ROSCon 2016: Proposal deadline July 8th and venue information

With just over 3 months to go before ROSCon 2016, we have some important announcements:

* The deadline for submitting presentation proposals is July 8, 2016. If you want to present your work at ROSCon this year, make sure to submit your proposal before the deadline: http://roscon.ros.org/2016/#call-for-proposals.
* The conference will be held at the Conrad Seoul. Hotel rooms at the discounted conference rate are limited! Reserve your room today. http://roscon.ros.org/2016/#location. Also listed are some options for child care during the conference, which we hope will be helpful for attendees traveling with families.
* Registration will open in a couple of weeks: http://roscon.ros.org/2016/#important-dates.

We can’t put on ROSCon without the support of our generous sponsors, who now include Clearpath Robotics, Southwest Research Institute, GaiTech, and ARM!
http://roscon.ros.org/2016/#sponsors

We’d like to especially thank our Platinum and Gold Sponsors: Fetch Robotics, Clearpath Robotics, Intel, Southwest Research Institute, and Yujin Robot.

Moritz Tenorth (Magazino): Maru and Toru — Item-Specific Logistics Solutions Based on ROS

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)

Tom Moore: Working with the Robot Localization Package

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.

robot_localization 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. robot_localization 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)

Matt Vollrath and Wojciech Ziniew (End Point): ROS-Driven User Applications in Idempotent Environments

Matt Vollrath and Wojciech Ziniew work at an ecommerce consultancy called End Point, where they provide support for Liquid Galaxy; a product that’s almost as cool as it sounds. Originally an open source project begun by Google engineers on their twenty percent time, Liquid Galaxy is a data visualization system consisting of a collection of large vertical displays that wrap around you horizontally. The displays show an immersive (up to 270°) image that’s ideal for data presentations, virtual tours, Google Earth, or anywhere you want a visually engaging environment. Think events, trade shows, offices, museums, galleries, and the like.

Last year, End Point decided to take all of the ad hoc services and protocols that they’d been using to support Liquid Galaxy and move everything over to ROS. The primary reason to do this was ROS support for input devices: you can use just about anything to control a Liquid Galaxy display system, from basic touchscreens to Space Navigator 3D mice to Leap Motions to depth cameras. The modularity of ROS is inherently friendly to all kinds of different hardware.

Check out this week’s ROSCon15 video as Matt and Wojciech take a deep dive into their efforts in bringing ROS to bear for these unique environments.

Next up: Tom Moore (Clearpath Robotics)

Jerry Towler (SwRI): Mapviz – An Extensible 2D Visualization Tool for Automated Vehicles

ROS already comes with a fantastic built-in visualization tool called rviz, so why would you want to use anything else? At Southwest Research Institute, Jerry Towler explains how they’ve created a new visualization tool called Mapviz that’s specifically designed for the kind of large-scale outdoor environments necessary for autonomous vehicle development. Specifically, Mapviz is able to integrate all of the sensor data that you need on top of a variety of two-dimensional maps, such as road maps or satellite imagery.

As an autonomous vehicle visualization tool, Mapviz works just like you’d expect that it would, which Jerry demonstrated with several demos at ROSCon. Mapviz shows you a top-down view of where your vehicle is, and tracks it across a basemap that seamlessly pulls image tiles at multiple resolutions from a wide variety of local or networked map servers, including Open MapQuest and Bing Maps. Mapviz is, of course, very plugin-friendly. You can add things like stereo disparity feeds, GPS fixes, odometry, grids, pathing data, image overlays, projected laser scans, markers (including textured markers) from most sensor types, and more. It can’t really handle three dimensional data (although it’ll do two-and-a-half dimensions via color gradients), but for interactive tracking of your vehicle’s navigation and path planning behavior, Mapviz should offer most of what you need.

For a variety of non-technical reasons, SwRI hasn’t been able to release all of its tools and plugins as open source quite yet, but they’re working on getting approval as fast as they can. They’re also in the process of developing even more enhancements for Mapviz, and you can keep up to date with the latest version of the software on GitHub.

Next up: Matt Vollrath & Wojciech Ziniewicz (End Point)

Michael Aeberhard (BMW): Automated Driving with ROS at BMW

BMW has been working on automated driving for the last decade, steadily implementing more advanced features ranging from emergency stop assistance and autonomous highway driving to fully automated valet parking and 360° collision avoidance. Several of these projects were presented at the 2015 Consumer Electronics Show, and as it turns out, the cars were running ROS for both environment detection and planning.

BMW, being BMW, has no problem getting new research hardware. Their latest development platform is the 335I G. This model comes with an advanced driver assistance system based around cameras and radar. The car has been outfitted with four low-profile laser scanners and one long-range radar, but otherwise, it’s pretty close (in terms of hardware) to what’s available in production BMWs.

