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research:projects [2013/06/28 13:14]
Simon Haller [Current EU Projects]
research:projects [2017/11/11 13:03] (current)
Justus Piater
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 ====== Externally-Funded,​ Collaborative Projects ====== ====== Externally-Funded,​ Collaborative Projects ======
  
-===== Current ​EU Projects =====+===== Current Projects =====
  
-{{:​research:​pacman_logo2.png?​nolink&​110 |PaCMan}} PaCMan (EU FP7-ICT-STREP, 2013-2016) advances methods for object perceptionrepresentation and manipulation so that a robot is able to robustly manipulate ​objects ​even when those objects are unfamiliar, ​and even though ​the robot has unreliable perception and actionThe proposal ​is founded on two assumptions. The first of these is that the representation ​of the object'​s shape in particular and of other properties in general will benefit from being compositional (or very loosely hierarchical and part based). The second is that manipulation planning ​and execution benefits from explicitly reasoning about uncertainty in object pose, shape etcetera; how it changes under the robot'​s actions, ​and the robot should plan actions that not only achieve ​the task, but gather information ​to make task achievement more reliable.+{{:​research:​flexrop-logo.png?​nolink&​200 ||}}[[https://​www.profactor.at/​en/​research/​industrial-assistive-systems/​roboticassistance/​projects/​flexrop/​|FlexRoP ​Flexibleassistive ​robot for customized production]] (FFG (Austria) ICT of the Future, 2016-2018): Production of mass customized products ​is not easy to automate since objects and object positions remain more uncertain compared to mass production scenarios. Uncertainty handling motivates ​the application of advanced sensor-based control strategies which increases system complexity of robot applications dramaticallyA possible solution to this conflict ​is the concept ​of task level or skill based programming that will render modern robot systems. Such systems can be applied without safety fence, are easier to program, more applicable and transformable into capable robot assistants. The project will implement a skill based programming framework ​and will apply it on selected industrial demo scenarios ​and evaluate research results. The main focus of the project is the application of methods ​to acquire process information by worker monitoring and thus make the robot assistants self-learning.
  
-{{:​research:​xperience.png?​nolink&​110 |Xperience}} [[http://www.xperience.org/|Xperience]] (EU FP7-ICT-IP2011-2015pursues two principal objectives. The first goal is to show that the state of the art enactive embodied cognition systems can be significantly enhanced ​by using structural bootstrapping - a concept taken from language learningThe second goal is to implement a complete ​robot system for automating introspectivepredictive, and interactive understanding ​of actions ​and dynamic situations.+<​html>​ 
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 +{{:​research:​imagine-transparent.png?​nolink&​200 ||}}[[https://www.imagine-h2020.eu|IMAGINE - Robots Understanding Their Actions by Imagining Their Effects ​]] (EU H20202017-2020): seeks to enable robots to understand ​the structure ​of their environment and how it is affected ​by its actions“Understanding” here means the ability of the robot (a) to determine the applicability of an action along with parameters to achieve the desired effectand (b) to discern to what extent an action succeeded, and to infer possible causes ​of failure ​and generate recovery actions.
  
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-{{:​research:​intellact.png?​nolink&​110 |IntellAct}} [[http://​www.intellact.eu/|IntellAct]]  (EU FP7-ICT-STREP, ​2011-2014addresses the problem ​of understanding ​and exploiting ​the meaning ​(semanticsof manipulations in terms of objectsactions ​and their consequences for reproducing human actions with machinesThis is in particular ​required for the interaction between humans and robots in which the robot has to understand ​the human action ​and then to transfer it to its own embodiment.+{{:​research:​squirrel.png?​nolink&​200 |}}[[http://​www.squirrel-project.eu/|SQUIRREL]] (EU FP7-ICT-STREP, ​2014-2018): Clutter in an open world is a challenge for many aspects ​of robotic systems, especially for autonomous robots deployed in unstructured domestic settings, affecting navigation, manipulation,​ vision, human robot interaction ​and planning. ​ SQUIRREL addresses these issues by actively controlling clutter and incrementally learning to extend ​the robot'​s capabilities while doing so. We term this the B3 (bit by bitapproachas the robot tackles clutter one bit at a time and also extends its knowledge continuously as new bits of information become available ​SQUIRREL ​is inspired by a user driven scenario, that exhibits all the rich complexity ​required ​to convincingly drive research, but allows tractable solutions with high potential ​for exploitation. We propose a toy cleaning scenario, where a robot learns ​to collect toys scattered in loose clumps or tangled heaps on the floor in a child'​s room, and to stow them in designated target locations.
  
