly couples scan-to-scan and scan-to-map point cloud registration factors…
Single-Shot Global Localization via Graph-Theoretic Correspondence Matching
Shigemichi Matsuzaki, Kenji Koide, Shuji Oishi +2
This paper describes a method of global localization based on graph-theoretic association of instances between a query and the prior map. The proposed framework employs corresponde…
General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox
Kenji Koide, Shuji Oishi, Masashi Yokozuka +1
This paper presents an open source LiDAR-camera calibration toolbox that is general to LiDAR and camera projection models, requires only one pairing of LiDAR and camera data withou…
Scalable Fiducial Tag Localization on a 3D Prior Map via Graph-Theoretic Global Tag-Map Registration
Kenji Koide, Shuji Oishi, Masashi Yokozuka +1
This paper presents an accurate and scalable method for fiducial tag localization on a 3D prior environmental map. The proposed method comprises three steps: 1) visual odometry-bas…