lidar_cloud_to_image

Conversion from 3D LiDAR pointcloud to images

This work was inspired on cloud_to_image from I. Bogoslavskyi, C. Stachniss, University of Bonn https://github.com/PRBonn/cloud_to_image.git

Operation

Several 3D LiDARs are supported:

• Velodyne: HDL-64-S2, HDL-64-S3, HDL-32, VLP-32, VLP-16
• Ouster: OS-1-16, OS-1-64 (both in 512, 1024 and 2048 modes)

Several pointclouds are supported:

• XYZ
• XYZI
• XYZIR
• XYZIF
• XYZIRF
• XYZIFN
• XYZIRFN

(I=intensity, R=ring, F=reflectivity, N=ambient noise)

Several image output modes supported, depending on the pointcloud type:

• SINGLE: each image is independent
• GROUP: all images are grouped into one
• STACK: all images are combined one per channel
• ALL: single images + group images + stack images will be published

Examples:

• Group image for pointcloud type XYZIFN:

• Stack image for pointcloud type XYZIFN:

How to build

1. Create a ROS workspace (if necessary):

mkdir ~/wkspace-cloud2image/src -p
cd ~/wkspace-cloud2image/src
catkin_init_workspace

2. Clone this repository:

cd ~/wkspace-cloud2image/src
git clone https://github.com/alexandrx/lidar_cloud_to_image.git

3. Build it:

cd ~/wkspace-cloud2image/
catkin build

How to run

The following is an example how to generate images for an Ouster OS-1-64 in 2048x10 mode, pointcloud type XYZIFN, output all images in 8bpp, with histogram equalization and horizontal flipped, images resized 3x in vertical.

roslaunch lidar_cloud_to_image cloud2image.launch sensor_model:="OS-1-64-2048" point_type:="XYZIFN" v_scale:=3.0 output_mode:="ALL" 8bpp:=true equalize:=true flip:=true

To show the group-mode image:

rosrun image_view image_view image:=/c2i_group_image

And to show the stack-mode image:

rosrun image_view image_view image:=/c2i_stack_image

Todo

• Documentation
• [] VLS-128 support (more testing needed)
• [] Correct odd black horizontal lines
• [] Add HESAI Pandar64, Pandar40, and Pandar40p support
• [] Add Robosense RSLidar32 support