Watch a swarm of 1000 mini-robots assemble into shapes - tech - 14 August 2014 - New Scientist

Watch a swarm of 1000 mini-robots assemble into shapes - tech - 14 August 2014 - New Scientist: To do the assembling, the desired end shape is first transmitted to all the robots and then four stationary robots are positioned by hand to mark the shape's starting point. Next, some of the robots start to shuffle until they reach a place-holding robot and then fan out from that point to stop in the right place. Each robot can only communicate with the others nearby. Successive robots build up the shape by stopping near the robots already in place. It can take about 12 hours for 1000 robots to fill in a pattern.

How bird flocks are like liquid helium | Science/AAAS | News

How bird flocks are like liquid helium | Science/AAAS | News: Using tracking software on the recorded video, the team could pinpoint when and where individuals decide to turn, information that enabled them to follow how the decision sweeps through the flock. The tracking data showed that the message to turn started from a handful of birds and swept through the flock at a constant speed between 20 and 40 meters per second. That means that for a group of 400 birds, it takes just a little more than a half-second for the whole flock to turn...

The team proposes that instead of copying the direction in which a neighbor flies, a bird copies how sharply a neighbor turns...

Interestingly, Cavagna adds, the new model is mathematically identical to the equations that describe superfluid helium.

Fire ants writhe to make unsinkable rafts - life - 26 November 2013 - New Scientist

Fire ants writhe to make unsinkable rafts - life - 26 November 2013 - New Scientist: A raft of live fire ants, on the other hand, resists and dissipates external forces equally well on all scales. The ants can act as tiny, resistive springs by flexing and extending their legs, and they break and reform connections with their neighbours to create a flow around external forces, like being prodded with sticks. Importantly, rafts of live ants are significantly more elastic than those made of flash-frozen dead ants.

Video: Robotic Ants Solve Riddles Without Math

Video: Robotic Ants Solve Riddles Without Math: Researchers used tiny, cube-shaped robots that were powered by watch motors and ran on dime-sized wheels. They gave the machines three rules: to walk randomly in a given direction, to turn away from obstacles they bump into, and to follow a trail of light left by other robots (as seen in the video)—similar to the way real ants use their antennae to sense chemicals left behind by other ants. These simple tenets were enough to allow the robots to copy ants' ability to find the shortest path home.

Shhh, the Ants Are Talking

Shhh, the Ants Are Talking: To see how the ants used this acoustic communication, the team removed the abdominal spike from some of the mature pupae in a nest. The researchers then disturbed the nest, spilling out larvae, pupae, and adult workers into an experimental arena. Normally, the adult ants rescue their nestmates in a specific order: mature pupae, immature pupae, and, finally, the larvae. In the experiments by Schönrogge and colleagues, the adult workers indeed rescued the unmuted mature pupae first. However, the adult ants completely ignored the muted ants. It was as if the mute mature pupae simply didn't exist.

"The sounds they make rescue them by signaling their social status," Schönrogge says.

‘Green Brain’ project to create an autonomous flying robot with a honey bee brain - News releases - News - The University of Sheffield

‘Green Brain’ project to create an autonomous flying robot with a honey bee brain - News releases - News - The University of Sheffield: The team will build models of the systems in the brain that govern a honey bee's vision and sense of smell. Using this information, the researchers aim to create the first flying robot able to sense and act as autonomously as a bee, rather than just carry out a pre-programmed set of instructions.

Flying Math: Bees Solve Traveling Salesman Problem

Flying Math: Bees Solve Traveling Salesman Problem: After trying about “20 of the 120 possible routes, the bees were able to select the most efficient path to visit the flowers,” Lihoreau says. “They did not need to compute all the possibilities.” A naïve bee traveled almost 2,000 meters on its first foraging bout among the pentagonal array; by her final trip, she’d reduced that distance to a mere 458 meters.

Stanford researchers discover the 'anternet'

Stanford researchers discover the 'anternet':  ...A forager won't return to the nest until it finds food. If seeds are plentiful, foragers return faster, and more ants leave the nest to forage. If, however, ants begin returning empty handed, the search is slowed, and perhaps called off.

Prabhakar wrote an ant algorithm to predict foraging behavior depending on the amount of food – i.e., bandwidth – available. Gordon's experiments manipulate the rate of forager return. Working with Stanford student Katie Dektar, they found that the TCP-influenced algorithm almost exactly matched the ant behavior found in Gordon's experiments...

They also found that the ants followed two other phases of TCP. One phase is known as slow start, which describes how a source sends out a large wave of packets at the beginning of a transmission to gauge bandwidth; similarly, when the harvester ants begin foraging, they send out foragers to scope out food availability before scaling up or down the rate of outgoing foragers.

Another protocol, called time-out, occurs when a data transfer link breaks or is disrupted, and the source stops sending packets. Similarly, when foragers are prevented from returning to the nest for more than 20 minutes, no more foragers leave the nest.

Humanoid Robot Swarm Synchronized Using Quorum Sensing� - Technology Review

Humanoid Robot Swarm Synchronized Using Quorum Sensing� - Technology Review: Now Bechon and Slotine say a similar approach provides a robust way to synchronise humanoid robots. The ideal approach  to synchronisation is for each robot to have access to every other robot's position. Instead, the quorum sensing approach gives, each robot  access to a global variable such as the average position or average clock time. Each robot can also change this variable because it contributes to the average.

The idea is that if each robot attempts to synchronise with this global average, the swarm as whole should keep good time.

