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Above: Meka bimanual robot using Meka A2 compliant arm and H2 compliant hand

Meka builds a wide-range of robot hardware targeted at mobile manipulation research in human environments. Meka's work was previously featured in the post on the mobile manipulator Cody from Georgia Tech, which uses Meka arms and torso.

Meka was started by Aaron Edsinger and Jeff Weber to capitalize on their experience building robots like Domo, which featured force-controlled arms, hands, and neck built out of series-elastic actuators. Meka's expertise with series-elastic actuators allows them to target their hardware at human-centered applications, where compact, lightweight, compliant, force-controlled hardware is desired. Georgia Tech's HRI robot Simon, which uses Meka torso, head, arms, and hands, has proportions similar to a 5'7" female.

Meka initially built robot hands and arms, but is now transitioning into building all the components you need for a mobile manipulation platform. As Meka began to make this transition, they also started to transition to ROS. As a small startup company, they didn't have the resources to design and build the software drivers and libraries for a more complete mobile manipulation platform. They were also transitioning from a single real-time computer to using multiple computers, and they needed a middleware platform that would help them utilize this increased power.

One of Meka's new hardware products is the B1 Omni Base, which is getting close to completion. The B1 is based on the Nomadic XR4000 design and uses Holomni's powered casters. It is also integrated with the M3 realtime system and will have velocity, pose, and operational-space control available. The base houses a RTAI Ubuntu computer and can have up to two additional computers.

Meka is also designing two sensor heads that will be 100% integrated with ROS. The more fully-featured of the two will have five cameras, including Videre stereo, as well as a laser range finder, microphone array, and IMU. The tilting action of the head will enable to robot to use the laser rangefinder as a 3D sensor, in addition to the stereo.

The Meka software system consists of the Meka M3 control system coupled with ROS and other open-source libraries like Orocos' KDL. M3 is used to manage the realtime system and provide low-level GUI tools. ROS is used to provide visualizations and higher-level APIs to the hardware, such as motion planners that incorporate obstacle avoidance. ROS is also being used to integrate the two sensor heads that Meka has in development, as well as provide a larger set of hardware drivers so that customers can more easily integrate new hardware.

ROS is fully available with Meka's robots starting with last month's M3 v1.1 release. For lots of photos and video of Meka's hardware in action, see this Hizook post.

Skybotix is offering their CoaX helicopter complete with basic ROS setup so customers can use ROS right out of the box.

The CoaX helicopter is a micro UAV targeted at the research and educational markets. The small 320g helicopter includes an IMU, a downward-looking and three optional sideward-looking sonars, pressure sensor, color camera, and Bluetooth, XBee, or WiFi communication. In addition to two DSPs (dsPIC33), the CoaX has an optional Gumstix Overo computer that can run ROS. You can see more of the specs on their hardware wiki page.

Skybotix fully supports open source with the CoaX. The CoaX API, including low-level firmware and controller, is available open source under a GNU LGPL license. Their Gumstix Overo setup comes with a basic ROS installation. They include a ROS publisher for the CoaX state, a demo application for transmitting video data, and a GUI for visualizing both. Although the CoaX comes with minimal additional ROS libraries, there is a growing community of micro-UAV developers using ROS, including the micro-UAV-focused ccny-ros-pkg repository.

The CoaX was developed in collaboration with ETH Zurich. The Skybotix Youtube channel has videos of ETH Zurich student projects. Skybotix released recently a speed module for CoaX based on optical sensor, which enables indoor speed control as well as indoor hovering (video).

DARPA is having a contest to name their new robot for the ARM program. "The ARM Robot" has two Barrett WAM arms, BarrettHands, 6-axis force torque sensors at the wrist, and pan-tilt head. For sensors, it has a color camera, SwissRanger depth camera, stereo camera, and microphone.

The final software architecture and APIs have not been released yet, but the FAQ notes:

The software architecture is TBD, but is leaning toward a nodal software architecture using a tool such as Robotic Operating System (ROS).

