Sökning: WFRF:(Nardi Andrea) >
Capturing Frame-Lik...
Capturing Frame-Like Object Descriptors in Human Augmented Mapping
-
- Faridghasemnia, Mohamadreza, 1991- (författare)
- Department of Computer, Control and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, Rome, Italy,AASS
-
- Vanzo, Andrea (författare)
- Mathematical and Computer Science School, Heriot-Watt University, Edinburgh, UK
-
- Nardi, Daniele (författare)
- Department of Computer, Control and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, Rome, Italy
-
(creator_code:org_t)
- 2019-11-12
- 2019
- Engelska.
-
Ingår i: AI*IA 2019 - Advances in Artificial Intelligence. - Cham : Springer. - 9783030351656 - 9783030351663 ; , s. 392-404
- Relaterad länk:
-
https://urn.kb.se/re...
-
visa fler...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- The model of an environment plays a crucial role in autonomous mobile robots, by providing them with the necessary task-relevant information. As robots become more intelligent, they need a richer and more expressive environment model. This model is a map that contains a structured description of the environment that can be used as the robot’s knowledge for several tasks, such as planning and reasoning. In this work, we propose a framework that allows to capture important environment descriptors, such as functionality and ownership of the robot’s surrounding objects, through verbal interaction. Specifically, we propose a corpus of verbal descriptions annotated with frame-like structures. We use the proposed dataset to train two multi-task neural architectures. We compare the two architectures through an experimental evaluation, discussing the design choices. Finally, we describe the creation of a simple interactive interface with our system, implemented through the trained model. The novelties of this work are: (i) the definition of a new problem, i.e., addressing different object descriptors, that plays a crucial role for the robot’s tasks accomplishment; (ii) a specialized corpus to support the creation of rich Semantic Maps; (iii) the design of different neural architectures, and their experimental evaluation over the proposed dataset; (iv) a simple interface for the actual usage of the proposed resources.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Natural Language understanding
- Semantic mapping
- Human robot interaction
- Neural networks
- Semantic mapping corpus
- Corpus annotator
- Computer Science
- Datavetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
Hitta via bibliotek
Till lärosätets databas