Logging and playback is one of the most critical features when developing software for robotics. Whether you're a hardware engineer recording diagnostic data, a researcher collecting data sets, or a developer testing algorithms, the ability to record data from a robot and play it back is crucial. ROS supports these needs with "Bag files" and tools like rosbag and rxbag.

rosbag can record data from any ROS data source into a bag file, whether it be simple text data or large sensor data, like images. The tool can also record data from programs running on multiple computers. rosbag can play back this data just as it was recorded -- it looks identical. This means that data can be recorded from a physical robot and used to create virtual robots to test software. With the appropriate bag file, you don't even need to own a physical robot.

There are a variety of tools to help you manage your stored data, such as tools for filtering data and updating data formats. There are also tools to manage research workflows for sending bag files to Amazon's Mechanical Turk for dataset labeling. For data visualization, there is the versatile rxbag tool. rxbag can scan through camera data like a movie editor, plot numerical data, and view the raw message data. You can also write plugins to define viewers for your own data types.

You can watch the video to see rosbag and rxbag in action. Both of these tools are part of the ROS Box Turtle release, which you can download from ROS.org.

Several stacks have transitioned to 1.1 unstable development branches: commonmsgs 1.1.1, imagepipeline 1.1.0, and vision_opencv 1.1.0. These are unstable development releases: it is recommended for users to keep using the 1.0 branch in Box Turtle. Our stack version policy describes our general development model for stable and unstable releases.

common 1.1

The primary part of this release is the addition of the nodelet package. There was discussion on the ros-users mailing list earlier about how this can be used as an optimization. If you are interested please take a look at the documentation or code. Feedback is always appreciated.

image_pipeline 1.1

The major new features are in stereo_image_proc. It takes advantage of improvements to the OpenCV stereo block matcher, particularly to reduce fringe artifacts at edges. For comparison, the reference implementation of stereo block matching (on which OpenCV's was based) can be used instead, but they should now give roughly the same results. stereo_image_proc now advertises a separate point cloud topic using the new and improved PointCloud2 message type.

Change lists

• common_msgs
• image_pipeline
• vision_opencv

Several stacks have been updated with patches for Box Turtle.

• camera_drivers 0.9.2
• geometry 1.0.2
• laser_drivers 1.0.4
• vision_opencv 1.0.1
• web_interface 0.3.11

pr2_calibration, which is still in unstable development, was also updated to 0.3.0.

Change lists

• camera_drivers
• geometry
• laser_drivers
• pr2_calibration
• vision_opencv
• web_interface

Like the Aldebaran Nao, the "Prairie Dog" platform from the Correll Lab at Colorado University is an example of the ROS community building on each others' results, and the best part is that you can build your own.

Prairie Dog is an integrated teaching and research platform built on top of an iRobot Create. It's used in the Multi-Robot Systems course at Colorado University, which teaches core topics like locomotion, kinematics, sensing, and localization, as well as multi-robot issues like coordination. The source code for Prairie Dog, including mapping and localization libraries, is available as part of the prairiedog-ros-pkg ROS repository.

Prairie Dog uses a variety of off-the-shelf robot hardware components: an iRobot Create base, a 4-DOF CrustCrawler AX-12 arm, a Hokuyo URG-04LX laser rangefinder, a Hagisonic Stargazer indoor positioning system, and a Logitech QuickCam 3000. The Correll Lab was able to build on top of existing ROS software packages, such as brown-ros-pkg's irobot_create and robotis packages, plus contribute their own in prairiedog-ros-pkg. Prairie Dog is also integrated with the OpenRAVE motion planning environment.

Starting in the Fall of 2010, RoadNarrows Robotics will be offering a Prairie Dog kit, which will give you all the off-the-shelf components, plus the extra nuts and bolts. Pricing hasn't been announced yet, but the basic parts, including a netbook, will probably run about $3500.

For more information, please see:

• Prairie Dog homepage
• prairiedog-ros-pkg documentation on ROS.org

Photo: Prairie Dogs busy creating maps for kids and parents

The Care-O-bot 3 is a mobile manipulation robot designed by Fraunhofer IPA that is available both as a commercial robotic butler, as well as a platform for research. The Care-O-bot software has recently been integrated with ROS, and, in just short period of time, already supports everything from low-level device drivers to simulation inside of Gazebo.

The robot has two sides: a manipulation side and an interaction side. The manipulation side has a SHUNK Lightweight Arm 3 with SDH gripper for grasping objects in the environment. The interaction side has a touchscreen tray that serves as both input and "output". People can use the touchscreen to select tasks, such as placing drink orders, and the tray can deliver objects to people, like their selected beverage.

The goals of the Care-O-bot research program are to:

• provide a common open source repository for the hardware platform
• provide simulation models of hardware components
• provide remote access to the Care-O-bot 3 hardware platform

Those first two goals are supported by the care-o-bot open source repository for ROS, which features libraries for drivers, simulation, and basic applications. You can easily download the source code and perform a variety of tasks in simulation, such as driving the base and moving the arm. These support the third goal of providing remote access to physical Care-O-Bot hardware via their webportal.

For sensing, the Care-O-bot uses two SICK S300 laser scanners, a Hokuyu URG-04LX laser scanner, two Pike F-145 firewire cameras for stereo, and Swissranger SR3000/SR4000s. The cob3_driver stack provides ROS software integration for these sensors in the sick_s300, cob3_camera_sensors, and cob3_hokuyo packages.