The software track for the ARM program currently includes Carnegie Mellon University, HRL Laboratories, iRobot, NASA-Jet Propulsion Laboratory, SRI International and University of Southern California. It would certainly be a great boost for the ROS community to have more common platforms to develop and share the latest perception and manipulation techniques.

Below is a video from Dr. Motilal Agrawal of SRI (via Hizook) showing it in action. Dr. Agrawal and SRI are looking for Ph.D/Masters students with experience in robotics, ROS, and OpenCV. Want a job?

The CityFlyer project at the CCNY Robotics and Intelligent Systems Lab is using Ascending Technologies Pelican and Hummingbird Quadrotor helicopters to do research in 3D mapping and navigation. The Ascending Technologies platform provides a 1.6Ghz Intel Atom processor, 500 gram payload, GPS, and barometric altimeter. The CityFlyer add several sensors, including a Hokuyo URG-04LX and IMU. The Hokuyo URG has been modified to double as a laser height estimator. The CityFlyer project is able to combine data from these sensors to do indoor SLAM using GMapping.

The CityFlyer project has also created an RGB-D sensor by combining data from a SwissRanger 4000 and Logitech Webcam. They use this to build 3D maps for indoor environments using a 3D Multi-Volume Occupancy Grid (MVOG). Their MVOG technique is described in their RGB-D 2010 paper and more videos are here and here. Although the full sensor package exceeds the payload of the quadrotor, they anticipate that advances in RGB-D will make these techniques feasible for micro UAVs.

CCNY has released a variety of drivers, libraries and tools to support the ROS community. These include drivers and tools for the AscTec platform, libraries for dealing with aerially mounted laser rangefinders, a New College Dataset parser, and libraries for using AR tags with ROS.

CCNY has also developed a "Ground Station" application that acts as a virtual cockpit for visualizing telemetry data from an AscTec quadrotor. It is also able to overlay GPS data on an outdoor map to visualize the UAV's tracks. I Heart Robotics has a great writeup on Ground Station, and you can also checkout the documentation on ROS.org.

The ccny-ros-pkg is an excellent resource for the ROS community with complete documentation on a variety of packages, including videos that demonstrate these packages in use.

Bag files for the video above can be downloaded here (elevator_2010-08*).

Qbo is a personal, open-source robot being developed by Thecorpora. Francisco Paz started the Qbo project five years ago to address the need for a low cost, open-source robot to enable the ordinary consumer to enter the robotics and the artificial intelligence world.

A couple months ago, Thecorpora decided to switch their software development to ROS and have now acheived "99.9%" integration. You can watch the video below of Qbo's head servos being controlled by the ROS Wiimote drivers, as well as this video of the Wiimote controlling Qbo's wheels. Their use of the ROS joystick drivers means that any of the supported joysticks can be used with Qbo, including the PS3 joystick and generic Linux joysticks.

Qbo's many other sensors are also integrated with ROS, which means that they can be used with higher-level ROS libraries. This includes the four ultrasonic sensors as well as Qbo's stereo webcams. They have already integrated the stereo and odometry data with OpenCV in order to provide SLAM capabilities (described below).

It's really exciting to see an open-source robot building and extending upon ROS. From their latest status update, it sounds like things are getting close to done, including a nice GUI that lets even novice users interact with the robot.

Qbo SLAM algorithm:

The algorithm can be divided into three different parts:

The first task is to calculate the movement of the robot. To do that we use the driver for our robot that sends an Odometry message.

The second task is to detect natural features in the images and estimate their positions in a three dimensional space. The algorithm used to detect the features is the GoodFeaturesToTrackDetector function from OpenCV. Then we extract SURF descriptors of those features and match them with the BruteForceMatcher algorithm, also from OpenCV.

We also track the points matched with the sparse iterative version of the Lucas-Kanade optical flow in pyramids and avoid looking for new features in places where we are already tracking another feature.

