Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.588402
Title: Spatially motivated dialogue for a pedestrian robot
Author: Frost, Jamie
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2012
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Abstract:
In the field of robotics, there has recently been tremendous progress in the development of autonomous robots that offer various services to their users. Most of the systems developed so far, however, are restricted to indoor scenarios, non-urban outdoor environments, or road usage with cars. There is a serious lack of capabilities of mobile robots to navigate safely in highly populated outdoor environments. This ability, however, is a key competence for a series of robotic applications. We consider the task of developing a spatially motivated dialogue system that can operate on a robotic platform, where the purpose of such a robot is to aid pedestrians in urban environments to provide information about surrounding objects and services, and guide users to desired destinations. In this thesis, we make a number of contributions to the fields of spatial language interpretation/generation and discourse modelling. This includes the development of a dialogue framework called HURDLE which builds on the strengths of existing systems, accompanied by a specific implementation for spatially oriented dialogue including disambiguating amongst objects and locations in the environment, and a natural language parser which combines an extension of Synchronous Context Free Grammars with a Part-of-Speech tagger. Our research also presents a number of probabilistic models for spatial prepositions such as `in front of' and `between' that make significant advances in effectively utilising geometric environment data, encompassing visibility considerations and being reusable for both indoor and outdoor environments. We also present a number of algorithms in which these models can be utilised, most significantly a novel and highly effective algorithm that can generate natural language descriptions of objects that disambiguates on their location. All these components, while modular, operate in tandem and interact with a variety of external components (such as path planning) on the robot platform.
Supervisor: Pulman, Stephen Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.588402  DOI: Not available
Keywords: Robotics ; computational linguistics ; spatial cognition ; semantics
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