A Qualitative Approach to Localization and Navigation Based on Visibility Information

Fogliaroni, Paolo; Wallgrün, Jan Oliver; Clementini, Eliseo; Tarquini, Francesco; Wolter, Diedrich

doi:10.1007/978-3-642-03832-7_19

Cited by 33 publications

(21 citation statements)

References 15 publications

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“…For the sake of clarity, the point size is exaggerated Table 3 Summary of topological relations for all models and for all dimensions between simple objects Table 4 Number of topological relations between two complex spatial objects for the 9IM tion of few contributions about topological relations [34] and projective relations [16]. In urban applications, it is important to examine 3D objects that are anchored to the Earth's surface with an added vertical direction: work on visibility relations between such objects has been preliminary carried out in [41,43,64].…”

Section: Dimension Of the Embedding Spacementioning

confidence: 99%

A Conceptual Framework for Modelling Spatial Relations

Clementini¹

2019

ITC

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Various approaches lie behind the modelling of spatial relations, which is a heterogeneous and interdisciplinary field. In this paper, we introduce a conceptual framework to describe the characteristics of various models and how they relate each other. A first categorization is made among three representation levels: geometric, computational, and user. At the geometric level, spatial objects can be seen as point-sets and relations can be formally defined at the mathematical level. At the computational level, objects are represented as data types and relations are computed via spatial operators. At the user level, objects and relations belong to a context-dependent user ontology. Another way of providing a categorization is following the underlying geometric space that describes the relations: we distinguish among topologic, projective, and metric relations. Then, we consider the cardinality of spatial relations, which is defined as the number of objects that participate in the relation. Another issue is the granularity at which the relation is described, ranging from general descriptions to very detailed ones. We also consider the dimension of the various geometric objects and the embedding space as a fundamental way of categorizing relations.

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Section: Dimension Of the Embedding Spacementioning

confidence: 99%

A Conceptual Framework for Modelling Spatial Relations

Clementini¹

2019

ITC

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“…The space bounded by these lines define regions, which can then be treated as vertices of a topological map. The spatial representation behind this idea was further developed in [17,39,44]. In particular, [17] considers extended convex (instead of point-wise) objects as landmarks and the decomposition of space is based on the notions of occlusion and visibility, which has much in common to the PQRS formalism investigated in this paper.…”

Section: Related Researchmentioning

confidence: 99%

Reasoning about shadows in a mobile robot environment

et al. 2012

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Fenelon, V., Santos, P. E., Dee, H. M., Cozman, F. G. (2013). Reasoning about shadows in a mobile robot environment. Applied Intelligence, 38 (4), 553-565This paper describes a logic-based formalism for qualitative spatial reasoning with cast shadows (Perceptual Qualitative Relations on Shadows, or PQRS) and presents results of a mobile robot qualitative self-localisation experiment using this formalism. Shadow detection was accomplished by mapping the images from the robot?s monocular colour camera into a HSV colour space and then thresholding on the V dimension. We present results of self-localisation using two methods for obtaining the threshold automatically: in one method the images are segmented according to their grey-scale histograms, in the other, the threshold is set according to a prediction about the robot?s location, based upon a qualitative spatial reasoning theory about shadows. This theory-driven threshold search and the qualitative self-localisation procedure are the main contributions of the present research. To the best of our knowledge this is the first work that uses qualitative spatial representations both to perform robot self-localisation and to calibrate a robot?s interpretation of its perceptual input.Peer reviewe

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“…Viewshed computation and analysis have long been applied in landscape and urban studies [15,16,17]. The main principle of a viewshed analysis is commonly determined by defining one location as the viewing point, and then calculating the line-of-sight to every other point within the region of interest.…”

Section: Visibility-based Approachmentioning

confidence: 99%

A Visibility and Spatial Constraint-Based Approach for Geopositioning

Yaouanc

Saux

Claramunt

2010

Geographic Information Science

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Abstract. Over the past decade, automated systems dedicated to geopositioning have been the object of considerable development. Despite the success of these systems for many applications, they cannot be directly applied to qualitative descriptions of space. The research presented in this paper introduces a visibility and constraint-based approach whose objective is to locate an observer from the verbal description of his/her surroundings. The geopositioning process is formally supported by a constraint-satisfaction algorithm. Preliminary experiments are applied to the description of environmental scenes.

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A Qualitative Approach to Localization and Navigation Based on Visibility Information

Cited by 33 publications

References 15 publications

A Conceptual Framework for Modelling Spatial Relations

A Conceptual Framework for Modelling Spatial Relations

Reasoning about shadows in a mobile robot environment

A Visibility and Spatial Constraint-Based Approach for Geopositioning

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