Why did BMW choose to move from their internally developed software architecture to ROS? Michael explains how ROS’ reputation in the robotics research community prompted his team to give it a try, and they were impressed with its open source nature, distributed architecture, existing selection of software packages, as well as its helpful community. “A large user base means stability and reliability,” Michael says, “because somebody else probably already solved the problem you’re having.” Additionally, using ROS rather than a commercial software platform makes it much easier for BMW to cooperate with universities and research institutions.

Michael discusses the ROS software architecture that BMW is using to do its autonomous car development, and shows how the software interprets the sensor data to identify obstacles and lane markings and do localization and trajectory planning to enable full highway autonomy, based on a combination of lane keeping and dynamic cruise control. BMW also created their own suite of RQT and rviz plugins specifically designed for autonomous vehicle development.

After about two years of experience with ROS, BMW likes a lot of things about it, but Michael and his team do have some constructive criticisms: message transport needs more work (although ROS 2 should help with this), managing configurations for different robots is problematic, and it’s difficult to enforce compliance with industry standards like ISO and AUTOSAR, which will be necessary for software that’s usable in production vehicles.

Next up: Jerry Towler & Marc Alban (SwRI)

Amit Moran (Intel): Introducing ROS-RealSense: 3D Empowered Robotics Innovation Platform

While Intel is best known for making computer processors, the company is also interested in how people interact with all of the computing devices that have Intel inside. In other words, Intel makes brains, but they need senses to enable those brains to understand the world around them. Intel has developed two very small and very cheap 3D cameras (one long range and one short range) called RealSense, with the initial intent of putting them into devices like laptops and tablets for applications such as facial recognition and gesture tracking.

Robots are also in dire need of capable and affordable 3D sensors for navigation and object recognition, and fortunately, Intel understands this, and they’ve created the RealSense Robotics Innovation Program to help drive innovation using their hardware. Intel itself isn’t a robotics company, but as Amit explains in his ROSCon talk, they want to be a part of the robotics future, which is why they prioritized ROS integration for their RealSense cameras.

A RealSense ROS package has been available since 2015, and Intel has been listening to feedback from roboticists and steadily adding more features. The package provides access to the RealSense camera data (RGB, depth, IR, and point cloud), and will eventually include basic computer vision functions (including plane analysis and blob detection) as well as more advanced functions like skeleton tracking, object recognition, and localization and mapping tools.

Intel RealSense 3D camera developer kits are available now, and you can order one for as little as $99.

Next up: Michael Aeberhard, Thomas Kühbeck, Bernhard Seidl, et al. (BMW Group Research and Technology)
Check out last week’s post: The Descartes Planning Library for Semi-Constrained Cartesian Trajectories

Shaun Edwards (SwRI): The Descartes Planning Library for Semi-Constrained Cartesian Trajectories

Descartes is a path planning library that’s designed to solve the problem of planning with semi-constrained trajectories. Semi-constrained means that the degrees of freedom of the path you need to plan are fewer than the degrees of freedom that your robot has. In other words, when planning a path, there are one or more “free” axes that your robot has to work with that can be moved any which way without disrupting the path. This can open up the planning space if you can utilize them creatively, which traditional robots (especially in the industrial space) usually can’t. This results in reduced workspaces and (most dangerous of all) increased reliance on human intuition during the planning process.

Descartes was designed to generate common sense plans, exhibiting similar characteristics to paths planned by a human. It can solve easy problems quickly, and difficult problems eventually, integrating hybrid trajectories and dynamic replanning. It’s easy to use, with a GUI that allows you to quickly set anchor points that the robot replans around, with visual confirmation of the new path. The second half of Shaun’s ROSCon talk is an in-depth explanation of Descartes’ interfaces and implementations intended for path planning fans (you know who you are).

As with many (if not most) of the projects being presented at ROSCon, Descartes is open source, and all of the development is public. If you’d like to try it out, the current stable release runs on ROS Hydro, and a tutorial is available on the ROS Wiki to help you get started.

Next up: Amit Moran & Gila Kamhi (Intel)
Check out last week’s post: Phobos — Robot Model Development on Steroids

Kai von Szadkowski (University of Bremen): Phobos — Robot Model Development on Steroids

To model a robot in rviz, you first need to create what’s called a Unified Robot Description Format (URDF) file, which is an XML-formatted text file that represents the physical configuration of your robot. Fundamentally, it’s not that hard to create a URDF file, but for complex robots, these files tend to be enormously complicated and very tedious to put together. At the University of Bremen, Kai von Szadkowski was tasked with developing a URDF model for a 60 degrees of freedom robot called MANTIS (Multi-legged Manipulation and Locomotion System). Kai got a bit fed up with the process and developed a better way of doing it, called Phobos.