We take the images to this node from image messages synchronized and send a PointCloud message with the position of the features, their covariance in the three coordinates, and the SURF descriptor of the features.

The third task is to implement an Extended Kalman Filter and a data association algorithm based in the mahalanobis distance from the CloudPoint seen from the robot and the CloudPoint of the map. To do that we read the Odometry and PointCloud messages and we send also an Odometry message and a PointCloud message with the position of the robot and the features included in the map as an output.

Lego Mindstorms NXT is a low-cost programmable robotics kit that is used in education and by hobbyits throughout the world. One of the most visible NXT events is First Lego League. The developers of foote-ros-pkg have developed a bridge that connects NXT with ROS, allowing NXT users to leverage all the ROS tools and capabilities.

The NXT-ROS software stack provides many useful tools to interface NXT robots with ROS. Currently NXT users can take robot models created with Lego Digital Designer, and automatically convert them into robot models compatible with ROS. The converted robot model can be visualized in rviz, and in the future we hope to add simulation capabilities in Gazebo, our 3D simulator. The bridge between NXT and ROS creates a ROS topic for each motor and sensor of the NXT robot.

Once a robot is connected to ROS, you can start running applications such as the base controller, wheel odometry, keyboard/joystick teleoperation, and even assisted teleoperation using the ROS navigation stack. The NXT-ROS software stack includes a number of example robot models for users to play with and to get a feel for using NXT with ROS.

This new NXT-ROS software stack provides NXT users access to the open-source ROS community. NXT users now have access to state of the art open source robotics libraries available on ros.org.

Please see the nxt page on the ROS wiki for documentation, demos, and more. The developers would like to thank the nxt-python project for support and development.

The folks at the ModLab/GRASP Lab at Penn recently got their PR2 and used the occassion to test out "Mini-PR2". They used $5000 worth of CKBot modules to replicate the degrees of freedom of the real PR2 -- all except the torso. They used 18 modules (14 U-Bar, 4 L7, 4 motor) to create Mini-PR2, and they also added a counter-balance on the shoulder to help balance the arm.

The CKBot modules, which have previously been featured here, enable their lab to try out new ideas quickly and cheaply. In this case, they can use the PR2 simulator to drive their real robot, and they've used an actual PR2 to puppet Mini-PR2 (see 0:49 in video). They are now working on using the Mini-PR2 to puppet the actual PR2.

The CKBot modules don't have the computation power to run ROS on their own, but they can communicate with another computer that translates between the two systems. Their current system listens to the joint_states topic on the PR2 and translates those messages into CKBot joint angles.

You can now use Shadow Robot hardware with ROS! Engineers at Shadow Robot have been busy building a ROS stack and have now reached their first release. This initial release includes an interface to both simulated and real hardware, which means that, whether or not you have a Shadow Dextrous Hand of your own, you can use your ROS software to see the Shadow hand move inside of ROS tools like rviz.

To get started, you should check the Shadow Robot ROS FAQ or checkout the Launchpad site.

Robotino is a commercially available mobile robot from Festo Didactic. It's used for both education and research, including competitions like RoboCup. It features an omnidirectional base, bumps sensors, infrared distance sensors, and a color VGA camera. The design of Robotino is modular, and it can easily be equipped with a variety of accessories, inluding sensors like laser scanners, gyroscopes, and the Northstar indoor positioning system.

REC has been supportive of the Openrobotino community, which provides open-source software for use with the Robotino, and now, they are providing official ROS drivers in the robotino_drivers stack. Their current ROS integration already supports the ROS navigation stack, and you can watch the video below that shows the Robotino being controlled inside of rviz.

We're very excited to see commercially available robot hardware platforms being support with official ROS drivers. There are over a thousand Robotino systems around the world and we hope that these drivers will help connect the Robotino and ROS communities.

