All posts by MIT News

Trees and other plants, from towering redwoods to diminutive daisies, are nature’s hydraulic pumps. They are constantly pulling water up from their roots to the topmost leaves, and pumping sugars produced by their leaves back down to the roots. This constant stream of nutrients is shuttled through a system of tissues called xylem and phloem, which are packed together in woody, parallel conduits.

Now engineers at MIT and their collaborators have designed a microfluidic device they call a “tree-on-a-chip,” which mimics the pumping mechanism of trees and plants. Like its natural counterparts, the chip operates passively, requiring no moving parts or external pumps. It is able to pump water and sugars through the chip at a steady flow rate for several days. The results are published this week in Nature Plants.

Anette “Peko” Hosoi, professor and associate department head for operations in MIT’s Department of Mechanical Engineering, says the chip’s passive pumping may be leveraged as a simple hydraulic actuator for small robots. Engineers have found it difficult and expensive to make tiny, movable parts and pumps to power complex movements in small robots. The team’s new pumping mechanism may enable robots whose motions are propelled by inexpensive, sugar-powered pumps.

“The goal of this work is cheap complexity, like one sees in nature,” Hosoi says. “It’s easy to add another leaf or xylem channel in a tree. In small robotics, everything is hard, from manufacturing, to integration, to actuation. If we could make the building blocks that enable cheap complexity, that would be super exciting. I think these [microfluidic pumps] are a step in that direction.”

Hosoi’s co-authors on the paper are lead author Jean Comtet, a former graduate student in MIT’s Department of Mechanical Engineering; Kaare Jensen of the Technical University of Denmark; and Robert Turgeon and Abraham Stroock, both of Cornell University.

A hydraulic lift

The group’s tree-inspired work grew out of a project on hydraulic robots powered by pumping fluids. Hosoi was interested in designing hydraulic robots at the small scale, that could perform actions similar to much bigger robots like Boston Dynamic’s Big Dog, a four-legged, Saint Bernard-sized robot that runs and jumps over rough terrain, powered by hydraulic actuators.

“For small systems, it’s often expensive to manufacture tiny moving pieces,” Hosoi says. “So we thought, ‘What if we could make a small-scale hydraulic system that could generate large pressures, with no moving parts?’ And then we asked, ‘Does anything do this in nature?’ It turns out that trees do.”

The general understanding among biologists has been that water, propelled by surface tension, travels up a tree’s channels of xylem, then diffuses through a semipermeable membrane and down into channels of phloem that contain sugar and other nutrients.

The more sugar there is in the phloem, the more water flows from xylem to phloem to balance out the sugar-to-water gradient, in a passive process known as osmosis. The resulting water flow flushes nutrients down to the roots. Trees and plants are thought to maintain this pumping process as more water is drawn up from their roots.

“This simple model of xylem and phloem has been well-known for decades,” Hosoi says. “From a qualitative point of view, this makes sense. But when you actually run the numbers, you realize this simple model does not allow for steady flow.”

In fact, engineers have previously attempted to design tree-inspired microfluidic pumps, fabricating parts that mimic xylem and phloem. But they found that these designs quickly stopped pumping within minutes.

It was Hosoi’s student Comtet who identified a third essential part to a tree’s pumping system: its leaves, which produce sugars through photosynthesis. Comtet’s model includes this additional source of sugars that diffuse from the leaves into a plant’s phloem, increasing the sugar-to-water gradient, which in turn maintains a constant osmotic pressure, circulating water and nutrients continuously throughout a tree.

Running on sugar

With Comtet’s hypothesis in mind, Hosoi and her team designed their tree-on-a-chip, a microfluidic pump that mimics a tree’s xylem, phloem, and most importantly, its sugar-producing leaves.

To make the chip, the researchers sandwiched together two plastic slides, through which they drilled small channels to represent xylem and phloem. They filled the xylem channel with water, and the phloem channel with water and sugar, then separated the two slides with a semipermeable material to mimic the membrane between xylem and phloem. They placed another membrane over the slide containing the phloem channel, and set a sugar cube on top to represent the additional source of sugar diffusing from a tree’s leaves into the phloem. They hooked the chip up to a tube, which fed water from a tank into the chip.

With this simple setup, the chip was able to passively pump water from the tank through the chip and out into a beaker, at a constant flow rate for several days, as opposed to previous designs that only pumped for several minutes.

