From OSRF

It's not sexy, but the next big thing for robots is starting to look like warehouse logistics. The potential market is huge, and a number of startups are developing mobile platforms to automate dull and tedious order fulfillment tasks. Transporting products is just one problem worth solving: picking those products off of shelves is another. Magazino is a German startup that's developing a robot called Toru that can grasp individual objects off of warehouse shelves, a particularly tricky task that Magazino is tackling with ROS.

Moritz Tenorth is Head of Software Development at Magazino. In his ROSCon talk, Moritz describes Magazino's Toru as "a mobile pick and place robot that works together with humans in a shared environment," which is exactly what you'd want in an e-commerce warehouse. The reason that picking is a hard problem, as Moritz explains, is perception coupled with dynamic environments and high uncertainty: if you want a robot that can pick a wide range of objects, it needs to be able to flexibly understand and react to its environment; something that robots are notoriously bad at. ROS is particularly well suited to this, since it's easy to intelligently integrate as much sensing as you need into your platform.

Magazino's experience building and deploying their robots has given them a unique perspective on warehouse commercialization with ROS. For example, databases and persistent storage are crucial (as opposed to a focus on runtime), and real-time control turns out to be less important than being able to quickly and easily develop planning algorithms and reducing system complexity. Software components in the ROS ecosystem can vary wildly in quality and upkeep, although ROS-Industrial is working hard to develop code quality metrics. Magazino is also working on remote support and analysis tools, and trying to determine how much communication is required in a multi-robot system, which native ROS isn't very good at.

Even with those (few) constructive criticisms in mind, Magazino says that ROS is a fantastic way to quickly iterate on both software and hardware in parallel, especially when combined with 3D printed prototypes for testing. Most importantly, Magazino feels comfortable with ROS: it has a familiar workflow, versatile build system, flexible development architecture, robust community that makes hiring a cinch, and it's still (somehow) easy to use.

Next up: Michael Ferguson (Fetch Robotics)

Shadow Robot - looking for a new Software Engineer

Job description The role of software engineers at Shadow Robot Ltd is to advance robotic systems, by implementing new solutions and algorithms, in order to realize complex tasks with a complex robots. Think about all the knowledge and skills a human requires to lift a simple glass of water, and try to imagine how you'd implement that with a highly sophisticated robotic system.

Should you join our team your job would center on solving real world problems using robotics. We work on highly challenging and stimulating problems to deliver new solutions using advanced robotic systems. The job is quite versatile, ranging from driver development, to more high level cognition. Being part of a team of highly skilled individuals, we always strive to make you work on what you're best at.

Overall your goal will be making our robotic systems more reliable and easier to use for our customers.

Company We're a small central London based company formed in 1987 with a well established reputation for developing top end robotic systems. Our core product is our robotic Hand, but we're also involved in a list of Robotics based projects for research, nuclear, MOD, space and other applications.

We're a close knit team, all passionate about robotics and will be happy to share our knowledge in different domains, ranging from electronics to manufacturing.

Shadow's mission is to use robotics technology to solve real-world problems.

Skills:

Must have:

  • highly proficient in C++ or python
  • good knowledge of programming under Linux

Nice to have:

  • previous experience or keen interest in robotics
  • previous experience using ROS

Experience:

  • minimum 2 years programming experience.

Contact toni@shadowrobot.com www.shadowrobot.com

Middlesex University intro to ROS summer school

From Nick Weldin

Middlesex University is running a one week Intro to ROS summer school 4 - 8 July in London, UK.

This is a practical introductory course in ROS, we will cover what ROS is, the way it works, and how you use it to control robots. We will start with the basic command line tools to get ROS running, and checking whats going on.

You will will learn how to use turtlebots to make maps and autonomously navigate around them. We will look at the basics of the Baxter Robot and how what you have learnt about ROS with one robot can be immediately applied to a very different robot.

We will cover the basics about writing code to work with ROS, and look at using simulation so you can carry on working on things once the course is finished and you may not have immediate access to a robot.

More details are available at http://www.mdx.ac.uk/courses/summer-school/courses/introduction-to-robot-operating-system

From NXROBO and ExBot Robotics Lab:

"Spark" is a series of ROS courses co-organized by NXROBO and Exbot Robotics Lab in order to promote the ROS and robotics in China.

