RoboEarth

Waibel, Markus; Beetz, Michael; Civera, Javier; D’Andrea, Raffaello; Elfring, Jos; Gálvez-López, Dorian; Häußermann, Kai; Janssen, Rob; Montiel, José María; Perzylo, Alexander; Schießle, Björn; Tenorth, Moritz; Zweigle, Oliver; Molengraft, René De

doi:10.1109/mra.2011.941632

Cited by 404 publications

(159 citation statements)

References 48 publications

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“…Big Data can also facilitate learning in Computer Vision, by matching sensor data to 3D models in an online database. [14] The RoboEarth project stores data related to objects maps, and tasks, for applications ranging from object recognition to mobile navigation to grasping and manipulation (see Figure 1) [16].…”

Section: A Big-datamentioning

confidence: 99%

IoT and Robotics: a synergy

Chowdhury¹

2017

Preprint

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Abstract-The Internet of Robotic Things (IoRT) [9] is a concept first introduced by Dan Kara at ABI Research, which talks about augmenting the existing IoT with active sensorization; thereby, opening the doors to novel business ideas, at the intersection of both IoT and Robotics. This position paper considers the synergy between IoT and robotics: it talks about the technologies in IoT that would benefit the robotics domain. The advent of Cloud Robotics and its role in aiding robot functions like sensing, manipulation, and mobility. The paper then discusses the ways in which robots can extend the capabilities of existing IoT infrastructure by acting as a special class of edge device. IoT-aided robotic applications are discussed in various domains like health-care, military, industrial plants and rescue operations. The paper concludes by considering the use case of an Intelligent Transportation System endowed by an IoRT-inspired architecture.

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Section: A Big-datamentioning

confidence: 99%

IoT and Robotics: a synergy

Chowdhury¹

2017

Preprint

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“…Web-based databases of user-generated content, such as videos from YouTube, images from Flickr, and 3D models from Google 3D Warehouse, have begun to support the development of robots and technology relevant to robots (Klank et al 2009;Lai and Fox 2009;Kollar and Roy 2009;Kuffner 2010;Waibel et al 2011). More generally, research has shown that large datasets can lead to performance gains and make computationally simple methods effective (Torralba et al 2008;Halevy et al 2009).…”

Section: Broader Implicationsmentioning

confidence: 99%

Improving robot manipulation with data-driven object-centric models of everyday forces

Jain

Kemp

2013

Auton Robot

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Based on a lifetime of experience, people anticipate the forces associated with performing a manipulation task. In contrast, most robots lack common sense about the forces involved in everyday manipulation tasks. In this paper, we present data-driven methods to inform robots about the forces that they are likely to encounter when performing specific tasks. In the context of door opening, we demonstrate that data-driven object-centric models can be used to haptically recognize specific doors, haptically recognize classes of door (e.g., refrigerator vs. kitchen cabinet), and haptically detect anomalous forces while opening a door, even when opening a specific door for the first time. We also demonstrate that two distinct robots can use forces captured from people opening doors to better detect anomalous forces. These results illustrate the potential for robots to use shared databases of forces to better manipulate the world and attain common sense about everyday forces.

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“…The challenge focuses on the following aspects: (1) there is no predefined order of actions to carry out; and (2) environmental reasoning is required to deduce unknown facts. In our example the unknown information consists of the specific locations of objects and locations, such as the 'Living room', 'Side table' etc.…”

Section: Basic Experimentsmentioning

confidence: 99%

“…The RoboEarth project [1] aims to provide robots with such storage and communication mechanisms, enabling the global sharing of information between robots required to efficiently and safely execute their instructed tasks. The information shared through RoboEarth consists out of the maps used for localization and navigation, the object models used for perception and navigation, object ontologies used for reasoning and classification, and task descriptions, or so called action recipes, that symbolically describe task related action sequences and constraints.…”

Section: Introductionmentioning

confidence: 99%

Integrating planning and execution for ROS enabled service robots using hierarchical action representations

Janssen

Meijl

Marco

et al. 2013

2013 16th International Conference on Advanced Robotics (ICAR)

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Abstract-The aim of the RoboEarth project is to develop a globally accessible database, that enables service robots to share reusable information relevant to the execution of their daily tasks. Examples of this information are the hierarchical task descriptions, or action recipes, that represent typical household tasks as symbolic action sequences. By annotating these static action representations with hierarchical planner predicates, they can be interpreted by the Hierarchical Task Network planner SHOP2 to compose more flexible, optimized robot plans, based on the actual state of the environment and the available capabilities of the robot. To subsequently execute the composed plans in a typical household environment, the CRAM executive toolbox is adopted, allowing a tight integration between plan execution and run-time knowledge inference. This paper presents the integration of these two components into one cohesive planning and execution framework, tailored for the safe execution of abstract tasks in a challenging household environment. The resulting framework is implemented on the AMIGO service robot and a basic experiment is conducted to demonstrate the frameworks integral functionality.

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RoboEarth

Cited by 404 publications

References 48 publications

IoT and Robotics: a synergy

IoT and Robotics: a synergy

Improving robot manipulation with data-driven object-centric models of everyday forces

Integrating planning and execution for ROS enabled service robots using hierarchical action representations

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