Reasoning about natural language phrases for semantic goal driven exploration

Talbot, Ben, Schulz, Ruth, Upcroft, Ben, & Wyeth, Gordon (2015) Reasoning about natural language phrases for semantic goal driven exploration. In Proceedings of the Australasian Conference on Robotics and Automation 2015, Australian National University, Canberra, A.C.T.

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Abstract

This paper presents a symbolic navigation system that uses spatial language descriptions to inform goal-directed exploration in unfamiliar office environments. An abstract map is created from a collection of natural language phrases describing the spatial layout of the environment. The spatial representation in the abstract map is controlled by a constraint based interpretation of each natural language phrase. In goal-directed exploration of an unseen office environment, the robot links the information in the abstract map to observed symbolic information and its grounded world representation. This paper demonstrates the ability of the system, in both simulated and real-world trials, to efficiently find target rooms in environments that it has never been to previously. In three unexplored environments, it is shown that on average the system travels only 8.42% further than the optimal path when using only natural language phrases to complete navigation tasks.

Impact and interest:

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ID Code: 91065
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: semantic navigation, symbolic spatial information, natural language
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Natural Language Processing (080107)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Divisions: Current > Research Centres > ARC Centre of Excellence for Robotic Vision
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2015 [Please contact author]
Deposited On: 07 Dec 2015 23:23
Last Modified: 08 Dec 2015 23:37

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