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Determining where to grasp cloth using depth information
(IOS Press, 2011)
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In this paper we address the problem of finding an initial good grasping point for the robotic manipulation of textile objects lying on a flat surface. Given as input a point cloud of the cloth acquired with a 3D camera, ...
Learning robot policies using a high-level abstraction persona-behaviour simulator
(2019)
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Collecting data in Human-Robot Interaction for training learning agents might be a hard task to accomplish. This is especially true when the target users are older adults with dementia since this usually requires hours of ...
Robot-aided cloth classification using depth information and CNNs
(2016)
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We present a system to deal with the problem of classifying garments from a pile of clothes. This system uses a robot arm to extract a garment and show it to a depth camera. Using only depth images of a partial view of the ...
Single image 3D human pose estimation from noisy observations
(2012)
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Markerless 3D human pose detection from a single image is a severely underconstrained problem because different 3D poses can have similar image projections. In order to handle this ambiguity, current approaches rely on ...
Planning surface cleaning tasks by learning uncertain drag actions outcomes
(2013)
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A method to perform cleaning tasks is presented where
a robot manipulator autonomously grasps a textile and
uses different dragging actions to clean a surface. Ac-
tions are imprecise, and probabilistic planning is ...
Probabilistic planning for robotics with ROSPlan
(2019)
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Probabilistic planning is very useful for handling uncertainty in planning tasks to be carried out by robots. ROSPlan is a framework for task planning in the Robot Operating System (ROS), but until now it has not been ...
Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
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For a safe and successful daily living assistance, far from the highly controlled environment of a factory, robots should be able to adapt to ever-changing situations. Programming such a robot is a tedious process that ...
Finding safe policies in model-based active learning
(2014)
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Task learning in robotics is a time-consuming process, and model-based reinforcement learning algorithms have been proposed to learn with just a small amount of experiences. However, reducing the number of experiences used ...
External force estimation for textile grasp detection
(2012)
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Our current work on external force estimation without end-effector force sensor is resented.To verify if a grasp of a textile has been successful, the external wrench applied on the robot is computed online, with a state ...
Teaching grasping points using natural movements
(IOS Press, 2015)
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The research on robots performing every-day tasks at home, has pursued the problem of the manipulation of everyday objects. Among them, grasping a cloth is a challenging task, as the textile is highly-deformable and it is ...