Autonomous robots typically rely on internal representations of the environment, or maps, to plan and execute their tasks. Several types of maps have been proposed in the literature, and there is general consensus that different types have different advantages and limitations, and that each type is more suited to certain tasks and less to others. Because of these reasons, it is becoming common wisdom in the field of mobile robotics to use hybrid maps that integrate several representations, usually of different types. Hybrid maps provide scalability and multiple views, allowing for instance to combine robot-centered and human-centered representations. There is, however, little understanding of the general principles that can be used to combine different maps into a hybrid one, and to make it something more than the sum of its parts. There is no systematic analysis of the different ways in which different maps can be combined…
Contents
1 Introduction
1.1 Aworldofmaps
1.2 Motivation and goals
1.3 Proposedapproach
1.4 Maincontributions
1.5 Outlineofthisthesis
2 Literature Survey
2.1 Introduction
2.2 Metricmaps
2.2.1 Metricmapbuilding
2.2.2 Metriclocalization
2.2.3 Metricpathplanning
2.3 Topologicalmaps
2.3.1 Topologicalmapbuilding
2.3.2 Topologicallocalization
2.3.3 Topologicalpathplanning
2.4 Hybridmaps
2.4.1 Motivation
2.4.2 Earlyhybridmaps
2.4.3 Parallelmaps
2.4.4 Patchworkmaps
3 Anatomy of Hybrid Maps
3.1 A foundational gap
3.2 Mapdefinitions
3.3 Usabilities
3.4 Propertiesofhybridization
3.5 Componentco-operation
3.5.1 Injection
3.5.2 Synergy
3.6 Challengesinhybridmaps
3.7 Designguidelines
3.7.1 Domainparameters
3.7.2 Designanewhybridmap
3.7.3 Enhancing an existing map
3.8 Summary
4 Analysis of Existing Hybrid Maps
4.1 Analysismethodology
4.2 GroupI:Extensivehybridmaps
4.3 GroupII:Patchworkofmetricmaps
4.4 GroupIII:Parallelmaps
4.5 GroupIV:Purelyhierarchicalmaps
4.6 Discussion
5 Design of a Hybrid Map
5.1 Mapdesign
5.1.1 Scenario
5.1.2 Domainparameters
5.1.3 Decidingthestructure
5.1.4 Deciding the co-operations
5.2 Thefinalmap
5.2.1 AlternativeI, No localizationco-operation
5.2.2 AlternativeII, localization injections
5.2.3 AlternativeIII, localization synergies
5.3 Buildingthehybridmap
5.3.1 Overview
5.3.2 Preprocessing
5.3.3 BuildingtheT-component
5.3.4 BuildingtheM-components
5.3.5 Addinglinks
5.3.6 Postprocessing
5.4 Localization
5.4.1 Overview
5.4.2 LocalizationintheT-component
5.4.3 LocalizationintheM-component
5.4.4 Localizationinthehybridmap
5.5 Summary description of the methods
5.5.1 Mapbuilding
5.5.2 Localization
5.6 Discussion
6 Enhancement of an Existing Hybrid Map
6.1 Theexistinghybridmap
6.1.1 Mapbuilding
6.1.2 Localization
6.1.3 Pathplanning
Author: Buschka, Pär
Source: Orebro University
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