Horizontal Plane Extractor (or HoPE for short) is a ROS package for extracting horizontal planes given point cloud input. The planes can be for example the ground or a tabletop surface, with which robotic tasks such as navigation or manipulation can be performed with ease.

Installation

This package requests following dependencies:

• ROS (tested on Indigo, Kinetic, and Melodic)
• PCL 1.7+
• OpenCV (tested on 2.4 and 3.3)
• Boost
• Eigen

On a fresh Ubuntu 14.04+ system, you can install aforementioned packages by installing ros-<distro>-desktop using:

sudo apt-get install ros-<distro>-desktop ros-<distro>-compressed-*

Make sure to change <distro> to the ROS distribution you want to use.

After these prerequisites have been met, if you only want to use HoPE without ROS:

git clone https://github.com/DrawZeroPoint/hope.git
cd hope
mkdir build & cd build
cmake ..
make -j

Or with ROS:

cd catkin_ws/src
git clone https://github.com/DrawZeroPoint/hope.git
cd ..
catkin_make

Basic Usage

Assume hope is built without ROS:

cd ~/hope/build/devel/lib/hope
roscore
./hope_node ~/hope/example/ 1305031459.259760.png 1305031459.274941.png -0.2171 -0.0799 1.3959 -0.8445 -0.0451 0.0954 0.5251 

Or, assume hope/ is built with ROS and located at ~/catkin_ws/devel/lib

cd ~/catkin_ws/devel/lib/hope
roscore
./hope_node ../../../src/hope/example/ 1305031459.259760.png 1305031459.274941.png -0.2171 -0.0799 1.3959 -0.8445 -0.0451 0.0954 0.5251

The output should look like this:

You can also start it using rosrun, by default, we assume the pointcloud file model.pcd is located at ~

roscore
rosrun hope hope_ros

Note that since hope is mainly developed for robotic usage, running roscore beforehand is mandatory in all modes for now.

Advanced Usage

To reproduce the experiments in our paper:

Test on TUM RGB-D data

Using a single image pair (RGB and depth), in a terminal, navigate to the location of hope_node (typically in hope/build/devel/lib/hope), run

./hope_node {PATH}/TUM/rgbd_dataset_freiburg1_desk/ rgb/1305031459.259760.png depth/1305031459.274941.png -0.2171 -0.0799 1.3959 -0.8445 -0.0451 0.0954 0.5251

In this example, we assume that you have already downloaded the TUM RGB-D test set to your local folder {PATH}. The scenario to test on is given as the first parameter, followed by an RGB-D pair in that folder and the camera position parameters (-0.2171 ...), which could be found in the ground_truth.txt within the dataset. Please notice that the sequence numbers for an RGB-depth pair are not exactly the same.

Test on Indoor Lidar-RGBD point cloud dataset

With a point cloud file, in the terminal run:

./hope_node {PATH}/loft.ply ply

The ply parameter indicates the type of the point cloud, it can be ply or pcd. Please notice that to use HoPE extracting the horizontal planes within the point cloud, we must align the normal direction of these planes with the z-axis of that scene. We recommend using CloudCompare to do that.

Customize the parameters in real-time ROS usage

The launch files in launch/ provides some references for using HoPE in real-time. hope_ros.launch initialize the hope node and ready for extracting planes from given point cloud with cloud_topic. Note that this cloud only needs to be a mono one, i.e., no RGB information. To obtain the cloud with devices like RGBD cameras, you can turn to pub_cloud.launch.

You can get horizontal planes in a certain height range with the dynamic reconfigure tool. This function is useful when you only needs a tabletop rather than the ground. Note that the height is relative to the base_link frame.

License

MIT.

Cite

If you referred or used HoPE in your article, please considering cite:

@Article{s18103214,
AUTHOR = {Dong, Zhipeng and Gao, Yi and Zhang, Jinfeng and Yan, Yunhui and Wang, Xin and Chen, Fei},
TITLE = {HoPE: Horizontal Plane Extractor for Cluttered 3D Scenes},
JOURNAL = {Sensors},
VOLUME = {18},
YEAR = {2018},
NUMBER = {10},
ARTICLE NUMBER = {3214},
URL = {http://www.mdpi.com/1424-8220/18/10/3214},
ISSN = {1424-8220},
DOI = {10.3390/s18103214}
}