ROS has taken to the air! In a video that's quickly making the rounds on the Internet, you can see quadrotors from Penn's GRASP Lab performing all sorts of "aggressive" acrobatic stunts, from flying through narrow windows to landing on vertical perches. The entire system uses a mix of high-level ROS software for modularization and communication, as well as low-level microcontroller code.

The goal of this project was to fly a quadrotor precisely along aggressive trajectories. The basic components of the system are the quadrotor, a control laptop, and the Vicon motion capture system. The onboard microcontroller runs an attitude control loop at 1 kHz. The control laptop runs the higher-level position control loop. The control computer communicates with the quadrotor via an XBee link.

Communication between different programs on the control computer is done through ROS. A motion-capture node sends pose messages to a central controller, which in turn outputs control messages to code that sends the commands to the quadrotor. Experimentation was performed in a 3D simulator using a quadrotor model that contains a very accurate description of the dynamics of the actual quadrotor. The simulator communicates through ROS in a similar way as the hardware does, allowing for minimal overhead to switch between experimentation in simulation and on the actual quadrotor. ROS made it easy to modularize the code and write programs for each aspect of the entire problem independently.

Daniel Mellinger's Quadrotor Page
GRASP Lab

Thanks to Daniel Mellinger of Penn for helping to put together this post.

The Media and Machines Lab at Washington University in St. Louis has integrated several of their robots with ROS, including an iRobot B21r and several Videre ERRATICs. They are also maintaining wu-ros-pkg, which is a repository of research projects, drivers, and utilities related to these robots.

Wash U.'s B21r, known as Lewis, is best known for being a mobile robot photographer. Lewis is currently being used for HRI research, and they are also reimplementing the photographer functionality in ROS. Lewis is fully integrated with ROS, including sensor data from 48 sonar sensors, 56 bump sensors, 2 webcams, and a Hokuyo laser rangerfinder. There is also Directed Perception PTU-46 pan-tilt unit that they have mounted the webcams on (driver).

The B21r community will be happy to know that Wash U. has deeply integrated this platform with ROS. They have created an urdf model, complete with meshes for visualizing in rviz, and they have also integrated the B21r with the ROS navigation stack. They are also providing an rwi stack, which includes their rflex driver. The rflex driver is capable of driving other iRobot/RWI robot platforms, including the B18, ATRV, and Magellan Pro.

Wash U. has also integrated their four Videre ERRATICs with ROS. They've named these robots Blood, Sweat, Toil, and Tears, and have equipped them with Hokuyo laser rangerfinders and webcams. The ERRATICs enable them to explore research in multi-robot coordination and control. They're also developing on iRobot Creates using drivers from brown-ros-pkg.

The research at the Media and Machines Lab has led to several interfaces and visualizations for using robots. This includes RIDE (Robot Interactive Display Environment), which takes cues from Real Time Strategy (RTS) video games to provide an interface for easily controlling multiple robots simultaneously. They have also developed a visualization for mapping sensor data over time for search tasks and a 3D interface for binocular robots. RIDE is available in the ride stack, and much of their other research will soon be released in wu-ros-pkg.

HERB (Home Exploring Robotic Butler) is a mobile manipulation platform built by Intel Research Pittsburgh, in collaboration with the Robotics Institute at Carnegie Mellon University. HERB is designed to be a "robotic butler" and has been demonstrated in a variety of real-world kitchen tasks, such as opening refrigerator and cabinet doors, finding and collecting coffee mugs, and throwing away trash. HERB is powered by a variety of open-source libraries, including several developed by CMU researchers, like OpenRAVE and GATMO.

OpenRAVE is a software platform for robotics that was designed specifically for the challenges related to motion planning. It was created in 2006 by Rosen Diankov, and in late 2008 he integrated it with ROS. The benefits of this integration can be seen on HERB.

HERB has a Barrett WAM arm, a pair of low-power onboard computers, Pointgrey Flea and Dragonfly cameras, a SICK LMS lidar, a rotating Hokuyo lidar, and a Logitech 9000 webcam, all of which sit on a Segway RMP200 base. HERB communicates with off-board PCs over a wireless network.

