In this article, we cover ROS installation of the Intel RealSense Camera on the NVIDIA Jetson TK1. Looky here:
Background
Note: This article is intended for intermediate to advanced users who are familiar with ROS.
One of the intended uses of Intel RealSense Cameras is robotics. The premiere operating system for robots is Robot Operating System (ROS). A great platform for running ROS and RealSense Cameras? Jetson TK1! Let’s get the shotgun out and have wedding!
Installation
In order to get started, there are three prerequisites required. First, librealsense needs to be installed on the Jetson TK1. Here is an article on how to do that, librealsense installation on Jetson TK1.
Second, we need to have ROS installed on the Jetson. If you do not already have ROS installed, here is a way excellent article on installing ROS on the Jetson TK1. In a nutshell:
To install ROS on the Jetson:
$ git clone https://github.com/jetsonhacks/installROS.git
$ cd installROS
$ ./installROS.h
$ cd ..
This will install ROS Indigo ros-base, rosdep, and rosinstall.
Next, we download the realsense_camera package installer:
$ git clone https://github.com/jetsonhacks/installRealSenseCameraROS.git
$ cd installRealSenseCameraROS
The third prerequisite we need is a Catkin Workspace for our base of operations. There is a convenience script to create a new Catkin Workspace.
$ ./setupCatkinWorkspace [workspace name]
In the video above, jetsonros is the workspace name. This script creates an initialized Catkin Workspace in the ~/ directory.
With the prerequisites installed, we’re ready to install the realsense_camera package:
$ ./installRealSense.sh [workspace name]
where [workspace name] is the name of the Catkin Workspace where you want the realsense_camera package installed. In the video, the workspace name used is jetsonros.
If you do not have a swap file enabled on your Jetson, there may be issues compiling the package because the TK1 does not have enough memory to compile this in one pass. The installation script has been changed since the video was filmed to compile using only one core to relieve memory pressure, i.e.
$ catkin_make -j1″
If this doesn’t fix the problem, refer to the video for a workaround.
Note: As of this writing, the ROS package in the debian repository cv_bridge is hard linked against an OpenCV package which is not installed on the Jetson (2.4.8). There are several ways to get around this, discussed on the ROS Answers forum. For this installation, installing cv_bridge from source is chosen.
At this point, you are ready to launch the node.
Launch RealSense Camera Node
There are several launch files included in the realsense_camera package. These are covered in the README.md file in real_sense camera directory. In order to launch the camera on the Jetson:
$ roslaunch realsense_camera realsense_r200_nodelet_standalone_preset.launch
Visualzation Workstation
On your visualization workstation, you can view the camera configuration:
$ rosrun rqt_reconfigure rqt_reconfigure
If you intend to view a point cloud, you must setup a frame of reference, i.e.
$ rosrun tf static_transform_publisher 0.0 0.0 0.0 0.0 0.0 0.0 map camera_depth_optical_frame 100
You can also open RVIZ and load the provided RVIZ configuration file: realsenseRvizConfiguration1.rviz.
$ roscd realsense_camera
$ rosrun rviz rviz -d rviz/realsenseRvizConfiguration1.rviz
Please read the README.md file for more information.
Conclusion
RealSense camera support under ROS is still relatively new. Some interesting features of the camera are not yet supported, such as hardware registration of the color and depth map in the package. However things are shaping up quite nicely for this new entry in the RGBD camera space.
The post RealSense Camera ROS Install on Jetson TK1 appeared first on JetsonHacks.