In physics, particles are small localized objects with physical characteristics like mass or volume. From those humble ingredients, our virtually limitless universe is built.
The concept, presented in an article in the journal Nature, is that a cooperative system of small robots might be able to do complex work, even if no single component in the system is computationally complex. It's the theory at the heart of a branch of automation called swarm robotics. Though still largely the purview of research universities, sectors like defense, agriculture, and infrastructure inspection will one day rely on swarms of small, cheap robots to operate in environments and perform tasks that individual robots never could.
The particle robot researchers were inspired by the principles of attraction and repulsion. Each particle is disc-shaped and loosely connected to other particles around it via magnets. A single particle can push away surrounding particles or pull them closer, and that's it.
But that simple action belies the incredible diversity of tasks that the cluster can perform as a whole. Like a team of ants, the particle robots can pick up and transport objects in their way. They can also seamlessly navigate around objects the way water flows around obstacles in a rushing river -- something a single large robot can't do.
"We have small robot cells that are not so capable as individuals but can accomplish a lot as a group," says Daniela Rus, director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science. "The robot by itself is static, but when it connects with other robot particles, all of a sudden the robot collective can explore the world and control more complex actions. With these 'universal cells,' the robot particles can achieve different shapes, global transformation, global motion, global behavior, and, as we have shown in our experiments, follow gradients of light. This is very powerful."
In the Nature article, the researchers presented results from simulated scenarios that employed up to 100,000 particles. The team also used a smaller set of about a dozen real life particles to demonstrate the concept.
Each particle's cylindrical base houses a battery and small motor, along with a light sensor and microcontroller. The particles don't directly communicate to one another, which is one of the system's advantages. New particles can be added to a system and other particles taken away without affecting the performance of surrounding particles.
The system works when individual particles within the collective are sent instructions for when to contract or expand. With the right sequence, the whole group begins to undulate and move. In this case, the light sensors on the tiny robots moved the collective toward a light source. By comparing the intensity of light perceived by particles closer to the light source and farther away from the light source, the cluster of particles is able to get an accurate fix and the system begins to expand and contract.
"This creates a mechanical expansion-contraction wave, a coordinated pushing and dragging motion, that moves a big cluster toward or away from environmental stimuli," Li says. The key component, Li adds, is the precise timing from a shared synchronized clock among the particles that enables movement as efficiently as possible: "If you mess up the synchronized clock, the system will work less efficiently."
While there are no direct applications to the technology yet, possible use cases include construction, materials handling, and inspection. The next step in the project is to miniaturize the particles so that hundreds of thousands or even millions can be deployed together.