Computers powered by swarms of crabs

Computers powered by swarms of crabs: Yukio-Pegio Gunji of Kobe University in Japan and colleagues realised that when two swarms of crabs collide, they merge and continue in a direction that is the sum of their velocities. This behaviour means the researchers could adapt a previous model of unconventional computing, based on colliding billiard balls, to work with swarms of crabs, with 0s and 1s represented by the absence or presence of a swarm.

They first tried the idea with simulated crab swarms. The OR gate, which simply combines one or two crab swarms into one, worked every time, but the more complicated AND gate, which involves the combined swarm heading down one of three paths, was less reliable.

Using ant-based swarm intelligence for materials handling

Using ant-based swarm intelligence for materials handling: The scientists have assembled a testing facility with a swarm of 50 autonomous devices. “In the future, transport systems should be able to perform all of these tasks autonomously, from removal from the shelf to delivery to a picking station...

“We rely on agent-based software and use ant-like algorithms based on the work of Marco Dorigo. These are methods of combinational optimization based on the behavior of real ants in their search for food.“

How to create an ant spiral of death

How to create an ant spiral of death: One can create an ant mill just by diverting a few ants and placing them into an enclosed space where they are likely to loop back on their own scent. Biologist and photographer Alex Wild remembers ants getting trapped in a vortex simply by walking onto dinner plates in his kitchen and exploring the plate until they found their own scent.

Ants can learn vibrational and magnetic landmarks

Ants can learn vibrational and magnetic landmarks: Trained ants of the species Cataglyphis noda pinpointed their nest without any problem if a battery-powered vibrational device was buried next to the nest entrance so that the ants could localize their nest by using the vibrational landmark. To exclude electromagnetic effects of the device, experiments were performed using the vibrational device without contact to the ground. The result: The ants behaved like their untrained conspecifics. They wandered around aimlessly. If two strong neodym magnets generating a magnetic field of about 21 millitesla (the earth’s magnetic field was, for comparison, only 0.041 millitesla) were placed above ground next to the nest, trained ants again found their home without any problems.

Bee swarms behave just like neurons in the human brain

Bee swarms behave just like neurons in the human brain: "It appears that the stop signals in bee swarms serve the same purpose as the inhibitory connections in the brains of monkeys deciding how to move their eyes in response to visual input. In one case we have bees and in the other we have neurons that suppress the activity levels of units – dancing bees or nerve centers – that are representing different alternatives. Bee behavior can shed some light on general issues of decision making..."

This phenomenon, known as cross inhibition, serves precisely the same function with bees that it does in nervous systems. It's a way of avoiding decision-making deadlock when presented with a set of equally viable alternatives.

Tiny Kilobots to go on sale

Tiny Kilobots to go on sale: Along with its lithium-ion battery and rigid legs, each Kilobot incorporates an LED bulb, two motors (which vibrate the legs), a wide-angle infrared transceiver, and a microcontroller. An unlimited number of the little guys can be programmed via a computer-linked overhead infrared controller in under 40 seconds, and each have the ability to act autonomously, based on the parameters of that programming.

One Per Cent: Flying, flocking, and squirming robots at IROS

One Per Cent: Flying, flocking, and squirming robots at IROS: When the planes were allowed to make tight turns and maintain communication links over distances of hundreds of meters, they were able to autonomously form a coherent flock, circling above a target. When tight-turning was disabled, the planes were not able to organize themselves. And when tight-turning was re-enabled, but communication was limited to short ranges, the flocks split into multiple unstable sub-groups.

Kilobots bring us one step closer to a robot swarm

Kilobots bring us one step closer to a robot swarm: These small and simple robots are about the size of a US quarter that moves around on a set of vibrating legs. These small robots are able to communicate with each other by blinking lights mounted on their cases. While each individual unit may not seem that advanced or impressive the real impact is what happens when the robots work as a system.

Can bees color maps better than ants?

Can bees color maps better than ants?: A mathematical model of this system known as "Marriage in honey bees optimization" (MBO) was developed in the early 2000s to help solve so-called combinatorial optimization problems, such as the traveling salesman problem of logistics and the minimum spanning tree problem for reducing the amount of resources and materials used in engineering, such as laying pipelines or fiber optic to fully connect a network. It mimics the genetic selection process in bees in which the queen mates with many drones and then randomly fertilizes her eggs with sperm from each male to generate a mixed pool of offspring among which only the fittest will thrive.
Bessedik and colleagues reasoned that that fact that MBO uses self-organization, unlike ant colony models, would allow it to solve one of the most complex problems - map coloring.

Next generation of algorithms inspired by problem-solving ants

Next generation of algorithms inspired by problem-solving ants: "Even simple mass-recruiting ants have much more complex and labile problem solving skills than we ever thought. Contrary to previous belief, the pheromone system of ants does not mean they get stuck in a particular path and can't adapt. Having at least two separate pheromones gives them much more flexibility and helps them to find good solutions in a changing environment. Discovering how ants are able to solve dynamic problems can provide new inspiration for optimisation algorithms, which in turn can lead to better problem-solving software and hence more efficiency for human industries."

Rooting For Swarm Intelligence In Plants - Science News

Rooting For Swarm Intelligence In Plants - Science News: Three plant scientists now propose that roots growing this way and that in their dark and dangerous soil world may fit a definition for what’s called swarm intelligence. Each tip in a root system acquires information at least partly independently, says plant cell biologist František Baluška of the University of Bonn in Germany. If that information gets processed in interactions with other roots and the whole tangle then solves what might be considered a cognitive problem in a way that a lone root couldn’t, he says, then that would be swarm intelligence.