ROS is glue for this setup: ROS is used for the hardware drivers, process management, and communication on HERB. ROS' ability to distribute processes across computers is used to help perform computation off the robot.

OpenRAVE provides an environment on top of this that unifies the controls and sensors for doing motion-planning algorithms, including sending trajectories to the arm and hand. OpenRAVE implements Diankov et. al's work on caging grasps, which enables HERB to perform tasks like opening and closing doors, drawers, cabinets, and turning handles.

In addition to manipulating objects, HERB has to be able to keep track of people and other movable objects that exist in real-world environments. HERB uses the GATMO (Generalized Approach to Tracking Movable Objects) library to track these movable objects. GATMO was developed by Garratt Gallagher and is available from gatmo.org. The GATMO library includes packaging and installation instructions for ROS.

The collaboration between CMU and Intel Labs Pittsburgh has produced numerous other libraries that have found their way into ROS. Rosen Diankov started the cmu-ros-pkg repository, which houses many of these libraries, and he also wrote rosoct, an Octave client library for ROS. Another library of note is the chomp_motion_planner package, which was implemented by Mrinal Kalakrishnan based on the work of Ratliff et. al.

You can find more videos of HERB in action at the Personal Robotics Intel site. For more on how HERB uses ROS, OpenRAVE, and GATMO, you can read "HERB: a home exploring robot butler".

The Intelligent Autonomous Systems Group at TU München (TUM) built TUM-Rosie with the goal of developing a robotics system with a high-degree of cognition. This goal is driving research in 3D perception, cognitive control, knowledge processing, and highlevel planning. TUM is building their research on TUM-Rosie using ROS and has setup the open-source tum-ros-pkg repository to share their research, libraries, and hardware drivers. TUM has already released a variety of ROS packages and is in the process of releasing more.

TUM-Rosie is a mobile manipulator built on a Kuka mecanum-wheeled omnidrive base, with two Kuka LWR-4 arms and DLR-HIT hands. It has a variety of sensors for accomplishing perception tasks, including a SwissRanger 4000, FLIR thermal camera, Videre stereo camera, SVS-VISTEK eco274 RGB cameras, a tilting "2.5D" Hokuyo UTM-30LX lidar, and both front and rear Hokuyo URG-04LX lidars.

One of the new libraries that TUM is developing is the cloud_algos package for 3D perception of point cloud data. cloud_algos is being designed as an extension of the pcl (Point Cloud Library) package. The cloud_algos package consists of a set of point-cloud-processing algorithms, such as a rotational object estimator. The rotational object estimator enables a robot to create models for objects like pitchers and boxes from incomplete point cloud data. TUM has already released several packages for semantic mapping and cognitive perception.

TUM is also working on systems that combine knowledge reasoning with perception. The K-COPMAN (Knowledge-enabled Cognitive Perception for Manipulation) system in the knowledge stack generates symbolic representations of perceived objects. This symbolic representation allows a robot to make inferences about what is seen, like what items are missing from a breakfast table.

In the field of knowledge processing and reasoning for personal robots, TUM developed the KnowRob system that can provide:

• spatial knowledge about the world, e.g. the positions of obstacles
• ontological knowledge about objects, their types, relations, and properties
• common-sense knowledge, for instance, that objects inside a cupboard are not visible from outside unless the door is open
• knowledge about the functions of objects like the main task a tool serves for or the sequence of actions required to operate a dishwasher

KnowRob is part of the tum-ros-pkg repository, and there is a wiki with documentation and tutorials.

