May 2015 Archives

Clearpath Robotics announced the newest member of its robot fleet: an omnidirectional development platform called Ridgeback. The mobile robot is designed to carry heavy payloads and easily integrate with a variety of manipulators and sensors. Ridgeback was unveiled as a mobile base for Rethink Robotics' Baxter research platform at ICRA 2015 in Seattle, Washington.

"Many of our customers have approached us looking for a way to use Baxter for mobile manipulation research - these customers inspired the concept of Ridgeback. The platform is designed so that Baxter can plug into Ridgeback and go," said Julian Ware, General Manager for Research Products at Clearpath Robotics. "Ridgeback includes all the ROS, visualization and simulation support needed to start doing interesting research right out of the box."

Ridgeback's rugged drivetrain and chassis is designed to move manipulators and other heavy payloads with ease. Omnidirectional wheels provide precision control for forward, lateral or twisting movements in constrained environments. Following suit of other Clearpath robots, Ridgeback is ROS-ready and designed for rapid integration of sensors and payloads; specific consideration has been made for the integration of the Baxter research platform.

"Giving Baxter automated mobility opens up a world of new research possibilities," said Brian Benoit, senior product manager at Rethink Robotics. "Researchers can now use Baxter and Ridgeback for a wide range of applications where mobility and manipulation are required, including service robotics, tele-operated robotics, and human robot interaction."

Learn more about Ridgeback AGV at www.clearpathrobotics.com/ridgeback. 

• The node publishes a new message (user_IDs) containing the ID of the tracked user
• The node publishes the video stream captured by the Xtion
• The node publishes the Point Cloud captured by the Xtion

The package can be downloaded here: https://github.com/Chaos84/skeleton_tracker.git
Just type:
    $ git clone https://github.com/Chaos84/skeleton_tracker.git

Programming is fun. Robots are fun. Programming robots is awesome! This episode Michael speaks with Dirk Thomas from the ROS (Robot Operating System) project. You will learn how to use ROS and ROSPy to program robots.

We discuss how to use ROS from some of the largest and most complex robots built (including one on the International Space Station!) all the way down to basic robots controlled via micro-controllers such as arduinos.  

We're excited to announce that OSRF and BIT Systems are seeking innovative and revolutionary robotics projects for the Robotics Fast Track (RFT) effort, sponsored by the Defense Advanced Research Projects Agency (DARPA).

The goals of Robotics Fast Track are:

1. Enable rapid, cost-effective development of new robotics capabilities designed to respond to, and even anticipate, quickly evolving needs in space, maritime, ground, and air operations. RFT will focus on the development of groundbreaking robotic hardware and software by funding novel approaches as well as creative adaptations of existing technologies.
2. Achieve breakthrough capabilities in less time and at a fraction of the cost typical of government-supported robotic development processes by engaging highly agile organizations and individuals who traditionally have not worked with the U.S. government.

Learn more and apply at rft.osrfoundation.org!

if someone is searching for a driver for the DepthSense DS325 RGB-D time-to-flight camera, I'm glad to say that the first working version of it is available on Github:

https://github.com/Myzhar/ros_depthsense_camera

At this stage the driver can correctly publish RGB videostream, Simple XYZ Pointcloud and RGB XYZ Pointcloud.

One of the strenght of my driver is the fact that it does not use neither OpenCV nor PCL libraries.
It publishes only  sensor_msg::pointcloud2 and sensor_msg::Image messages.

The next step will be the porting on CUDA of the heaviest function like the RGB to XYZ mapping and the use of the builtin accelerometer to compensate robot asset.
I will also write the code to simulate a 2D laser scanner to provide full information... if requested.

All this with an eye on the use of 100% of the potential of NVidia Jetson TK1...

Any comment or debug will be really appreciated

We would like to announce the recent completion of the Rapid Autonomous Complex-Environment Competing Ackermann-steering Robots (RACECAR) class. RACECAR is a new MIT Independent Activities Period (IAP) course focused on demonstrating high-speed vehicle autonomy in MIT's basement hallways (tunnels). The MIT News Office published an overview article with video at: https://newsoffice.mit.edu/2015/students-autonomous-robots-race-mit-tunnels-0406 . The course website is: http://racecar.mit.edu/ .

Instructors provided student teams with an model car outfitted with sensors, embedded processing, and a ROS-based software infrastructure. The base platform is a Traxxas 1:10-scale radio-controlled (RC) brushless motor rally car that is capable of reaching 40+ mph speeds. The sensor suite consists of a Hokuyo 10m scanning lidar, Pixhawk's PX4Flow optical flow camera, a Point Grey imaging camera, and SparkFun's Razor inertial measurement unit. Control and autonomy algorithms are processed on-board with an embedded NVIDA Jetson TK1 development kit running the Ubuntu Linux operating system with "The Grinch" custom kernel. The TK1's pulse width modulation (PWM) output signals drive the motor electronic speed controller and steering servomotor, bypassing the RC receiver.

The system uses the Robot Operating System (ROS) framework to facilitate rapid development. Existing ROS drivers (urg_node, razor_imu_9dof, pointgrey_camera_driver, and px4flow_node) receive data from the sensors. The model car's throttle and steering signals are commanded with a new ROS driver interface to the kernel's sysfs-based PWM subsystem. Students develop software and visualize data through a wireless network connection to a virtual machine running on their personal laptops.

Given the hardware platform and basic teleoperation software stack, teams of 4 -5 students prototype autonomy algorithms over an intense two week period. Students are invited to explore a variety of navigation approaches, from reactive to map-based control. At the end of the class, the teams' solutions are tested in a timed race around a closed-circuit course in MIT's tunnels. In January 2015, three of four teams reached the finish line with the winning team's average speed exceeding 7mph.

We would like to thank the many contributors to ROS and, in particular, Austin Hendrix for hosting the armhf binaries at the time.

RACECAR Instructors

• Install `ros-jade-desktop-full` on Ubuntu and test out packages you regularly use.
  
• Testing on other platforms is also appreciated!
• Try out any documentation that you can, including tutorials, package wiki pages, and generated code docs.
  
• Continue releasing packages and fill out the gaps between Jade and Indigo where possible.