Indoor Navigation Using Semantic Symbolic Information

Sriharee, Gridaphat

doi:10.1109/cse.2013.173

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…This paper enhances the ontology-based spatial information model proposed in the previous work 15 with additional relations of spatial information. The spatial information model consists of connectivity, accessibility and some relations between spatial objects such as shown in Fig.…”

Section: The Ontology-based Spatial Information Modelmentioning

confidence: 94%

“…This enhances better interaction between the system and the user. The algorithm and technique for path finding are discussed in previous work 15 .…”

Section: Related Workmentioning

confidence: 99%

“…The communication of mobile application and the system is provided by servlet protocol. Path finding is considered from accessibility relation 15 . Fig.5 depicts some screens of mobile application.…”

Section: System Developmentmentioning

confidence: 99%

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A Symbolic-based Indoor Navigation System with Direction-based Navigation Instruction

Sriharee

2015

Procedia Computer Science

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Indoor navigation is difficult because of complexity of indoor space. The efficient navigation system is required for locating the objects in space with accuracy. This research proposes an indoor navigation system which relies on symbolic information described by OWL. The description is used for path finding and for generating navigation instruction. The proposed indoor navigation system is developed using semantic web technology and the mobile application for navigation is developed on Android platform. With OWL-based symbolic information, spatial object information is described semantically in which both computer and human are readable and therefore, the spatial object information is easier to create and to maintain. Using direction-based navigation, interaction between human and system is flexible and the users are able to realise the orientation of current location easily.

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Section: The Ontology-based Spatial Information Modelmentioning

confidence: 94%

“…This enhances better interaction between the system and the user. The algorithm and technique for path finding are discussed in previous work 15 .…”

Section: Related Workmentioning

confidence: 99%

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A Symbolic-based Indoor Navigation System with Direction-based Navigation Instruction

Sriharee

2015

Procedia Computer Science

Self Cite

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“…where the knowledge about locations, persons, or activities is mainly concerned. Ontologies about indoor spaces, people, activities can be found in literatures [26][27][28][29], and Protégé ontology library 1 can also be used as a good reference. We chose to design the ontology ourselves because of the specificity of the application.…”

Section: Construction Of the Domain Knowledge Ontologymentioning

confidence: 99%

Information Retrieval Based on Knowledge-Enhanced Word Embedding Through Dialog: A Case Study

Ren¹,

Wang²,

Liu³

2020

IJCIS

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The aim of this paper is to provide a systematic route of information retrieval from a knowledge-based database (or domain knowledge) through a dialog system of natural language interaction. The application is about a comprehensive building at a university, with classrooms, laboratory rooms, meeting rooms, research rooms and offices, and is to present related information the user asks for. First, the domain knowledge is expressed with predicate expressions based on the ontology structure; then the vocabulary is presented distributedly with word embedding enhanced with the domain knowledge; queries from the user are then converted into the intent (general) and slot elements (specific) with the help of trained recurrent neural network (RNN). The system works smoothly. The key point is integrating the two methods of knowledge-based and data-driven natural language processing into one system, and the domain knowledge is in the central part which is incorporated into the word embedding to make it specifically fit the natural language in this application.

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“…Approaches in the literature have advanced from requiring a human-in-the-loop, to automatically linking symbols and robot spatial models. Human-in-the-loop approaches began with using humans to interpret and follow automatically generated navigation instructions [39], before progressing to robots using Object Concept Symbol physical grounding social grounding symbol grounding Fig. 4: The semiotic triangle, first described by Peirce [29] human-annotated semantic maps to follow complex natural language instructions like "go to the kitchen while hugging the right wall" [8].…”

Section: Use Of Human Symbols In Robot Navigationmentioning

confidence: 99%

Robot Navigation in Unseen Spaces using an Abstract Map

Talbot,

Dayoub,

Corke

et al. 2020

Preprint

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Human navigation in built environments depends on symbolic spatial information which has unrealised potential to enhance robot navigation capabilities. Information sources such as labels, signs, maps, planners, spoken directions, and navigational gestures communicate a wealth of spatial information to the navigators of built environments; a wealth of information that robots typically ignore. We present a robot navigation system that uses the same symbolic spatial information employed by humans to purposefully navigate in unseen built environments with a level of performance comparable to humans. The navigation system uses a novel data structure called the abstract map to imagine malleable spatial models for unseen spaces from spatial symbols. Sensorimotor perceptions from a robot are then employed to provide purposeful navigation to symbolic goal locations in the unseen environment. We show how a dynamic system can be used to create malleable spatial models for the abstract map, and provide an open source implementation to encourage future work in the area of symbolic navigation. Symbolic navigation performance of humans and a robot is evaluated in a real-world built environment. The paper concludes with a qualitative analysis of human navigation strategies, providing further insights into how the symbolic navigation capabilities of robots in unseen built environments can be improved in the future.

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Indoor Navigation Using Semantic Symbolic Information

Cited by 6 publications

References 8 publications

A Symbolic-based Indoor Navigation System with Direction-based Navigation Instruction

A Symbolic-based Indoor Navigation System with Direction-based Navigation Instruction

Information Retrieval Based on Knowledge-Enhanced Word Embedding Through Dialog: A Case Study

Robot Navigation in Unseen Spaces using an Abstract Map

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