===================
Ouster Example Code
:Description: Sample code provided for working with Ouster sensors
.. contents:: Contents:
:local:
Summary
To get started building the client and visualizer libraries, see the Sample Client and Visualizer_
section below. For instructions on ROS, start with the Example ROS Code_ section.
This repository contains sample code for connecting to and configuring ouster sensors, reading and
visualizing data, and interfacing with ROS.
ouster_client <ouster_client/>_ contains an example C++ client for ouster sensorsouster_viz <ouster_viz/>_ contains a basic point cloud visualizerouster_ros <ouster_ros/>_ contains example ROS nodes for publishing point cloud messages
Sample Client and Visualizer
Building the example code requires a compiler supporting C++11 and CMake 3.1 or newer and the tclap,
jsoncpp, and Eigen3 libraries with headers installed on the system. The sample visualizer also
requires the GLFW3 and GLEW libraries.
Building on Linux / macOS
To install build dependencies on Ubuntu, run::
sudo apt install build-essential cmake libglfw3-dev libglew-dev libeigen3-dev \
libjsoncpp-dev libtclap-dev
On macOS, install XCode and homebrew <https://brew.sh>_ and run::
brew install cmake pkg-config glfw glew eigen jsoncpp tclap
To build run the following commands::
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release <path to ouster_example>
make
where <path to ouster_example> is the location of the ouster_example source directory. The
CMake build script supports several optional flags::
-DBUILD_VIZ=OFF Do not build the sample visualizer
-DBUILD_SHARED_LIBS Build shared libraries (.dylib or .so)
-DCMAKE_POSITION_INDEPENDENT_CODE Standard flag for position independent code
Building on Windows
The example code can be built on Windows 10 with Visual Studio 2019 using CMake support and vcpkg
for dependencies. Follow the official documentation to set up your build environment:
Visual Studio <https://visualstudio.microsoft.com/downloads/>_Visual Studio CMake Support <https://docs.microsoft.com/en-us/cpp/build/cmake-projects-in-visual-studio?view=vs-2019>_Visual Studio CPP Support <https://docs.microsoft.com/en-us/cpp/build/vscpp-step-0-installation?view=vs-2019>_Vcpkg, at tag "2020.07" installed and integrated with Visual Studio <https://docs.microsoft.com/en-us/cpp/build/vcpkg?view=msvc-160#installation>_
Note You'll need to run git checkout 2020.07 in the vcpkg directory before bootstrapping to
use the correct versions of the dependencies. Building may fail unexpectedly if you skip this step.
Don't forget to integrate vcpkg with Visual Studio after bootstrapping::
.\vcpkg.exe integrate install
You should be able to install dependencies with::
.\vcpkg.exe install --triplet x64-windows glfw3 glew tclap jsoncpp eigen3
After these steps are complete, you should be able to open, build and run the ouster_example
project using Visual Studio:
-
Start Visual Studio.
-
When the prompt opens asking you what type of project to open click Open a local folder and
navigate to theouster_examplesource directory. -
After opening the project for the first time, wait for CMake configuration to complete.
-
Make sure Visual Studio is
building in release mode_. You may experience performance issues and
missing data in the visualizer otherwise. -
In the menu bar at the top of the screen, select Build > Build All.
-
To use the resulting binaries, go to View > Terminal and run, for example::
.\out\build\x64-Release\ouster_client\ouster_client_example.exe -h
.. _building in release mode: https://docs.microsoft.com/en-us/visualstudio/debugger/how-to-set-debug-and-release-configurations?view=vs-2019
Running the Sample Client
Make sure the sensor is connected to the network. See "Connecting to the Sensor" in the Software User Manual <https://www.ouster.com/downloads>_ for instructions and different options for network
configuration.
Navigate to ouster_client under the build directory, which should contain an executable named
ouster_client_example. This program will attempt to connect to the sensor, capture lidar data,
and write point clouds out to CSV files::
./ouster_client_example <sensor hostname> <udp data destination>
where <sensor hostname> can be the hostname (os-99xxxxxxxxxx) or IP of the sensor and <udp data destingation> is the hostname or IP to which the sensor should send lidar data.
On Windows, you may need to allow the client/visualizer through the Windows firewall to receive
sensor data.
Running the Sample Visualizer
Navigate to ouster_viz under the build directory, which should contain an executable named
simple_viz . Run::
./simple_viz <flags> <sensor hostname> <udp data destination>
where <sensor hostname> can be the hostname (os-99xxxxxxxxxx) or IP of the sensor and <udp data destingation> is the hostname or IP to which the sensor should send lidar data.