At the high level, TUM is working on CRAM (Cognitive Robot Abstraction Machine), which provides a language for programming cognitive control systems. The goal of CRAM is to allow autonomous robots to infer decisions, rather than just having pre-programmed decisions. Practically, the approach will enable tackling of the complete pick-and-place housework cycle, which includes setting the table, cleaning the table as well as loading the dishwasher, unloading it and returning the items to their storage locations. CRAM features showcased in this scenario include the probabilistic inference of what items should be placed where on the table, what items are missing, where items can be found, which items can and need to be cleaned in the dishwasher, etc. As robots become more capable, it will be much more difficult to explicitly program all of their decisions in advance, and the TUM researchers hope that CRAM will help drive AI-based robotics.

Researchers at TUM have also made a variety of contributions to the core ROS system, including many features for the roslisp client library. They are also maintaining research datasets for the community, including a kitchen dataset and a semantic database of 3d objects, and they have contributed to a variety of other open-source robotics systems, like YARP and Player/Stage.

Research on the TUM-Rosie robot has been enabled by the Cluster of Excellence CoTeSys (Cognition for Technical Systems). For more information:

• TUM-Rosie hardware and software description
• IAS Video Channel
• tum-ros-pkg on ROS.org
• Datasets
• Overview Article: Towards Performing Everyday Manipulation Activities
• Overview Article: Towards Automated Models of Activities of Daily Life
• Overview Article: Generality and Legibility in Mobile Manipulation

The Modlab at Penn designed the CKBot (Connector Kinetic roBot) module to be fast, small, and inexpensive. These qualities enable it to be used to explore the promise of modular robotics systems, including adaptability, reconfigurability, and fault tolerance. They've researched dynamic rolling gaits, which use a loop configuration to achieve speeds of up to 1.6/ms, as well as bouncing gaits by attaching passive legs. They are also using the CKBots to research the difficult problem of configuration recognition, and, for the Terminator 2 fans, they have even demonstrated "Self re-Assembly after Explosion" (SAE).

More recently, Modlab has developed ROS packages that can be used when the CKBots are connected to a separate ROS system. They have also created an open source repository, modlab-ros-pkg, for CKBot ROS users. The CKBot modules only have a few PIC processors -- not enough to run ROS -- so an off-board system enables them to use algorithms that require more processing power. In one experiment, they used a camera to locate AR tags on the CKBot modules. The locations were stored in tf, which was used to calculate coordinate transforms between modules. They have also used rviz to display the estimated position of modules during SAE when AR tags were not in use.

One of the projects Modlab is currently working on is a "mini-PR2" made out of CKBot modules. The mini-PR2 will be kinematically similar to the Willow Garage PR2 and is powered by a separate laptop. You can see an early prototype of mini-PR2 opening an Odwalla fridge:

CKbots trace their ancestry back to Professor Mark Yim's work on the PolyBot system at PARC. The PolyBot system had an impressive range of demonstrations, including fence and stair climbing, tricycle riding, and even transforming from a loop, to a snake, to a spider.

Modlab does a variety of other modular robotics research, and has even demonstrated a quick-change end effector for the PR2.

I Heart Robotics has released a rovio stack for ROS, which contains a controller, a joystick teleop node, and associated launch files for the WowWee Rovio. There are also instructions and configuration for using the probe package from brown-ros-pkg to connect to Rovio's camera.

You can download the rovio stack from iheart-ros-pkg:

http://github.com/IHeartRobotics/iheart-ros-pkg

As the announcement notes, this is still a work in progress, but this release should help other Rovio hackers participate in adding new capabilities.

Marvin is an autonomous car from Austin Robot Technology and the Department of Computer Science at The University of Texas at Austin. The modified 1999 Isuzu VehiCross competed in the 2007 DARPA Urban Challenge and was able to complete many of the difficult tasks presented to the vehicles, including merging, U-turns, intersections, and parking.

The team members for Marvin have a long history of contributing to open-source robotics software, including the Player project. Recently, Marvin team members have been porting their software to ROS. As part of this effort, they have setup the utexas-art-ros-pkg open-source code repository, which provides drivers and higher-level libraries for autonomous vehicles.

