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Novel Technology for Creating Robot Formed of Loosely Coupled Components

For several decades, fans of science fiction have been enthralled by the concept of “gray goo,” a robot formed of billions of nanoparticles. However, a majority of the scientists have rejected it as merely a wild theory.

Particle robots are composed of loosely coupled components, or particles, that lack an individual identity or addressable position. They are capable of only a simple motion—expansion and contraction. However, when a group of particles is coordinated to move as a collective, interesting behavior is observed. Even in amorphous configurations, particle robots exploit statistical mechanics phenomena to produce locomotion. (Image credit: Columbia Engineering)

In general, existing robots are self-contained candidates formed of interdependent subcomponents, each with a particular function. In case one part fails, the robot stops working. Considering swarms of robots, each robot acts like a machine that functions independently.

In a new research reported in Nature on March 20th, 2019, scientists at Columbia Engineering and MIT Computer Science & Artificial Intelligence Lab (CSAIL) showed for the first time a technology to make a robot formed of several loosely coupled components, or “particles.” In contrast to modular or swarm robots, each component is simple and has no individual identity or address. In the system developed by the researchers, which they have named a “particle robot,” each particle has the potential to carry out only uniform volumetric oscillations (expanding and contracting to a certain extent), but cannot move independently.

The group, headed by Hod Lipson, professor of mechanical engineering at Columbia Engineering, and CSAIL Director Daniela Rus, found out that when thousands of these particles were grouped together in a “sticky” cluster and made to oscillate in response to a light source, the entire particle robot gradually started to move toward the light.

You can think of our new robot as the proverbial ‘Gray Goo’. Our robot has no single point of failure and no centralized control. It’s still fairly primitive, but now we know that this fundamental robot paradigm is actually possible. We think it may even explain how groups of cells can move together, even though individual cells cannot.

Hod Lipson, Professor of Mechanical Engineering, Columbia Engineering.

For over a hundred years, although scientists have been developing autonomous robots, these have been non-biological machines that lack the potential to grow, recover from damage, or heal. The focus of the Columbia Engineering/MIT group has been to create rugged, scalable robots with the ability to operate even if individual components fail.

We’ve been trying to fundamentally rethink our approach to robotics, to discover if there is a way to make robots differently,” stated Lipson, who directs the Creative Machines lab. “Not just make a robot look like a biological creature but actually construct it like a biological system, to create something that is vast in complexity and abilities yet composed of fundamentally simple parts.”

All creatures in nature are made of cells that combine in different ways to make organisms. In developing particle robots, the question we ask is, can we have robotic cells that can be composed in different ways to make different robots? The robot could have the best shape required by the task—a snake to crawl through a tunnel or a three-handed machine for a factory floor. We could even give these particle robots the ability to make themselves. Suppose, for example, that a robot needs a screw driver from the table—the screw driver is too far to reach. What if the robot could reshuffle its cells to grow an extra long arm? As its goals change, its body can change too.

Daniela Rus, Director, CSAIL

Rus is also the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT.

The group, in collaboration with Chuck Hoberman at Harvard’s Wyss Institute and other scientists at Cornell, employed several identical components, or particles, that could carry out a simple motion such as contraction and expansion. Through simulations, they showcased robots composed of 100,000 particles. They experimentally demonstrated a system formed of two dozen particles.

The particles closer to the light source experience brighter light and thus start their cycle earlier. That movement creates a sort of wave throughout the cluster, from the ones closer to the light to the ones further away, and that wave makes the entire cluster move towards the light. The movement toward light creates a global motion, even though the individual particles cannot move independently.

Shuguang Li, Study Co-First Author, Postdoc, CSAIL.

Li, who conducted the physical experiments, was a postdoctoral fellow in Lipson’s former lab at Cornell and is currently a postdoc with Rus at CSAIL.

They modeled this behavior in simulations and investigated object transport and obstacle avoidance at greater scales, with hundreds and thousands of particles. They could also show the resilience of the particle robot paradigm to individual failure as well as noisy components.

We found that our particle robots maintained approximately half of their fully functioning speed even when 20 percent of the particles are dead,” stated Richa Batra, co-first author of the paper and Lipson’s PhD student who headed the simulation studies.

The researchers have already started testing their system using a larger number of centimeter-scale particles. They are also investigating other forms of particle robots, like vibrating microspheres.

We think it will be possible one day to make these kinds of robots from millions of tiny particles, like microbeads that respond to sound or light or chemical gradient,” stated Lipson. “Such robots could be used to do things like clean up areas or explore unknown terrains/structures.”

Particle Robotics: Based on Statistical Mechanics of Loosely Coupled Components

This video provides an overview of the particle robotics concept, describing the capabilities and experimental results. (Video credit: Columbia Engineering)

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