RoboEarth

European Robotics Week 2011 (Update)

Alexander Perzylo — Mon, 14 Nov 2011 05:23:18 +0000

Update (Jan 05, 2012):
More than 100 people joined the introduction to RoboEarth and the interactive workshops. They created and detected their first 3D object models using the RoboEarth platform. We want to thank everyone who helped to organize the successfull event as well as all participants who showed their interest.

RoboEarth will present itself as part of the European Robotics Week from November 28th – December 4th, 2011. Therefore the RoboEarth team will set up a live webcast on Friday, December 2nd, 2011, starting from 15.00 (CET).

Dr. Oliver Zweigle is going to present a brief introduction to the concepts of RoboEarth. Subsequently, an interactive workshop will be held. The aim for the workshop is to let anyone interested try out the RoboEarth software to build 3D object models themselves and use them to detect the described objects.

The workshop’s prerequisites and details on how to register can be found at http://www.roboearth.org/webcast. Registration will be open until November 20th, 2011. The webcast itself will also be made available through this website.

RoboEarth at IROS 2011

Alexander Perzylo — Thu, 06 Oct 2011 09:11:21 +0000

Members of the RoboEarth team contributed seven papers to the IROS’11 conference, which took place in San Francisco (USA) from September 25-30th. In addition, RoboEarth supported a workshop on Knowledge Representation for Autonomous Robots.

During the workshop Jos Elfring gave an introduction to RoboEarth’s approach to world modelling. It uses a multiple hypothesis filter (MHF) to keep track of objects over time and introduces techniques to improve the probabilistic models by taking prior knowledge about objects into account, e.g. object dynamics, expected locations, relations between object classes and detector characteristics. For more details on this topic take a look at the corresponding paper, Knowledge-Driven World Modeling.

Other papers presented during the regular paper sessions were:

Autonomous Semantic Mapping for Robots Performing Everyday Manipulation Tasks in Kitchen Environments. Nico Blodow, Lucian Cosmin Goron, Zoltan-Csaba Marton, Dejan Pangercic, Thomas Ruehr, Moritz Tenorth, and Michael Beetz
Parameterizing Actions to Have the Appropriate Effects. Lorenz Mösenlechner and Michael Beetz
Logic Programming with Simulation-Based Temporal Projection for Everyday Robot Object Manipulation. Lars Kunze, Mihai Emanuel Dolha and Michael Beetz
Towards Semantic SLAM using a Monocular Camera. Javier Civera, Dorian Gálvez-López, Luis Riazuelo, J.D. Tardós and J.M.M. Montiel
Dense Multi-Planar Scene Estimation from a Sparse Set of Images. Alberto Argiles, Javier Civera and Luis Montesano
Real-Time Loop Detection with Bags of Binary Words. Dorian Gálvez-López and Juan D. Tardós

RoboEarth’s First Open Source Release

Alexander Perzylo — Thu, 08 Sep 2011 09:04:01 +0000

We are happy to announce RoboEarth’s first open source software release. This release allows you to create 3D object models and upload them to RoboEarth. It also allows you to download any model stored in RoboEarth and detect the described object using a Kinect or a webcam.

If you are familiar with ROS, creating and using object models is easy. As shown in the video tutorial above, it uses three main packages:

RoboEarth’s re_object_recorder package allows you to create your own 3D object model using Microsoft’s Kinect sensor. By recording and merging point clouds gathered from different angles around the object, a detailed model is created, which may be shared with the world by uploading it to RoboEarth.
RoboEarth’s re_kinect_object_detector package allows you to detect models you download from RoboEarth using a Kinect.
Alternatively, you may also use RoboEarth’s re_vision package to detect objects using a common RGB camera.

A complete overview of the process can be found at http://www.ros.org/wiki/roboearth
RoboEarth aims at creating an object database including semantic descriptors. Semantic descriptors allow robots to not only detect objects, but reason about them. For example, if a robot is asked to serve a drink, semantic object descriptors allow the robot to determine if all required objects are available or if an additional object model is missing, and if a missing model is available via RoboEarth. You can help us with that process by supplying meaningful names and descriptions for the objects you create.

We are looking forward to your feedback in the comments below or at info at roboearth.org.

RoboEarth – A World Wide Web for Robots

Alexander Perzylo — Fri, 17 Jun 2011 08:00:39 +0000

The latest issue of the IEEE Robotics and Automation Magazine (RAM) is dedicated to building a WWW for robots.

Our contribution entitled RoboEarth – A World Wide Web for Robots gives an overview of RoboEarth: Its overall architecture, all key components, the available interfaces and an in-depth look at the topics the RoboEarth team is currently working on.
The paper also summarizes the work done so far and describes RoboEarth’s first three demonstrators.

Other contributions to this Special Issue highlight research that is intimately connected to RoboEarth’s vision of creating an Internet for robots:

Willow Garage’s Matai Ciocarlie et al. describes a 3D object database that contains grasp points, which paves the way for linking a first simple Action Recipe to grasp and pick up objects.
Tenorth et al. propose an approach that allows robots to make use of information from the Web, such as instructions to perform everyday tasks or descriptions of properties and the appearance of objects. The authors propose techniques to translate the information from human-readable form into representations the robot can use.
A contribution by Daniel Roggen et al. discusses methods for the automatic detection of actions in the wearable computing community, which provide valuable hints for RoboEarth’s Action and Situation Recognition and Labeling component.
Mozos et al. address the problem of exploiting the structure in today’s designed workplace interiors as an example for how future object model Web databases can be used by service robots to add semantics to their sensors’ readings and to build models of their environment.
Blake et al. introduce both developmental and operational paradigms, whereas robots can be outfitted with Web-oriented software interfaces that give them access to universally standard Web resources. A case study is performed to investigate and demonstrate the conversion of traditional robotic data exchange for communicating with web services.

It is exciting to see so many common efforts being made in the robotics community, and we hope that this Special Issue and our contribution will inspire many more researchers to work towards making the WWW for robots a reality.

RoboEarth in motion: Videos of the first three demonstrators

Alexander Perzylo — Thu, 16 Jun 2011 07:30:07 +0000

To catch a glimpse of what RoboEarth is all about, watch the following videos showing three demonstrators that have been developed in the last months.

During RoboEarth’s first internal workshop a demonstrator was built to showcase how sharing environmental information can be beneficial to robots, even if they use different hardware and/or software setups:

For the second demonstrator a humanoid robot was asked to serve a drink to a patient in a mock-up hospital room. By using RoboEarth the robot was able to achieve its task in spite of having only basic capabilities for movement, perception and mapping. It downloaded an Action Recipe from the RoboEarth database, which provided a machine understandable semantic description of the action. Using logical reasoning, the robot could identify missing components, such as a map of the room and models for all involved objects, and download them from RoboEarth:

The third demonstrator shows the feasibility of sharing articulation models for doors and drawers through RoboEarth.

Together, these three demonstrators take a first step towards showing that RoboEarth is feasible and useful. In particular, the first demonstrator illustrated how sharing data between multiple robots can lead to faster learning. The second demonstrator evidences that by taking prior knowledge into account the speed of performing complex tasks, such as serving a drink in the semi-structured environment of a hospital, can be greatly increased. The third demonstrator showed how robots can create knowledge that is useful across different robot platforms. Overall, using RoboEarth allows robots to benefit from the experience of other robots.