Like many Urban Challenge vehicles, Marvin has a Velodyne HDL lidar and Applanix Position and Orientation System for Land Vehicles (POS-LV). Drivers for both of these are available in the utexas-art-ros-pkg applanix package and velodyne stack, respectively. The velodyne stack also includes libraries for detecting obstacles and drive-able terrain, as well as tools for visualizing in rviz.

The Marvin team has also released an art_vehicle stack that provides the libraries that make Marvin go, including their navigation system. You can try it out with their simulator built on Stage.

Professor Peter Stone's group in the Department of Computer Science has been using Marvin to do multiagent research. You can learn about the algorithms used in the Urban Challenge in their paper, "Multiagent Interactions in Urban Driving". More recently, they have been doing research in "autonomous intersection management". This research is investigating a multiagent framework that can handle intersections for autonomous vehicles safely and efficiently. As you can see in the video above, these intersections for autonomous vehicles can handle far more vehicles than intersections designed for human-driven vehicles. For more information, you can watch a longer clip and read Kurt Dresner and Peter Stone's paper, "A Multiagent Approach to Autonomous Intersection Management"

Many people have contributed to the development of Marvin in the past. Current software development, including porting to ROS, is being led by Jack O'Quin and Dr. Michael Quinlan under the supervision of Professor Peter Stone.

Bosch's Research and Technology Center (RTC) has a Segway-RMP based robot that they have been using with ROS for the past year to do exploration, 3D mapping, and telepresence research. They recently released version 0.1 of their exploration stack in the bosch-ros-pkg repository, which integrates with the ROS navigation stack to provide 2D-exploration capabilities. You can use the bosch_demos stack to try this capability in simulation.

The RTC robot uses:

• 1 Mac Mini
• 2 SICK scanners
• 1 Nikon D90
• 1 SCHUNK/Amtec Powercube pan-tilt unit
• 1 touch screen monitor
• 1 Logitech webcam
• 1 Bosch gyro
• 1 Bosch 3-axis acceleromoter

Like most research robots, it's frequently reconfigured: they added an additional Mac mini, Flea camera, and Videre stereo camera for some recent work with visual localization.

Bosch RTC has been releasing drivers and libraries in the bosch-ros-pkg repository. They will be presenting their approach for mapping and texture reconstruction at ICRA 2010 and hope to release the code for that as well. This approach constructs a 3D environment using the laser data, fits a surface to the resulting model, and then maps camera data onto the surfaces.

Researchers at Bosch RTC were early contributors to ROS, which is remarkable as bosch-ros-pkg is the first time Bosch has ever contributed to an open source project. They have also been involved with the ros-pkg repository to improve the SLAM capabilities that are included with ROS Box Turtle, and they have been providing improvements to a visual odometry library that is currently in the works.

The Healthcare Robotics Lab focuses on robotic manipulation and human-robot interaction to research improvements in healthcare. Researchers at HRL have been using ROS on EL-E and Cody, two of their assistive robots. They have also been publishing their source code at gt-ros-pkg.

HRL first started using ROS on EL-E for their work on Physical, Perceptual, and Sematic (PPS) tags (paper). EL-E has a variety of sensors and Katana arm mounted on a Videre ERRATIC mobile robot base. The video below shows off many of EL-E's capabilities, including a laser pointer interface -- people select objects in the real-world for the robot to interact with using a laser pointer.

HRL does much of their research work in Python, so you will find Python-friendly wrappers for much of EL-E's hardware, including the Hokuyo UTM laser rangefinder, Thing Magic M5e RFID antenna, and Zenither linear actuator. You can also get CAD diagrams and source code for building your own tilting Hokuyo 3D scanner.

HRL also has a new robot, Cody, which you can see in the video below:

Update: you can read more on Cody at Hizook.

The end effector and controller are described in the paper, "Pulling Open Novel Doors and Drawers with Equilibrium Point Control" (Humanoids 2009). They've also published the CAD models of the end effector and the source code can be found in the 2009_humanoids_epc_pull ROS package.

