Skip to main content

Research Repository

See what's under the surface

Advanced Search

Toward controllable morphogenesis in large robot swarms

Carrillo-Zapata, Daniel; Sharpe, James; Winfield, Alan Frank T.; Giuggioli, Luca; Hauert, Sabine

Authors

Daniel Carrillo-Zapata

James Sharpe

Luca Giuggioli

Sabine Hauert



Abstract

Morphogenetic engineering aims to achieve functional, self-organized but controllable structures in human-designed systems. Controlling the structures is crucial if they are to be used for real-world applications. Building on previous work on morphogenesis, in this letter, we present a new algorithm, with controllability at its core, for large swarms of simple robots where morphogenesis occurs without self-localization, predefined map, or preprogrammed robots. Controllability is achieved through three parameters that influence the morphogenesis process and create a rich morphospace of quantitatively different shapes. The algorithm was tested in over 2000 simulations and three times on real swarms of 300 kilobots. Swarms were able to grow shapes using only local communication, and regrow missing parts when manually damaged. Extra simulations also demonstrated swarms adapting to an obstacle in the environment by getting around it. Results were compared with our previous work on morphogenesis to show how controllability allowed richer shapes. This letter represents a step into designing a controllable morphogenesis algorithm toward more functional swarms for real-world applications.

Journal Article Type Article
Publication Date Oct 1, 2019
Journal IEEE Robotics and Automation Letters
Print ISSN 2377-3766
Electronic ISSN 2377-3766
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 4
Issue 4
Pages 3386-3393
APA6 Citation Hauert, S., Carrillo-Zapata, D., Sharpe, J., Winfield, A. F. T., & Giuggioli, L. (2019). Toward controllable morphogenesis in large robot swarms. IEEE Robotics and Automation Letters, 4(4), 3386-3393. https://doi.org/10.1109/LRA.2019.2926961
DOI https://doi.org/10.1109/LRA.2019.2926961
Keywords Artificial Intelligence; Computer Vision and Pattern Recognition; Computer Science Applications
Publisher URL https://doi.org/10.1109/lra.2019.2926961
;