Name: Hibiki Kawai
Type: User
Company: Meiji University
Bio: Meiji University Department of Mechanical Engineering, Laboratory of Robotics. → Worker. Linkedin is used to summarize research achievements, qualifications, et
Location: Greater Tokyo
Blog: https://www.linkedin.com/in/hibiki-kawai/
Hibiki Kawai's Projects
This Github repository combines the class identification NN and the numerical regression NN in a single Docker image
Beginner's guide to learn basic way of thinking and representative algorithms for Autonomous Vehicle Control.
Inference camera's attitude from mono and depth image using DNN
Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.
Provides ROS integration for Cartographer.
YOLO ROS: Real-Time Object Detection for ROS
DJI RS2の制御用プログラム
ROS based controller for DJI RS3 Pro
🐳 Dockerfiles to provide HTML5 VNC interface to access Ubuntu LXDE + ROS
🐳 Dockerfiles to provide HTML5 VNC interface to access Ubuntu LXDE + ROS2
This repository contains all necessary meta information, results and source files to reproduce the results in the publication Eric Müller-Budack, Kader Pustu-Iren, Ralph Ewerth: "Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification", In: European Conference on Computer Vision (ECCV), Munich, 2018.
https://ozakiryota.github.io/about_me/papers/sii_2021.pdf code for sii2022
カメラ等のセンサを用いた姿勢推定手法
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping