Ant colonies could inspire better network algorithms and robot swarms


Colonies of ants base decisions like where to establish a nest based on their population density. Scientists theorize that ants can estimate how many of their kind are around by randomly exploring the area and bumping into other ants. New research from MIT computer scientists not only supports this theory but could also be used to analyze social networks, improve robot swarms, and yield improve algorithms for networked communications in distributed computing applications. From MIT News:

“It’s intuitive that if a bunch of people are randomly walking around an area, the number of times they bump into each other will be a surrogate of the population density,” says Cameron Musco, an MIT graduate student in electrical engineering and computer science and a co-author on the new paper. “What we’re doing is giving a rigorous analysis behind that intuition, and also saying that the estimate is a very good estimate, rather than some coarse estimate. As a function of time, it gets more and more accurate, and it goes nearly as fast as you would expect you could ever do.”

Musco and his coauthors — his advisor, NEC Professor of Software Science and Engineering Nancy Lynch, and Hsin-Hao Su, a postdoc in Lynch’s group — characterize an ant’s environment as a grid, with some number of other ants scattered randomly across it. The ant of interest — call it the explorer — starts at some cell of the grid and, with equal probability, moves to one of the adjacent cells. Then, with equal probability, it moves to one of the cells adjacent to that one, and so on.

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Self-assembling, multi-rotor drones

The Distributed Flight Array is an experimental project from ETH Zurich; it's a set of 3D-printed hexagonal rotors with magnets on their edges; they automatically join up with one another, sense and compute the aerodynamic properties of their current configuration, and cooperate to fly together.

The system is designed around a central propeller which provides thrust for the structure. Surrounding it are three omni-directional wheels that let the bots get into position with each other on the ground while magnets embedded in the frame provide a connection. A gyroscope provides positional information to an on-board microprocessor while an infrared sensor feeds information about altitude to the system. Pins allow the collected bots to communicate this real-time data between each other and adjust their individual thrusts to keep the combined unit stable. Despite the sensitive nature of the electronics, when a flight is over, the bots disengage midair and fall safely to the ground where the process can begin anew.

Individual units can only propel themselves spastically around a room, but when joined the DFA modules can create traditional quadcopters, more advanced decacopters, and their most impressive applications are atypical and asymmetrical arrays that defy traditional aeronautic aesthetics. These odd combos often produce interesting flight patterns — in one configuration where the bots are aligned linearly, the construct appears to flap as the opposite ends try to reach equilibrium.

...Next steps for the project will be removing the last vestiges of human control—currently a motion-capture system or an operator using a joystick has to provide a small amount of feedback to keep the system from drifting away.

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Chipping ants to understand colonies

University of Lausanne biologists chipped hundreds of ants and digitally tracked them to see how they form social groups and work collectively to get stuff done. Based on the data, they created heat maps and visualized the ants' trajectories. From Nature:

The biologists… have found that the workers fall into three social groups that perform different roles: nursing the queen and young; cleaning the colony; and foraging for food. The different groups move around different parts of the nest, and the insects tend to graduate from one group to another as they age, the researchers write in a paper published today in Science.

“The paper is a game-changer, in the size and detail of the data set that was collected,” says Anna Dornhaus, an entomologist at the University of Arizona in Tucson.

"Tracking whole colonies shows ants make career moves" (Thanks, Nic Weidinger!)

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