hdl_graph_slam

Disclaimer: The original work can be found at https://github.com/koide3/hdl_graph_slam and we take no credit for the author's work.

Kenji Koide, Active Intelligent Systems Laboratory, Toyohashi University of Technology [URL]
[email protected]

hdl_graph_slam is an open source ROS package for real-time 3D slam using a 3D LIDAR. It is based on 3D Graph SLAM with NDT scan matching-based odometry estimation and loop detection. It also utilizes floor plane detection to generate an environmental map with a completely flat floor. We have tested this packaged mainly in indoor environments, but it can be applied to outdoor environment mapping as well.

Results

Husky Dataset

video link

Quad Dataset

video link

Requirements

Note that this package should be installed in ROS indigo in Ubuntu 14.04

hdl_graph_slam requires the following libraries:

• OpenMP
• PCL 1.7
• g2o

Note that hdl_graph_slam cannot be built with older g2o libraries (such as ros-indigo-libg2o). Install the latest g2o: The latest g2o causes segfault. Use commit a48ff8c42136f18fbe215b02bfeca48fa0c67507 instead of the latest one:

git clone https://github.com/RainerKuemmerle/g2o.git
cd g2o
git checkout a48ff8c42136f18fbe215b02bfeca48fa0c67507
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=RELEASE
make -j8
sudo make install

The following ROS packages are required:

• geodesy
• nmea-msgs
• pcl-ros
• ndt_omp

sudo apt-get install ros-indigo-geodesy ros-indigo-pcl-ros ros-indigo-nmea-msgs

cd catkin_ws/src
git clone https://github.com/koide3/ndt_omp.git

[optional] bag_player.py script requires ProgressBar2.

sudo pip install ProgressBar2

Husky Dataset Instructions

Download husky.bag into catkin_ws/bags/

roslaunch hdl_graph_slam husky.launch
rosrun hdl_graph_slam bag_player.py bags/husky.bag

Quad Dataset Instructions

Download nardos3.bag into catkin_ws/bags/

roslaunch hdl_graph_slam nardos.launch