Robust and Adaptive Robot Self-Assembly Based on Vascular Morphogenesis

Mohammad Divband Soorati, Javad Ghofrani, Payam Zahadat, Heiko Hamann


Self-assembly is the aggregation of simple parts into complex patterns as frequently observed in nature. Following this inspiration, creating programmable systems of self-assembly that achieve similar complexity and robustness with robots is challenging. As a role model we pick the growth of natural plants that adapts to environmental conditions and is robust enough to withstand disturbances such as changes due to dynamic environments and cut parts. We program a robot swarm to self-assemble into tree-like shapes and to adapt efficiently to the environment. Our approach is inspired by the vascular morphogenesis of plants, the patterned formation of vascular tissue to transport fluids and nutrients internally. The aggregated robots establish an internal network of resource sharing, allowing them to make rational decisions collectively about where to add and where to remove robots. As a result, the growth is adaptive to an environmental feature (here, light) and robust to changes in a dynamic environment. The robot swarm is able to self-repair by regrowing lost parts. We successfully validate and benchmark our approach in a number of robot swarm experiments showing adaptivity, robustness, and self-repair.
Original languageEnglish
Number of pages6
Publication statusPublished - 05.10.2018
Event2018 IEEE/RSJ International Conference on Intelligent Robots and Systems
- Madrid, Spain
Duration: 01.10.201805.10.2018


Conference2018 IEEE/RSJ International Conference on Intelligent Robots and Systems


Dive into the research topics of 'Robust and Adaptive Robot Self-Assembly Based on Vascular Morphogenesis'. Together they form a unique fingerprint.

Cite this