Whether it's providing open source drivers for commonly used hardware, CAD models of their experimental hardware, or source code to accompany their papers, HRL has embraced openness with their research. For more information:

• Healthcare Robotics Lab homepage
• gt-ros-pkg documentation ROS.org
• gt-ros-pkg source code on Google Code

The Kawada HRP-2V is a variant of the HRP-2 "Promet" robot. It uses the torso, arms, and sensor head of the HRP-2, but it is mounted to an omni-directional mobile base instead of the usual humanoid legs. The JSK Lab at Tokyo University uses this platform for hardware and software research.

In May of 2009 at the ICRA conference, the HRP-2V was quickly integrated with the ROS navigation stack as a collaboration between JSK and Willow Garage. Previously, JSK had spent two weeks at Willow Garage integrating their software with ROS and the PR2. ICRA 2009 was held in Kobe, Japan, and Willow Garage had a booth. With laptops and the HRP-2V setup next to the booth, JSK and Willow Garage went to work getting the navigation stack on the HRP-2V. By the end of the conference, the HRP-2V was building maps and navigating the exhibition hall.

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 SCHUNK 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 cob_driver stack provides ROS software integration for these sensors.

The Care-O-bot runs on a CAN interface with a SCHUNK LWA3 arm, SDH gripper, and a tray mounted on a PRL 100 for interacting with its environment. It also has a SCHUNK 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 cob_generic_can and cob_canopen_motor, as well as wrappers for libntcan and libpcan. The SCHUNK components are also supported by various packages in the cob_driver stack.

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.

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.

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.

With so many open-source repositories offering ROS libraries, we'd like to highlight the many different robots that ROS is being used on. It's only fitting that we start where ROS started with STAIR 1: STanford Artificial Intelligence Robot 1. Morgan Quigley created the Switchyard framework to provide a robot framework for their mobile manipulation platform, and it was the lessons learned from building software to address the challenges of mobile manipulation robots that gave birth to ROS.

Solving problems in the mobile manipulation space is too large for any one group. It requires multiple teams tackling separate challenges, like perception, navigation, vision, and grasping. STAIR 1 is research robot built to address these challenges: a Neuronics Katana Arm, a Segway base, and an ever-changing array of sensors, including a custom laser-line scanner, Hokuyo laser range finder, Axis PTZ, and more. The experience developing for this platform in a research environment provided many lessons for ROS: small components, simple reconfiguration, lightweight coupling, easy debugging, and scalable.

STAIR 1 has tackled a variety of research challenges, from accepting verbal commands to locate staplers, to opening doors, to operating elevators. You can watch the video of STAIR 1 operating an elevator below, and you can watch more videos and learn more about the STAIR program at stair.stanford.edu. You can also read Morgan's slides on ROS and STAIR from an IROS 2009 workshop.

In addition to the many contribution made to the core, open-source ROS system, you can also find STAIR-specific libraries at sail-ros-pkg.sourceforge.net/, including the code used for elevator operation.

The science of robotics has suffered from the inability of researchers to replicate each other's results. Replicating results begins by being able to run demonstrations in different laboratories, often on different hardware. The JSK lab at the University of Tokyo and Willow Garage have recent had some success in this area.

In March, Professors Inaba, Okada and four students visited Willow Garage to create demos on PR2 robots combining their infrastructure with ROS. At ICRA in May, Ken Conley from Willow Garage worked with the JSK team to bring ROS and those same demonstrations up on an HRP-2V robot from Kawada industries. The HRP-2V combines the torso of an HRP-2 walking humanoid with an omni-directional wheeled base, producing a platform that is similar in structure to the PR2, but with different sensor configuration, different kinematics, etc...

On both occasions, the combined team was able to complete their work in under a week, demonstrating that replicating results in robotics is possible at a relatively low cost.