“As soon as we put this sugar source in, we had it running for days at a steady state,” Hosoi says. “That’s exactly what we need. We want a device we can actually put in a robot.”

Hosoi envisions that the tree-on-a-chip pump may be built into a small robot to produce hydraulically powered motions, without requiring active pumps or parts.

“If you design your robot in a smart way, you could absolutely stick a sugar cube on it and let it go,” Hosoi says.

This research was supported, in part, by the Defense Advance Research Projects Agency.

A new material that naturally adapts to changing environments was inspired by the strength, stability, and mechanical performance of the jaw of a marine worm. The protein material, which was designed and modeled by researchers from the Laboratory for Atomistic and Molecular Mechanics (LAMM) in the Department of Civil and Environmental Engineering (CEE), and synthesized in collaboration with the Air Force Research Lab (AFRL) at Wright-Patterson Air Force Base, Ohio, expands and contracts based on changing pH levels and ion concentrations. It was developed by studying how the jaw of Nereis virens, a sand worm, forms and adapts in different environments.

The resulting pH- and ion-sensitive material is able to respond and react to its environment. Understanding this naturally-occurring process can be particularly helpful for active control of the motion or deformation of actuators for soft robotics and sensors without using external power supply or complex electronic controlling devices. It could also be used to build autonomous structures.

“The ability of dramatically altering the material properties, by changing its hierarchical structure starting at the chemical level, offers exciting new opportunities to tune the material, and to build upon the natural material design towards new engineering applications,” wrote Markus J. Buehler, the McAfee Professor of Engineering, head of CEE, and senior author of the paper.

The research, recently published in ACS Nano, shows that depending on the ions and pH levels in the environment, the protein material expands and contracts into different geometric patterns. When the conditions change again, the material reverts back to its original shape. This makes it particularly useful for smart composite materials with tunable mechanics and self-powered roboticists that use pH value and ion condition to change the material stiffness or generate functional deformations.

Finding inspiration in the strong, stable jaw of a marine worm

In order to create bio-inspired materials that can be used for soft robotics, sensors, and other uses — such as that inspired by the Nereis — engineers and scientists at LAMM and AFRL needed to first understand how these materials form in the Nereis worm, and how they ultimately behave in various environments. This understanding involved the development of a model that encompasses all different length scales from the atomic level, and is able to predict the material behavior. This model helps to fully understand the Nereis worm and its exceptional strength.

“Working with AFRL gave us the opportunity to pair our atomistic simulations with experiments,” said CEE research scientist Francisco Martin-Martinez. AFRL experimentally synthesized a hydrogel, a gel-like material made mostly of water, which is composed of recombinant Nvjp-1 protein responsible for the structural stability and impressive mechanical performance of the Nereis jaw. The hydrogel was used to test how the protein shrinks and changes behavior based on pH and ions in the environment.

The Nereis jaw is mostly made of organic matter, meaning it is a soft protein material with a consistency similar to gelatin. In spite of this, its strength, which has been reported to have a hardness ranging between 0.4 and 0.8 gigapascals (GPa), is similar to that of harder materials like human dentin. “It’s quite remarkable that this soft protein material, with a consistency akin to Jell-O, can be as strong as calcified minerals that are found in human dentin and harder materials such as bones,” Buehler said.

At MIT, the researchers looked at the makeup of the Nereis jaw on a molecular scale to see what makes the jaw so strong and adaptive. At this scale, the metal-coordinated crosslinks, the presence of metal in its molecular structure, provide a molecular network that makes the material stronger and at the same time make the molecular bond more dynamic, and ultimately able to respond to changing conditions. At the macroscopic scale, these dynamic metal-protein bonds result in an expansion/contraction behavior.

Combining the protein structural studies from AFRL with the molecular understanding from LAMM, Buehler, Martin-Martinez, CEE Research Scientist Zhao Qin, and former PhD student Chia-Ching Chou ’15, created a multiscale model that is able to predict the mechanical behavior of materials that contain this protein in various environments. “These atomistic simulations help us to visualize the atomic arrangements and molecular conformations that underlay the mechanical performance of these materials,” Martin-Martinez said.

Specifically, using this model the research team was able to design, test, and visualize how different molecular networks change and adapt to various pH levels, taking into account the biological and mechanical properties.

