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Intel® RealSense™ is a platform for implementing gesture-based human-computer interaction techniques. It consists of series of consumer grade 3D cameras together with an easy to use machine perception library. The Intel® RealSense™ R200 camera is a USB 3.0 device that can provide color, depth, and infrared video streams. The TurtleBot3 Waffle model adopts Intel® RealSense™ R200 to enable 3D SLAM and navigation, and it is possible to apply various applications such as gesture recognition, object recognition and scene recognition based on 3D depth information obtained using RealSense™’s innovative Active Stereo Technology.


Technical Specifications

Items Specifications
RGB Video Resolution 1920 x 1280, 2M
IR Depth Resolution 640 x 480, VGA
Laser Projector Class 1 IR Laser Projector (IEC 60825-1:2007 Edition 2)
Frame Rate 30 fps (RGB), 60 fps (IR depth)
FOV (Field-of-View) 77° (RGB), 70° (IR depth), Diagonal Field of View
Range 0.3m ~ 4.0m
Operating Supply Voltage 5V (via USB port)
USB Port USB 3.0
Dimensions 101.56mm length x 9.55mm height x 3.8mm width
Mass Under 35g

Minimum System Requirements

Items Specifications
Processors 4th Generation and future Intel® Core™ processors
Disk Storage 1GB
Memory 2GB
Interface USB 3.0
  Ubuntu 14.04 and 16.04 LTS (GCC 4.9 toolchain)
Operating System Windows 8.1 and Windows 10 (Visual Studio 2015 Update 2)
for SDK Mac OS X 10.7+ (Clang toolchain)

Here is the detail specification document: Intel® RealSense™ Datasheet

Intel® RealSense™ R200 for TurtleBot3

The Intel® RealSense™ R200 is applied on TurtleBot3 Waffle.

Introduction Video

The TurtleBot3 Waffle uses Intel® RealSense™ Camera R200 as a default vision sensor. Check this video out that shows how Intel® RealSense™ Camera R200 can be used in TurtleBot3 Waffle.

User Guide

Intel® RealSense™ packages enable the use of Intel® RealSense™ R200, F200, SR300 and ZR300 cameras with ROS. Below table describes packages required to operate Intel® RealSense™. You will be guided to install these packaged in the next section.

Package Description
librealsense Underlying library driver for communicating with Intel® RealSense™ camera
realsense_camera ROS Intel® RealSense™ camera node for publishing camera


Warning! There are installation prerequisites for the Intel® RealSense™ package installation in http://wiki.ros.org/librealsense

[TurtleBot] The following commands will install relevant Intel® RealSense™ library.

$ sudo apt-get install linux-headers-generic
$ sudo apt-get install ros-kinetic-librealsense

[TurtleBot] To run the Intel® RealSense™ with ROS, the following package is needed. There are stable and unstable version packages. Choose one and install it.

$ cd catkin_ws/src
$ git clone https://github.com/intel-ros/realsense.git
$ cd realsense
$ git checkout 1.8.0
$ cd catkin_ws && catkin_make -j2
$ sudo apt-get install ros-kinetic-realsense-camera

Run realsense_camera Node

[TurtleBot] Run the following command

$ roslaunch realsense_camera r200_nodelet_default.launch

While the realsense_camera node is running, you can view various data from Intel® RealSense™ by launching rqt_image_view.

[Remote PC] Run the following command

$ rqt_image_view

Once the gui application is appeared on the screen, you can select data topic name related to Intel® RealSense™ from drop down menu at the top of the application.

(Optional) To Try as the Example Video Shows

[TurtleBot] Input ctrl + c to quit the previously run camera node, then run other realsense_camera node

$ roslaunch realsense_camera r200_nodelet_rgbd.launch

[TurtleBot] Run turtlebot3_bringup node to get datas for doing SLAM

$ roslaunch turtlebot3_bringup turtlebot3_robot.launch

[Remote PC] Run turtlebot3_slam node to do SLAM

$ roslaunch turtlebot3_slam turtlebot3_slam.launch

[Remote PC] Run RViz

$ rosrun rviz rviz -d `rospack find turtlebot3_slam`/rviz/turtlebot3_slam.rviz

[Remote PC] Click Panels - Views to open the view window

[Remote PC] Click TopDownOrtho (rviz) and change it into XYOrbit (rviz)

[Remote PC] Click add - By topic and find the PointCloud2 type /points topic in /camera/depth, then click it

[Remote PC] Click PointCloud2 type topic on the left window, then change Color Transformer from Intensity to AxisColor. This will show the depth of each points by color description.

[Remote PC] Click add - By topic and find the Image type /image_color topic in /camera/rgb, then click it. This will show the view of the rgb camera