Learning Semantic Maps from Natural Language Descriptions

Learning Semantic Maps from Natural Language Descriptions

This paper proposes an algorithm that enables robots to efficiently learn human-centric models of their environment from natural language descriptions. Typical semantic mapping approaches augment metric maps with higher-level properties of the robot’s surroundings (e.g., place type, object locations...

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Bibliographic Details
Main Authors: Walter, Matthew R., Hemachandra, Sachithra Madhaw, Homberg, Bianca S., Tellex, Stefanie, Teller, Seth
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Robotics: Science and Systems 2014
Online Access:http://hdl.handle.net/1721.1/87051
https://orcid.org/0000-0001-7036-000X

Internet

http://hdl.handle.net/1721.1/87051
https://orcid.org/0000-0001-7036-000X

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