The Care-O-bot runs on a CAN interface with a SHUNK LWA3 arm, SDH gripper, and a tray mounted on a PRL 100 for interacting with its environment. It also has a SHUNK PW 90 and PW 70 pan/tilt units, which give it the ability to bow through its foam outer shell. The CAN interface is supported through several Care-O-bot ROS packages, including generic_can and canopen_motor, as well as wrappers for libntcan and libpcan. The SHUNK components are supported by the sdh, powercube_chain, libm5api packages.

The video below shows the Care-O-bot in action. NOTE: as the Care-O-bot source code is still being integrated with ROS, the capabilities you see in the video are not part of the ROS repository.

Junior is the Stanford Racing team's autonomous car that most famously finished in a close second at the DARPA Urban Challenge. It successfully navigated a difficult urban environment that required obeying traffic rules, parking, passing and many other challenges of real-world driving.

Those of you familiar with Junior are probably saying, "Junior doesn't use ROS! It uses IPC!"

That's mostly true, but researchers have recently started using ROS-based perception libraries in Junior's obstacle classification system.

From the very start, one of the goals of ROS was to keep libraries small and separable so that you could use as little, or as much, as you want. In the case of the tiny i-Sobot, a developer was able to just use ROS's PS3 joystick driver. When frameworks get too large, they becomes much more difficult to integrate with other systems.

In the case of Junior, Alex Teichman was able to bring his image descriptor library for ROS onto Junior. He has been using this library, along with ROS point cloud libraries, to develop Junior's obstacle classification system. Other developers on the team will also be allowed to choose ROS for their programs where appropriate.

You can find out more about Alex's image descriptor library at ros.org/wiki/descriptors_2d.

In addition to core robotics libraries, like navigation, the ROS Box Turtle release also comes with a variety of tools necessary for developing robotics algorithms and applications. One of the most commonly used tools is rviz, a 3-D visualization environment that is part of the ROS Visualization stack.

Whether it's 3D point clouds, camera data, maps, robot poses, or custom visualization markers, rviz can display customizable views of this information. rviz can show you the difference between the physical world and how the robot sees it, and it can also help you create displays that show users what the robot is planning to do.

You can watch the video above for more details about what the ROS rviz tool has to offer, and you can read documentation and download the source code at: ros.org/wiki/rviz.

The Aldebaran Nao is a commercially available, 60cm tall, humanoid robot targeted at research lab and classrooms. The Nao is small, but it packs a lot into its tiny frame: four microphones, two VGA cameras, touch sensors on the head, infrared sensors, and more. The use of Nao with ROS has demonstrated how quickly open-source code can enable a community to come together around a common hardware platform.

The first Nao driver for ROS was released by Brown University's RLAB in November of 2009. This initial release included head control, text-to-speech, basic navigation, and access to the forehead camera. Just a couple of days later, the University of Freiburg's Humanoid Robot Lab used Brown's Nao driver to develop new capabilities, including torso odometry and joystick-based tele-operation. Development didn't stop there: in December, the Humanoid Robot Lab put together a complete ROS stack for the Nao that added IMU state, a URDF robot model, visualization of the robot state in rviz, and more.

The Nao SDK already comes with built-in support for the open-source OpenCV library. It will be exciting to see what additional capabilities the Nao will gain now that it can be connected to the hundreds of different ROS packages that are freely available.

Brown is also using open source and ROS as part of their research process:

Publishing our ROS code as well as research papers is now an integral part of disseminating our work. ROS provides the best means forward for enabling robotics researchers to share their results and more rapidly advance the state-of-the-art.

-- Chad Jenkins, Professor, Brown University

The University of Freiburg's Nao stack is available on alufr-ros-pkg. Brown's Nao drivers are available on brown-ros-pkg, along with drivers for the iRobot Create and a Gstream-based webcam driver.

There have been several new releases containing patches, new features, and unstable updates.

Two of our ROS stacks have gone to their "unstable" release cycle: common_msgs and vision_opencv. We will be using this release cycle to develop new features for the next stable release.

For our patch releases, web_interface and and laser_drivers have both been updated with bug fixes.

pr2_calibration, which is an unstable library still under active development, has reached it's 0.3.0 release.

• camera_drivers 0.9.2
• common_msgs 1.1.1
• laser_drivers 1.0.4
• pr2_calibration 0.3.0
• vision_opencv 1.1.0
• web_interface 0.3.11

Change lists

• camera_drivers
• common_msgs
• laser_drivers
• pr2_calibration
• vision_opencv
• web_interface

ROS is starting to gain traction in Japan thanks to some dedicated early adopters and community-based translation efforts. Last year, the ROS Navigation stack was ported to Tokyo University's Kawada HRP2-V robot, and now it's finding use with hobby robots as well.

ROS libraries are designed to be small and easily broken apart. In this case, a small use of ROS has led to the claim of "smallest humanoid robot controlled by ROS." As the video explains, ROS isn't running on the robot. The i-Sobot is hooked up to an Arduino, which talks to a PC, which uses the ROS PS3 joystick driver. We're always thrilled to see code being reused, whether it's something as big as the ROS navigation stack, or something as small as a PS3 joystick driver.

The video and demo was put together by "Ogutti", who has been maintaining a Japanese blog on ROS at ros-robot.blogspot.com/. Most recently, he has been blogging about using the Care-O-bot 3 simulation libraries.

In addition to Ogutti's Japanese ROS blog, you can go to ros.org/wiki/ja to follow the progress of the Japanese translation efforts for the ROS documentation.