title: Collective navigation of cargo-carrying swarms.
abstract: Much effort has been devoted to the study of swarming and collective navigation of micro-organisms, insects, fish, birds and other organisms, as well as multi-agent simulations and to the study of real robots. It is well known that insect swarms can carry cargo. The studies here are motivated by a less well-known phenomenon: cargo transport by bacteria swarms. We begin with a concise review of how bacteria swarms carry natural, micrometre-scale objects larger than the bacteria (e.g. fungal spores) as well as man-made beads and capsules (for drug delivery). A comparison of the trajectories of virtual beads in simulations (using different putative coupling between the virtual beads and the bacteria) with the observed trajectories of transported fungal spores implies the existence of adaptable coupling. Motivated by these observations, we devised new, multi-agent-based studies of cargo transport by agent swarms. As a first step, we extended previous modelling of collective navigation of simple bacteria-inspired agents in complex terrain, using three putative models of agent-cargo coupling. We found that cargo-carrying swarms can navigate efficiently in a complex landscape. We further investigated how the stability, elasticity and other features of agent-cargo bonds influence the collective motion and the transport of the cargo, and found sharp phase shifts and dual successful strategies for cargo delivery. Further understanding of such mechanisms may provide valuable clues to understand cargo-transport by smart swarms of other organisms as well as by man-made swarming robots.
authors: School of Physics and Astronomy , Tel Aviv University , Tel Aviv 69978 , Israel ; The Blavatnik School of Computer Science , Tel Aviv University , Tel Aviv 69978 , Israel.
authors: Adi
authors: A
authors: Shklarsh
authors: Alin
authors: A
authors: Finkelshtein
authors: Gil
authors: G
authors: Ariel
authors: Oren
authors: O
authors: Kalisman
authors: Colin
authors: C
authors: Ingham
authors: Eshel
authors: E
authors: Ben-Jacob
keywords: agent-based modelling; bacteria cargo transport; bacteria swarming; collective behaviour; social behaviour of bacteria; swarming intelligence