Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats

Giuseppe Calabrese; Arwin Hidding; Henriette Bier; Casper van Engelenburg; Seyran Khademi; Atousa Aslaminezhad

doi:10.1007/978-3-031-66431-1_23

Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats

Giuseppe Calabrese^*, Arwin Hidding, Henriette Bier, Casper van Engelenburg, Seyran Khademi, Atousa Aslaminezhad

^*Corresponding author for this work

Building Knowledge

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

This paper addresses the complexities inherent in constructing sustainable extraterrestrial habitats within lava tubes that are envisioned as promising locations for human habitation and scientific inquiry. These environments are characterized by various challenges, which are addressed in this case by integrating computer vision (CV) techniques and 3D printing in-situ. The CV component generates a detailed depth map from synthetic imagery to combine this depth map with an adaptive 3D printing process, which is proposed to ensure level surfaces at various depths, facilitating precise foundation and habitat placement within the demanding context of lava tubes. Significantly, synthetic imagery is employed due to the absence of real lava tube photos at this early stage of the current exploration. The focal point lies in utilizing advanced deep learning (DL) algorithms and convolutional neural networks (CNN) to generate depth maps for extra/-terrestrial environments. This research represents a platform for further knowledge development in the fields of CV and its application to 3D printing in-situ, hence opening new avenues for sustainable extraterrestrial habitats.

Original language	English
Title of host publication	Intelligent Systems and Applications
Subtitle of host publication	Proceedings of the 2024 Intelligent Systems Conference IntelliSys
Editors	Kohei Arai
Place of Publication	Cham
Publisher	Springer
Pages	349-360
Number of pages	12
Volume	3
ISBN (Electronic)	978-3-031-66431-1
ISBN (Print)	978-3-031-66430-4
DOIs	https://doi.org/10.1007/978-3-031-66431-1_23
Publication status	Published - 2024
Event	Intelligent Systems Conference 2024 - Van der Valk Hotel, Amsterdam, Netherlands Duration: 5 Sept 2024 → 6 Sept 2024 https://saiconference.com/IntelliSys

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1067 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	Intelligent Systems Conference 2024
Abbreviated title	IntelliSys 2024
Country/Territory	Netherlands
City	Amsterdam
Period	5/09/24 → 6/09/24
Internet address	https://saiconference.com/IntelliSys

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

3D printing
Adaptive filling
Computer vision
Depth map
Habitability
Lava tube habitats
Real-time mapping
Robotic construction
Surface irregularities

Access to Document

10.1007/978-3-031-66431-1_23

Cite this

Calabrese, G., Hidding, A., Bier, H., van Engelenburg, C., Khademi, S., & Aslaminezhad, A. (2024). Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats. In K. Arai (Ed.), Intelligent Systems and Applications: Proceedings of the 2024 Intelligent Systems Conference IntelliSys (Vol. 3, pp. 349-360). (Lecture Notes in Networks and Systems; Vol. 1067 LNNS). Springer. https://doi.org/10.1007/978-3-031-66431-1_23

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abstract = "This paper addresses the complexities inherent in constructing sustainable extraterrestrial habitats within lava tubes that are envisioned as promising locations for human habitation and scientific inquiry. These environments are characterized by various challenges, which are addressed in this case by integrating computer vision (CV) techniques and 3D printing in-situ. The CV component generates a detailed depth map from synthetic imagery to combine this depth map with an adaptive 3D printing process, which is proposed to ensure level surfaces at various depths, facilitating precise foundation and habitat placement within the demanding context of lava tubes. Significantly, synthetic imagery is employed due to the absence of real lava tube photos at this early stage of the current exploration. The focal point lies in utilizing advanced deep learning (DL) algorithms and convolutional neural networks (CNN) to generate depth maps for extra/-terrestrial environments. This research represents a platform for further knowledge development in the fields of CV and its application to 3D printing in-situ, hence opening new avenues for sustainable extraterrestrial habitats.",

keywords = "3D printing, Adaptive filling, Computer vision, Depth map, Habitability, Lava tube habitats, Real-time mapping, Robotic construction, Surface irregularities",

author = "Giuseppe Calabrese and Arwin Hidding and Henriette Bier and {van Engelenburg}, Casper and Seyran Khademi and Atousa Aslaminezhad",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; Intelligent Systems Conference 2024, IntelliSys 2024 ; Conference date: 05-09-2024 Through 06-09-2024",

