Aerial additive manufacturing with multiple autonomous robots

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 Darekar, Wenbin Li, Steven Hirschmann, Valentina Soana, Shamsiah Awang Ngah, Clément Grillot, Sina Sareh, Ashutosh Choubey, Laura Margheri, Vijay M. Pawar, Richard J. Ball, Chris Williams, Paul Shepherd, Stefan Leutenegger, Robert Stuart-Smith and Mirko Kovac ()
Additional contact information
Ketao Zhang: Imperial College 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
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
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
Robert Stuart-Smith: University College London
Mirko Kovac: Imperial College London

Nature, 2022, vol. 609, issue 7928, 709-717

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41586-022-04988-4

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