In January 2020, a lab on the second floor of Northwestern University was filled with the gentle clatter of three robots around each other. The trio found themselves in a small circle banging against each other, although the little robots weren’t the rock ’em, sock’ em variant. These were smart, active particles – ‘smarticles’ – equipped with two paddle-like flaps for arms, spanning less than 6 inches from end to end, and covered with tags to track their position and orientation. The little buggers went through the unpredictable and unflattering moves of disorder until at times they gracefully transitioned into recognizable coordinated movements: a dance.
The smarticles were not programmed with specific instructions, nor were they told to be nice to each other. The bots were prescribed drives or movement patterns for their flaps, which surprisingly gave way to dance-like sequences. The patterns and the physics underlying them are described in a paper published today in the journal Science. The research was funded by the National Science Foundation, the James S. McDonnell Foundation, and the Army Research Office.
When the smarticles were out of sync, there was a “chaos of chatter and collisions around the ring, which was fascinating to watch, but certainly not orderly,” said Thomas Berrueta, a roboticist at Northwestern University and co-author of the paper, in a video conversation. But in collaboration with Pavel Chvykov, a physicist at the Massachusetts Institute of Technology, and Jeremy England, a physicist who previously worked at MIT and now Georgia Tech, the research team programmed the smarticles to run the driving pattern simultaneously.
“Suddenly they did this beautiful rotating procession,” BerrEUsaid ta. “As someone who had smarticles and hadn’t done so before, it felt like [Chvykov] came and did a magic trick with my own tools. “
Order is in many places in the natural world – for example, birds flow together or water crystallizes into ice – but predict that it is a beast in a non-equilibrium situation, where there are external forces at play. (And to be clear, the world of non-equilibrium is the big, broad one outside your window – a huge realm compared to the achievements attainable in a predictable lab environment). In the 1870s, a Swiss physicist named Charles Soret conducted experiments that showed how a saline solution in a tube exposed to heat on one side would cause greater order of the particles on the colder side. Because molecules move more vigorously on the hot side of the tube, more of them end up in the cooler side; the cooler molecules, with their graceful movements, do not travel as far as fast. This means that the particles will accumulate on the cool side of the tube. The principle, called thermophoresis, modeled for England and Chvykov on seeing the promise of objects in so-called low-rattling states.
G / O Media can receive a commission
Rattling is when matter uses the energy flowing into it to move. According to England, the greater the chatter, the more random or spastic the movement, and the lower the chatter, the more deliberate or incremental the movement. Both can also be true.
“The idea is that if your matter and energy source allow for the possibility of a low-rattling state, the system will randomly rearrange until it finds that state and then gets stuck,” England said in a statement from Georgia Tech. “If you deliver energy through forces with a certain pattern, it means that the selected state will discover a way for matter to move that exactly matches that pattern.”
In this case, the pattern was the prescribed flapping motion, and the matter that matched that pattern was the bots that beat each other in rotations and translations around the ring that enclosed them. These little flappers were a great testing ground for the idea that low-rattling states would create stable, self-organized dances. Unlike other muses, the smarticles did not have a molecular source of self-ordering behavior (such as how water turns into ice at a certain temperature). The other variables at play in crystals give way to alternative explanations for ordering, obscuring the non-rattling idea the research team wanted to test.
Since the smarticles only move through contact with each other (they can’t take steps or roll around), there are also fewer unknowns as to where the objects’ mobility comes from, England said, a problem you’d have if all smarticles had small motors that propelled them forward in their dance. If the robots can only move by pushing each other around, you know that the movement you see is the result of collective behavior.
“This paper suggests a general principle that complex systems are naturally attracted to behaviors that minimize ‘rattling,'” Arvind Murugan, a University of Chicago physicist who is not affiliated with the recent paper, said in an email. “The current application to robots shows that the idea survives the first contact with reality. But future work will have to show whether this principle is a good approximation for other complex systems – from molecules to cells to human crowds at a rock concert (after COVID, of course). “
Murugan adds that the principle is not always true, “and is only approximately true if it is true.” But the idea as implemented by the bots shows that given that driving force, they will dance in a low rattling state.
“Once you have a bunch of robots interacting with each other and with people … the idea in this article is that they will be synchronized every now and then. And when they sync up, there will be emergent behavior, but you don’t necessarily know what that emerging behavior is going to be, ”said Todd Murphey, a roboticist at Northwestern University and co-author of the paper. “If we are not willing to talk about emergent behavior as a fundamental outcome that we should always expect for a sufficiently complex system that is not balanced, then we will miss things that can reasonably happen.”
The implications of the robot movements go beyond refining your DDR technique. While there were only three small structures in rotation, the smarticles exhibited a principle that could be applied to self-driving cars or even the people in them.