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Calabrese, G, Hidding, A , Bier, H , van Engelenburg, C , Khademi, S & Aslaminezhad, A 2024, Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats. in K Arai (ed.), Intelligent Systems and Applications: Proceedings of the 2024 Intelligent Systems Conference IntelliSys. vol. 3, Lecture Notes in Networks and Systems, vol. 1067 LNNS, Springer, Cham, pp. 349-360, Intelligent Systems Conference 2024, Amsterdam, Netherlands, 5/09/24. https://doi.org/10.1007/978-3-031-66431-1_23

Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats. / Calabrese, Giuseppe; Hidding, Arwin ; Bier, Henriette et al.
Intelligent Systems and Applications: Proceedings of the 2024 Intelligent Systems Conference IntelliSys. ed. / Kohei Arai. Vol. 3 Cham: Springer, 2024. p. 349-360 (Lecture Notes in Networks and Systems; Vol. 1067 LNNS).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Hidding, Arwin

AU - Bier, Henriette

AU - van Engelenburg, Casper

AU - Khademi, Seyran

AU - Aslaminezhad, Atousa

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2024

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N2 - This paper addresses the complexities inherent in constructing sustainable extraterrestrial habitats within lava tubes that are envisioned as promising locations for human habitation and scientific inquiry. These environments are characterized by various challenges, which are addressed in this case by integrating computer vision (CV) techniques and 3D printing in-situ. The CV component generates a detailed depth map from synthetic imagery to combine this depth map with an adaptive 3D printing process, which is proposed to ensure level surfaces at various depths, facilitating precise foundation and habitat placement within the demanding context of lava tubes. Significantly, synthetic imagery is employed due to the absence of real lava tube photos at this early stage of the current exploration. The focal point lies in utilizing advanced deep learning (DL) algorithms and convolutional neural networks (CNN) to generate depth maps for extra/-terrestrial environments. This research represents a platform for further knowledge development in the fields of CV and its application to 3D printing in-situ, hence opening new avenues for sustainable extraterrestrial habitats.

AB - This paper addresses the complexities inherent in constructing sustainable extraterrestrial habitats within lava tubes that are envisioned as promising locations for human habitation and scientific inquiry. These environments are characterized by various challenges, which are addressed in this case by integrating computer vision (CV) techniques and 3D printing in-situ. The CV component generates a detailed depth map from synthetic imagery to combine this depth map with an adaptive 3D printing process, which is proposed to ensure level surfaces at various depths, facilitating precise foundation and habitat placement within the demanding context of lava tubes. Significantly, synthetic imagery is employed due to the absence of real lava tube photos at this early stage of the current exploration. The focal point lies in utilizing advanced deep learning (DL) algorithms and convolutional neural networks (CNN) to generate depth maps for extra/-terrestrial environments. This research represents a platform for further knowledge development in the fields of CV and its application to 3D printing in-situ, hence opening new avenues for sustainable extraterrestrial habitats.

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KW - Habitability

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KW - Real-time mapping

KW - Robotic construction

KW - Surface irregularities

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Calabrese G, Hidding A , Bier H , van Engelenburg C , Khademi S, Aslaminezhad A. Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats. In Arai K, editor, Intelligent Systems and Applications: Proceedings of the 2024 Intelligent Systems Conference IntelliSys. Vol. 3. Cham: Springer. 2024. p. 349-360. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-66431-1_23

Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats

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Keywords

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