 

mantis

http://robotik.dfki-bremen.de/en/research/robot-systems/mantis.html

 

Phobos is an add-on for a piece of free and open-source 3D modeling and rendering software called Blender. Using Blender, you can create armatures, which are essentially kinematic skeletons that you can use to animate a 3D character. As it turns out, there are some convenient parallels between URDF models and 3D models in Blender: the links and joints in a URDF file equate to armatures and bones in Blender, and both use similar hierarchical structures to describe their models. Phobos adds a new toolbar to Blender that makes it easy to edit these models by adding links, motors, sensors, and collision geometries. You can also leverage Blender’s Python scripting environment to automate as much of the process as you’d like. Additionally, Phobos comes with a sort of “robot dictionary” in Python that manages all of the exporting to URDF for you.

 

Since the native URDF format can’t handle all of the information that can be incorporated into your model in Blender, Kai proposes an extended version of URDF called SMURF (Supplemental Mostly Universal Robot Format) that adds YAML files to a URDF, supporting annotations for sensor, motors, and anything else you’d like to include.

 

If any of this sounds good to you, it’s easy to try it out: Blender is available for free, and Phobos can be found on GitHub.

Mirko Bordignon (Fraunhofer IPA) and Shaun Edwards (SwRI): Bringing ROS to the Factory Floor

The ROS Industrial Consortium was established four years ago as a partnership between Yaskawa Motoman Robotics, Southwest Research Institute (SwRI), Willow Garage, and Fraunhofer IPA. The idea was to provide a ROS-based open-source framework for robotics applications, designed to make it easy (or at least possible) to leverage advanced ROS capabilities (like perception and planning) in industrial environments. Basically, ROS-I adds models, libraries, drivers, and packages to ROS that are specifically designed for manufacturing automation, with a focus on code quality and end user reliability.

Mirko Bordignon from Fraunhofer IPA opened the final ROSCon 2016 keynote by pointing out that ROS is still heavily focused on research and service robotics. This isn’t a bad thing, but with a little help, there’s an enormous opportunity for ROS to transform industrial robotics as well. Over the past few years. The ROS Industrial Consortium has grown into two international consortia (one in America and one in Europe), comprising over thirty members that provide financial and managerial support to the ROS-I community.

To help companies get more comfortable with the idea of using ROS in their robots, ROS-I holds frequent training sessions and other outreach events. “People out there are realizing that at least they can’t ignore ROS, and that they actually might benefit from it,” Bordignon says. And companies are benefiting from it, with ROS starting to show up in a variety of different industries in the form of factory floor deployments as well as products.

Bordignon highlights a few of the most interesting projects that the ROS-I community is working on at the moment, including a CAD to ROS workbench, getting ROS to work on PLCs, and integrating the OPC data protocol, which is common to many industrial systems.

Before going into deeper detail on ROS-I’s projects, Shaun Edwards from SwRI talks about how the fundamental idea for a ROS-I consortium goes back to one of their first demos. The demo was of a PR2 using 3D perception and intelligent path planning to pick up objects off of a table. “[Companies were] impressed by what they saw at Willow Garage, but they didn’t make the connection: that they could leverage that work,” Edwards explains. SwRI then partnered with Yaskawa to get the same software running on an industrial arm, “and this alone really sold industry on ROS being something to pay attention to,” says Edwards.

Since 2014, ROS-I has been refining a general purpose Calibration Toolbox for industrial robots. The goal is to streamline an otherwise time-consuming (and annoying) calibration process. This toolbox covers robot-to-camera calibration (with both stationary and mobile cameras), as well as camera-to-camera calibration. Over the next few months, ROS-I will be releasing templates for common calibration use cases to make it as easy as possible.

Path planning is another ongoing ROS-I project, as is ROS support for CANOpen devices (to enable IoT-type networking), and integrated motion planning for mobile manipulators. ROS-I actually paid the developers of the ROS mobile manipulation stack to help with this. “Leveraging the community this way, and even paying the community, is a really good thing, and I’d like to see more of it,” Edwards says.

To close things out, Edwards briefly touches on the future of ROS-I, including the seamless fusion of 3D scanning, intelligent planning, and dynamic manipulation, which is already being sponsored by Boeing and Caterpillar. If you’d like to get involved in ROS-I, they’d love for you to join them, and even if you’re not directly interested in industrial robotics, there are still plenty of opportunities to be part of a more inclusive and collaborative ROS ecosystem.

Next up: Kai von Szadkowski (University of Bremen)
Check out last week’s post: MoveIt! Strengths, Weaknesses, and Developer Insight