research:projects
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| ===== Current Projects ===== | ===== Current Projects ===== | ||
| - | [[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: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. |
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| + | ===== 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. | {{: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. | ||
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| - | ===== Completed Projects (Selection) ===== | ||
| {{:research:3rdhand.png?nolink&110 |3rdHand}} | {{:research:3rdhand.png?nolink&110 |3rdHand}} | ||
research/projects.txt · Last modified: 2024/02/19 12:24 by Antonio Rodriguez-Sanchez