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 ===== Completed Projects (Selection) ===== ===== Completed Projects (Selection) =====
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 +{{:​research:​3rdhand.png?​nolink&​110 |3rdHand}}
 +[[http://​3rdhandrobot.eu/​|3rdHand]] (EU FP7-ICT-STREP,​ 2013-2017) develops a semi-autonomous robot assistant that acts as a third hand of a human worker. It will be straightforward to instruct even by an untrained layman worker, allow for efficient knowledge transfer between tasks, and enable effective collaboration between a human worker with a robot third hand. The main contributions of this project will be the scientific principles of semi-autonomous human-robot collaboration,​ a new semi-autonomous robotic system that is able to (i) learn cooperative tasks from demonstration,​ (ii) learn from instruction,​ and (iii) transfer knowledge between tasks and environments.
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 +{{:​research:​pacman_logo2.png?​nolink&​110 |PaCMan}} [[http://​www.pacman-project.eu/​|PaCMan]] (EU FP7-ICT-STREP,​ 2013-2016) advances methods for object perception, representation and manipulation so that a robot is able to robustly manipulate objects even when those objects are unfamiliar, and even though the robot has unreliable perception and action. The proposal is founded on two assumptions. The first of these is that the representation of the object'​s shape in particular and of other properties in general will benefit from being compositional (or very loosely hierarchical and part based). The second is that manipulation planning and execution benefits from explicitly reasoning about uncertainty in object pose, shape etcetera; how it changes under the robot'​s actions, and the robot should plan actions that not only achieve the task, but gather information to make task achievement more reliable.
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 +{{:​research:​xperience.png?​nolink&​110 |Xperience}} [[http://​www.xperience.org/​|Xperience]] (EU FP7-ICT-IP, 2011-2015) pursues two principal objectives. The first goal is to show that the state of the art enactive embodied cognition systems can be significantly enhanced by using structural bootstrapping - a concept taken from language learning. The second goal is to implement a complete robot system for automating introspective,​ predictive, and interactive understanding of actions and dynamic situations.
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 +{{:​research:​intellact.png?​nolink&​110 |IntellAct}} [[http://​intellact.sdu.dk/​|IntellAct]] ​ (EU FP7-ICT-STREP,​ 2011-2014) addresses the problem of understanding and exploiting the meaning (semantics) of manipulations in terms of objects, actions and their consequences for reproducing human actions with machines. This is in particular required for the interaction between humans and robots in which the robot has to understand the human action and then to transfer it to its own embodiment.
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 {{:​research:​learnbip.png?​nolink&​110 |LearnBiP}} [[http://​www.learnbip.eu/​|LearnBiP]] (EU FP7-ICT ECHORD Experiment, 2011-2012) has two main aims. First it utilizes the huge amount of data generated in industrial bin-picking for the introduction of grasp learning. Second it evaluates the potential of the SCHUNK dexterous hand SDH-2 for its application in industrial bin-picking. {{:​research:​learnbip.png?​nolink&​110 |LearnBiP}} [[http://​www.learnbip.eu/​|LearnBiP]] (EU FP7-ICT ECHORD Experiment, 2011-2012) has two main aims. First it utilizes the huge amount of data generated in industrial bin-picking for the introduction of grasp learning. Second it evaluates the potential of the SCHUNK dexterous hand SDH-2 for its application in industrial bin-picking.
  
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research/projects.1372418088.txt.gz · Last modified: 2013/06/28 13:14 by Simon Haller