The first "Spark-8" course had 8 basic lessons to help fresh-hands learn ROS step by step, while the complete "Spark-20" course had 20 lessons, from basic ROS programming skills to advanced applications such as simulation, SLAM, navigation and so on.

After months of preparation, the project started on the 5th of March, at the Open Source Maker Space in Shenzhen, China. A second session of the project was kicked off on May 21st, at ShenZhen University. Future sessions are expected to be hold in Beijing, Shanghai, Xian, Wuhan.

project-spark-capture-1.png

"Practical and effective" was the main topic of the project. NXROBO and Exbot tried to emphasize the combination of the theory and the practice in a learning-by-doing approach: They took a concrete robot as the model, simulated a real R&D scene, provided first-hand experience of the robotics R&D process, solved the practical problems effectively which ROS amateurs confront. The other distinguishing feature of the Spark Robot Club was a technology exchange platform which gathered top talents of ROS users with practical experience.

The "Spark" initiative became a hot topic in the chinese robotics industry once launched which was beyond expectation. More than 300 people joined the "Spark Robot Club" and the number still keep increasing, from newbies to a savvy specialists. There are members who even came to participate in the event from distant regions in China, including Beijing, Ningbo, Hunan or Guangzhou.

Dr. Tin-Lun Lam (CEO of NXROBO) acted as the tutor of the first course. He has more than ten years of R&D experience in the field of robotics and his exhaustive R&D projects including telepresence robot, tree-climbing robot, four-wheel independent steering and driving vehicle, unmanned sea surface vehicle, 6-axis industrial robotic arm and rescue robot.

project-spark-capture-2.png

In the workshop, Dr. Lam gave an introduction of ROS, its background and development, the design idea and the core concepts. On the other side, Dr. Lam demonstrated the communication mechanism of ROS by accomplish practical operations, gave an in-depth explanation of the basic topic/service of ROS communication layer model and a navigation application on a real robot. In the after-course exchange, Dr. Lam shared his experiences and ideas with the trainees and specialists.

project-spark-capture-3.png

On May 21st, the second open course was held in the auditorium of science building at the University of Shenzhen. Generally, the situation of the robotics education in chinese colleges is fairly harsh and the course materials are rarely updated. Furthermore, courses do not generally involve real robots to assist in the teaching/learning process therefore, NXROBO and ExBot put months into coming up with a ROS training that addressed all these issues.

While highlighting the theoretical aspects, they emphasized the concrete object demonstration to solve the practical problems of the ROS amateurs.

project-spark-capture-4.png

More open courses will be held by NXROBO and ExBot in different regions separately. NXROBO is looking for those who would like to devote themselves to the robot industry to act as tutors, help ROS gain ground among chinese robot amateurs and ultimately promote the development of robot technology.

More information about "Spark" and organizers:

The AutoRally Platform

From Brian Goldfain at Georgia Tech

We're the AutoRally team from Georgia Tech and we're pushing autonomous driving to the extreme with our AutoRally robot. Our robot reaches speeds of 20mph driving fully autonomously using only onboard sensing and computing at our test track, often powersliding around turns. We built this ROS compatible robot in-house as a high performance testbed for control and perception research because there was nothing like it commercially available. The platform is designed to be safe, robust, and accessible for testing aggressive autonomous driving. autorally_platform_gallery.jpg autorally_platform_twowheels.jpg We initially chose to use ROS as our middle layer for the same reason so many other use ROS: so we didn't have to start from scratch. The node structure, messaging, existing sensor drivers, and visualization tools helped us get our system up and running quickly and focus on pushing the limits of autonomous driving. As the project grew, we found new students with ROS experience gained from tinkering, clubs, or classes. Instead of spending months familiarizing themselves with custom software, they arrive with an understanding of core concepts and vocabulary required to immediately contribute to the project.

We want other ROS users to play with our code, build their own AutoRally platforms, then come race against our robots. Check out the AutoRally platform details here: http://autorally.github.io and a video of recent research on the platform presented at ICRA2016 titled "Aggressive Driving with Model Predictive Path Integral Control":

skip to the 2 minute mark if you just want to see the the results.

