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Cooperative Vision for Swarm Navigation

Zhu, Chen (2019) Cooperative Vision for Swarm Navigation. Dissertation, Technische Universität München.

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Abstract

The efficiency of Mars exploration can be improved by using a swarm of small independent rovers. By using cameras, a rover can estimate its egomotion and build a map of the environment simultaneously. However, the error accumulation in the tracking strongly limits the accuracy of the positioning and the mapping, except if loop closures can be established in the exploring trajectory. We solved the challenges posed by the use of monocular cameras on small rovers and the lack of loop closures by a sensor fusion method based on images and ranges to a single anchor point, e.g., the landing site. Additionally, ranges can be determined between each pair of rovers in a swarm. We proposed a relative pose and scale estimation with low communication requirement and a swarm navigation solution based on that.

Item URL in elib:https://elib.dlr.de/133488/
Document Type:Thesis (Dissertation)
Title:Cooperative Vision for Swarm Navigation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Zhu, ChenUNSPECIFIEDhttps://orcid.org/0000-0002-4320-4826UNSPECIFIED
Date:2019
Refereed publication:Yes
Open Access:Yes
Number of Pages:123
Status:In Press
Keywords:Sensor Fusion; Cooperative Positioning; SLAM; Swarm Localization; Multi-agent Navigation; Low Communication Requirement; Relative Pose; Monocular Camera Scale; Error Mitigation; Field of View Detection; Clustering; Grouping
Institution:Technische Universität München
Department:Department of Electrical and Computer Engineering
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Communication and Navigation
DLR - Research area:Raumfahrt
DLR - Program:R KN - Kommunikation und Navigation
DLR - Research theme (Project):R - Project Navigation 4.0 (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation
Deposited By: Zhu, Chen
Deposited On:14 Jan 2020 14:10
Last Modified:14 Jan 2020 14:10

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