The sample visualizer does not currently include a GUI, but can be controlled with the mouse and
keyboard:
- Click and drag rotates the view
- Middle click and drag moves the view
- Scroll adjusts how far away the camera is from the vehicle
Keyboard controls:
============= ============================================
key what it does
============= ============================================
``p`` Increase point size
``o`` Decrease point size
``m`` Cycle point cloud coloring mode
``v`` Toggle color cycling in range image
``n`` Toggle display near-IR image from the sensor
``r`` Toggle auto-rotating
``shift + r`` Reset camera
``e`` Change range and signal image size
``;`` Increase spacing in range markers
``'`` Decrease spacing in range markers
``r`` Toggle auto rotate
``w`` Camera pitch up
``s`` Camera pitch down
``a`` Camera yaw left
``d`` Camera yaw right
``1`` Toggle point cloud visibility
``0`` Toggle orthographic camera
``=`` Zoom in
``-`` Zoom out
``shift`` Camera Translation with mouse drag
============= ============================================
For usage and other options, run ./simple_viz -h
Example ROS Code
The sample code include tools for publishing sensor data as standard ROS topics. Since ROS uses its
own build system, it must be compiled separately from the rest of the sample code.
The provided ROS code has been tested on ROS Kinetic, Melodic, and Noetic on Ubuntu 16.04, 18.04,
and 20.04, respectively. Use the installation instructions <https://www.ros.org/install/>_ to get
started with ROS on your platform.
Building
The build dependencies include those of the sample code::
sudo apt install build-essential cmake libglfw3-dev libglew-dev libeigen3-dev \
libjsoncpp-dev libtclap-dev
and, additionally::
sudo apt install ros-<ROS-VERSION>-ros-core ros-<ROS-VERSION>-pcl-ros \
ros-<ROS-VERSION>-tf2-geometry-msgs ros-<ROS-VERSION>-rviz
where <ROS-VERSION> is kinetic, melodic, or noetic. To build::
source /opt/ros/<ROS-VERSION>/setup.bash
mkdir -p ./myworkspace/src
cd myworkspace
ln -s <path to ouster_example> ./src/
catkin_make -DCMAKE_BUILD_TYPE=Release
Warning: Do not create your workspace directory inside the cloned ouster_example repository, as
this will confuse the ROS build system.
For each command in the following sections, make sure to first set up the ROS environment in each
new terminal by running::
source myworkspace/devel/setup.bash
Running ROS Nodes with a Live Sensor
Make sure the sensor is connected to the network. See "Connecting to the Sensor" in the Software User Manual_ for instructions and different options for network configuration.
To publish ROS topics from a running sensor, run::
roslaunch ouster_ros ouster.launch sensor_hostname:=<sensor hostname> \
udp_dest:=<udp data destination> \
metadata:=<path to metadata json> \
lidar_mode:=<lidar mode> viz:=<viz>
where:
<sensor hostname>can be the hostname (os-99xxxxxxxxxx) or IP of the sensor<udp data destination>is the hostname or IP to which the sensor should send data<path to metadata json>is an optional path to json file to save calibration metadata<lidar mode>is one of512x10,512x20,1024x10,1024x20, or2048x10, and<viz>is eithertrueorfalse: if true, a window should open and start displaying data
after a few seconds.
Note that if the metadata parameter is not specified, this command will write metadata to
${ROS_HOME}. By default, the name of this file is based on the hostname of the sensor,
e.g. os-99xxxxxxxxxx.json.
Recording Data
To record raw sensor output use rosbag record_. After starting the roslaunch command above, in
another terminal, run::
rosbag record /os_node/imu_packets /os_node/lidar_packets
This will save a bag file of recorded data in the current working directory.
It's recommended to
copy and save the metadata file at $(ROS_HOME)/<sensor_hostname>.json alongside the bag.
.. _rosbag record: https://wiki.ros.org/rosbag/Commandline#rosbag_record
Playing Back Recorded Data
To publish ROS topics from recorded data, specify the replay and metadata parameters when
running roslaunch::
roslaunch ouster_ros ouster.launch replay:=true metadata:=<path to metadata json>
And in a second terminal run rosbag play_::
rosbag play --clock <bag files ...>
If a metadata file is not available, the visualizer will default to 1024x10. This can be
overridden with the lidar_mode parameter. Visualizer output will only be correct if the same
lidar_mode parameter is used for both recording and replay.
.. _rosbag play: https://wiki.ros.org/rosbag/Commandline#rosbag_play
Visualizing Data in Rviz
To display sensor output using built-in ROS tools (rviz), follow the instructions above for running
the example ROS code with a sensor or recorded data. Then, run::
rviz -d ouster_example/ouster_ros/viz.rviz
in another terminal with the ROS environment set up. To view lidar intensity, near-IR, and range
images, add image:=true to the roslaunch command above.
Additional Information
- Sample sensor output usable with the provided ROS code
is available here <https://ouster.com/resources/lidar-sample-data>_. - For network configuration, refer to "Connecting to the Sensor" in the
Software User Manual_.