All of out our core code, a Gazebo world, and build instructions are available on GitHub: [https://github.com/AutoRally/autorally](https://github.com/AutoRally/autorally)

Tom Moore: Working with the Robot Localization Package

From OSRF

Clearpath Robotics is best known for building yellow and black robots that are the research platforms you'd build for yourself; that is, if it wasn't much easier to just get them from Clearpath Robotics. All of their robots run ROS, and Clearpath has been heavily involved in the ROS community for years. Now with Locus Robotics, Tom Moore spent seven months as an autonomy developer at Clearpath. He is the author and maintainer of the robot_localization ROS package, and gave a presentation about it at ROSCon 2015.

robotlocalization is a general purpose state estimation package that's used to give you (and your robot) an accurate sense of where it is and what it's doing, based on input from as many sensors as you want. The more sensors that you're able to use for a state estimate, the better that estimate is going to be, especially if you're dealing with real-worldish things like unreliable GPS or hardware that flakes out on you from time to time. robotlocalization has been specifically designed to be able to handle cases like these, in an easy to use and highly customizable way. It has state estimation in 3D space, gives you per-sensor message control, allows for an unlimited number of sensors (just in case you have 42 IMUs and nothing better to do), and more.

Tom's ROSCon talk takes us through some typical use cases for robot_localization, describes where the package fits in with the ROS navigation stack, explains how to prepare your sensor data, and how to configure estimation nodes for localization. The talk ends with a live(ish) demo, followed by a quick tutorial on how to convert data from your GPS into your robot's world frame.

The robot_localization package is up to date and very well documented, and you can learn more about it on the ROS Wiki.

Next up: Moritz Tenorth, Ulrich Klank, & Nikolas Engelhard (Magazino GmbH)

Internship at Bosch Research Institute, Palo Alto

From Lorenzo Riano via ros-users@

The Bosch Robotics Team is looking for outstanding Masters or PhD level interns to work on 3D perception applied to robotics. Identifying objects in cluttered environments, estimating their pose and tracking their position from a moving robotic arm are among the tasks to work on.

As the ideal candidate you have strong technical skills, are willing to tackle real-life problems and work in a highly dynamic team. You are also eager to solve real life problems and go the extra mile to create robust solutions. Depending on your background, you will solve challenging problems in 3D perception, computer vision, object reconstruction and localization. We strongly encourage producing research quality work that can lead to publications.

Skills / Job Requirements

· Currently pursuing a M.S. or PhD in CS, or related fields

· Robotics and/or computer vision-related coursework and experience

· Proven experience developing software using C++ (Python is a plus) and ROS

· Proven experience with Android and/or iOS development is a plus

· Knowledge of Linux and development on Linux systems

· Demonstrated ability to work independently as well as within a highly-motivated team environment.

· Excellent communication skills and a proven ability to deliver on challenging software development tasks.

· Experience in one or more of the research areas indicated above.

Required Application Materials

· Cover letter

· Resume/CV

· If possible, two references and/or two letters of recommendation

· Please indicate desired internship time frame

To apply please see the link http://www.bosch.us/content/language1/html/14884.htm

From Yanzhen Wang via ros-users@

This is an announcement for microsswarmframework, developed by Xuefeng Chang in our group (the micROS Team, https://micros.trustie.net). microsswarmframework is a ROS-based programming framework for swarm robotics. It is motivated by the rapidly increasing volume of research effort devoted into multi-robot systems and swarm robotics, and the design choice of API is largely enlightened by the Buzz programming language http://the.swarming.buzz/. Its goal is to facilitate ROS users in developing applications of robot swarms, by providing essential mechanisms, such as abstraction of swarms, swarm management, various communication tools, and a runtime environment, within the standard ROS ecosystem.

Currently, it is completely compatible with ROS indigo and presented in the form of a C++ library. Many additional features will be added in the future to make the framework more user-friendly and powerful.

Documentation can be found on ROS Wiki: https://wiki.ros.org/micros_swarm_framework. Source code for the framework and demos in the Stage simulator can be found on GitHub: https://github.com/xuefengchang/micros_swarm_framework.

Hope you enjoy! Comments and suggestions would be highly appreciated.

Find this blog and more at planet.ros.org.


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