slam-tutorial

Install ROS1::Noetic in Ubuntu 20.04

https://velog.io/@deep-of-machine/ROS-ROS1-%EC%84%A4%EC%B9%98-Ubuntu20.04-ROS-Noetic

Dataset

LiDAR: hdl LINK. CAMERA: HILTILINK

ros2 bag play -s rosbag_v2   uzh_tracking_area_run2.bag

ROS2 archive

https://github.com/stars/Taeyoung96/lists/ros2

install rosbag2

sudo apt install ros-foxy-rosbag2*

RUN bag file (https://storage.googleapis.com/hilti_challenge/uzh_tracking_area_run2.bag)

ros2 bag  play uzh_tracking_area_run2.bag -s rosbag_v2 --read-ahead-queue-size 1000  --topics /alphasense/cam0/image_raw /alphasense/cam1/image_raw

사전 준비물

1. Rosfoxy, Rosnoetic 설치
2. bashrc에 아래 명령어 추가

alias rosnoetic='source /opt/ros/noetic/setup.bash'
alias rosfoxy='source /opt/ros/foxy/setup.bash && sour    ce ~/gcamp_ros2_ws/install/local_setup.bash && source     ~/slam-tutorial_ws/install/local_setup.bash'

alias cba='colcon build --symlink-install'
alias cbp='colcon build --symlink-install --packages-s    elect'
alias killg='killall -9 gzserver && killall -9 gzclien    t && killall -9 rosmaster'
source /usr/share/colcon_cd/function/colcon_cd.sh
export _colcon_cd_root=~/gcamp_ros2_ws

3. Terminal 1: rosnoetic 실행 후 rosfoxy 실행
4. Terminal 1: bag 파일 play
5. Terminal 2: rosfoxy 입력 후 slam-tutorial build

cbp slam-tutorial

6. slam-tutorial 실행

ros2 run slam-tutorial main_node

To-do

1. Convert KITTI stereo to .bag format.
2. Implement PnP in call_back function to obtain R, t, and publish R, t.
3. Visualize published R, t via rviz

Library

1. tsl-robin-map