Ana-Lucia Ureche

Cette personne n’est plus à l’EPFL

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Publications associées (5)

Automatic extraction of constraints in manipulation tasks for autonomy and interaction

Ana-Lucia Ureche

Tasks routinely executed by humans involve sequences of actions performed with high dexterity and coordination. Fully specifying these actions such that a robot could replicate the task is often difficult. Furthermore the uncertainties introduced by the us ...

EPFL2018

Open Robotics Research Using Web-based Knowledge Services

Aude Billard, Zhou Fang, Ana-Lucia Ureche, Nadia Barbara Figueroa Fernandez

In this paper we discuss how the combination of modern technologies in "big data" storage and management, knowledge representation and processing, cloud-based computation, and web technology can help the robotics community to establish and strengthen an op ...

Ieee2016

Learning Complex Sequential Tasks from Demonstration: A Pizza Dough Rolling Case Study

Aude Billard, Ana-Lucia Ureche, Nadia Barbara Figueroa Fernandez

This paper introduces a hierarchical framework that is capable of learning complex sequential tasks from human demonstrations through kinesthetic teaching, with minimal human intervention. Via an automatic task segmentation and action primitive discovery a ...

Ieee2016

Task Parameterization Using Continuous Constraints Extracted From Human Demonstrations

Aude Billard, Ana-Lucia Ureche

In this work we propose an approach for learning task specifications automatically, by observing human demonstrations. Using this allows a robot to combine representations of individual actions to achieve a high-level goal. We hypothesize that task specifi ...

Institute of Electrical and Electronics Engineers2015

Assessing Interaction Dynamics in the Context of Robot Programming by Demonstration

Aude Billard, Brenna Dee Argall, Ana-Lucia Ureche

In this paper we focus on human-robot interaction particularities that occur during programming by demonstration. Understanding what makes the interaction rewarding and keeps the user engaged helps optimize the robot's learning. Two user studies are presen ...

Springer Netherlands2013

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