Author
Listed:
- Ketao Zhang
(Imperial College London
Queen Mary University of London)
- Pisak Chermprayong
(Imperial College London)
- Feng Xiao
(Imperial College London)
- Dimos Tzoumanikas
(Imperial College London)
- Barrie Dams
(University of Bath)
- Sebastian Kay
(University College London)
- Basaran Bahadir Kocer
(Imperial College London)
- Alec Burns
(University College London)
- Lachlan Orr
(Imperial College London
Swiss Federal Laboratories for Materials Science and Technology (Empa))
- Talib Alhinai
(Imperial College London)
- Christopher Choi
(Imperial College London)
- Durgesh Dattatray Darekar
(University College London)
- Wenbin Li
(Imperial College London)
- Steven Hirschmann
(University College London)
- Valentina Soana
(University College London)
- Shamsiah Awang Ngah
(University of Bath)
- Clément Grillot
(Imperial College London
Swiss Federal Laboratories for Materials Science and Technology (Empa))
- Sina Sareh
(Imperial College London)
- Ashutosh Choubey
(Imperial College London)
- Laura Margheri
(Imperial College London)
- Vijay M. Pawar
(University College London)
- Richard J. Ball
(University of Bath)
- Chris Williams
(University of Bath)
- Paul Shepherd
(University of Bath)
- Stefan Leutenegger
(Imperial College London
Technical University of Munich)
- Robert Stuart-Smith
(University College London
University of Pennsylvania)
- Mirko Kovac
(Imperial College London
Swiss Federal Laboratories for Materials Science and Technology (Empa))
Abstract
Additive manufacturing methods1–4 using static and mobile robots are being developed for both on-site construction5–8 and off-site prefabrication9,10. Here we introduce a method of additive manufacturing, referred to as aerial additive manufacturing (Aerial-AM), that utilizes a team of aerial robots inspired by natural builders11 such as wasps who use collective building methods12,13. We present a scalable multi-robot three-dimensional (3D) printing and path-planning framework that enables robot tasks and population size to be adapted to variations in print geometry throughout a building mission. The multi-robot manufacturing framework allows for autonomous three-dimensional printing under human supervision, real-time assessment of printed geometry and robot behavioural adaptation. To validate autonomous Aerial-AM based on the framework, we develop BuilDrones for depositing materials during flight and ScanDrones for measuring the print quality, and integrate a generic real-time model-predictive-control scheme with the Aerial-AM robots. In addition, we integrate a dynamically self-aligning delta manipulator with the BuilDrone to further improve the manufacturing accuracy to five millimetres for printing geometry with precise trajectory requirements, and develop four cementitious–polymeric composite mixtures suitable for continuous material deposition. We demonstrate proof-of-concept prints including a cylinder 2.05 metres high consisting of 72 layers of a rapid-curing insulation foam material and a cylinder 0.18 metres high consisting of 28 layers of structural pseudoplastic cementitious material, a light-trail virtual print of a dome-like geometry, and multi-robot simulations. Aerial-AM allows manufacturing in-flight and offers future possibilities for building in unbounded, at-height or hard-to-access locations.
Suggested Citation
Ketao Zhang & Pisak Chermprayong & Feng Xiao & Dimos Tzoumanikas & Barrie Dams & Sebastian Kay & Basaran Bahadir Kocer & Alec Burns & Lachlan Orr & Talib Alhinai & Christopher Choi & Durgesh Dattatray, 2022.
"Aerial additive manufacturing with multiple autonomous robots,"
Nature, Nature, vol. 609(7928), pages 709-717, September.
Handle:
RePEc:nat:nature:v:609:y:2022:i:7928:d:10.1038_s41586-022-04988-4
DOI: 10.1038/s41586-022-04988-4
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Citations
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Cited by:
- Sunanda Rani & Dong Jining & Khadija Shoukat & Muhammad Usman Shoukat & Saqib Ali Nawaz, 2024.
"A Human–Machine Interaction Mechanism: Additive Manufacturing for Industry 5.0—Design and Management,"
Sustainability, MDPI, vol. 16(10), pages 1-24, May.
- Arjun Prihar & Shashank Gupta & Hadi S. Esmaeeli & Reza Moini, 2024.
"Tough double-bouligand architected concrete enabled by robotic additive manufacturing,"
Nature Communications, Nature, vol. 15(1), pages 1-11, December.
- Huawei Qu & Chongjian Gao & Kaizheng Liu & Hongya Fu & Zhiyuan Liu & Paul H. J. Kouwer & Zhenyu Han & Changshun Ruan, 2024.
"Gradient matters via filament diameter-adjustable 3D printing,"
Nature Communications, Nature, vol. 15(1), pages 1-13, December.
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