Differences

This shows you the differences between two versions of the page.

--- research:projects [2013/06/28 13:14]
c703101 [Current EU Projects]
+++ research:projects [2018/09/07 11:29]
127.0.0.1 external edit
@@ Line 1: / Line 1: @@
 ====== 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 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.
+{{:research:flexrop-logo.png?nolink&200 ||}}[[https://www.profactor.at/en/research/industrial-assistive-systems/roboticassistance/projects/flexrop/|FlexRoP - Flexible, assistive 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 dramatically. A 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-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.
 <html>
-<div style="clear:both"></div>
+<div style="clear:both"><br></div>
 </html>
-{{:research:intellact.png?nolink&110 |IntellAct}} [[http://www.intellact.eu/|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.
+{{:research:imagine-transparent.png?nolink&200 ||}}[[https://www.imagine-h2020.eu|IMAGINE - Robots Understanding Their Actions by Imagining Their Effects ]] (EU H2020, 2017-2020): 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 effect, and (b) to discern to what extent an action succeeded, and to infer possible causes of failure and generate recovery actions.
 <html>
-<div style="clear:both"></div>
+<div style="clear:both"><br></div>
 </html>
 ===== Completed Projects (Selection) =====
+{{: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 bit) approach, as 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.
+<html>
+<div style="clear:both"><br></div>
+</html>
+{{: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.
+<html>
+<div style="clear:both"><br></div>
+</html>
+{{: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.
+<html>
+<div style="clear:both"><br></div>
+</html>
+{{: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.
+<html>
+<div style="clear:both"><br></div>
+</html>
+{{: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.
+<html>
+<div style="clear:both"><br></div>
+</html>
 {{: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.
 <html>
-<div style="clear:both"></div>
+<div style="clear:both"><br></div>
 </html>
@@ Line 29: / Line 57: @@
 <html>
-<div style="clear:both"></div>
+<div style="clear:both"><br></div>
 </html>
@@ Line 35: / Line 63: @@
 <html>
-<div style="clear:both"></div>
+<div style="clear:both"><br></div>
 </html>

User Tools

Site Tools

Differences

Page Tools