By looking at the molecular and biological makeup of a the Nereis virens and using the predictive model of the mechanical behavior of the resulting protein material, the LAMM researchers were able to more fully understand the protein material at different scales and provide a comprehensive understanding of how such protein materials form and behave in differing pH settings. This understanding guides new material designs for soft robots and sensors.

Identifying the link between environmental properties and movement in the material

The predictive model explained how the pH sensitive materials change shape and behavior, which the researchers used for designing new PH-changing geometric structures. Depending on the original geometric shape tested in the protein material and the properties surrounding it, the LAMM researchers found that the material either spirals or takes a Cypraea shell-like shape when the pH levels are changed. These are only some examples of the potential that this new material could have for developing soft robots, sensors, and autonomous structures.

Using the predictive model, the research team found that the material not only changes form, but it also reverts back to its original shape when the pH levels change. At the molecular level, histidine amino acids present in the protein bind strongly to the ions in the environment. This very local chemical reaction between amino acids and metal ions has an effect in the overall conformation of the protein at a larger scale. When environmental conditions change, the histidine-metal interactions change accordingly, which affect the protein conformation and in turn the material response.

“Changing the pH or changing the ions is like flipping a switch. You switch it on or off, depending on what environment you select, and the hydrogel expands or contracts” said Martin-Martinez.

LAMM found that at the molecular level, the structure of the protein material is strengthened when the environment contains zinc ions and certain pH levels. This creates more stable metal-coordinated crosslinks in the material’s molecular structure, which makes the molecules more dynamic and flexible.

This insight into the material’s design and its flexibility is extremely useful for environments with changing pH levels. Its response of changing its figure to changing acidity levels could be used for soft robotics. “Most soft robotics require power supply to drive the motion and to be controlled by complex electronic devices. Our work toward designing of multifunctional material may provide another pathway to directly control the material property and deformation without electronic devices,” said Qin.

By studying and modeling the molecular makeup and the behavior of the primary protein responsible for the mechanical properties ideal for Nereis jaw performance, the LAMM researchers are able to link environmental properties to movement in the material and have a more comprehensive understanding of the strength of the Nereis jaw.

The research was funded by the Air Force Office of Scientific Research and the National Science Foundation’s Extreme Science and Engineering Discovery Environment (XSEDE) for the simulations.

Distributed planning, communication, and control algorithms for autonomous robots make up a major area of research in computer science. But in the literature on multirobot systems, security has gotten relatively short shrift.

In the latest issue of the journal Autonomous Robots, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and their colleagues present a new technique for preventing malicious hackers from commandeering robot teams’ communication networks. The technique could provide an added layer of security in systems that encrypt communications, or an alternative in circumstances in which encryption is impractical.

“The robotics community has focused on making multirobot systems autonomous and increasingly more capable by developing the science of autonomy. In some sense we have not done enough about systems-level issues like cybersecurity and privacy,” says Daniela Rus, an Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT and senior author on the new paper.

“But when we deploy multirobot systems in real applications, we expose them to all the issues that current computer systems are exposed to,” she adds. “If you take over a computer system, you can make it release private data — and you can do a lot of other bad things. A cybersecurity attack on a robot has all the perils of attacks on computer systems, plus the robot could be controlled to take potentially damaging action in the physical world. So in some sense there is even more urgency that we think about this problem.”

Identity theft

Most planning algorithms in multirobot systems rely on some kind of voting procedure to determine a course of action. Each robot makes a recommendation based on its own limited, local observations, and the recommendations are aggregated to yield a final decision.

A natural way for a hacker to infiltrate a multirobot system would be to impersonate a large number of robots on the network and cast enough spurious votes to tip the collective decision, a technique called “spoofing.” The researchers’ new system analyzes the distinctive ways in which robots’ wireless transmissions interact with the environment, to assign each of them its own radio “fingerprint.” If the system identifies multiple votes as coming from the same transmitter, it can discount them as probably fraudulent.

“There are two ways to think of it,” says Stephanie Gil, a research scientist in Rus’ Distributed Robotics Lab and a co-author on the new paper. “In some cases cryptography is too difficult to implement in a decentralized form. Perhaps you just don’t have that central key authority that you can secure, and you have agents continually entering or exiting the network, so that a key-passing scheme becomes much more challenging to implement. In that case, we can still provide protection.

“And in case you can implement a cryptographic scheme, then if one of the agents with the key gets compromised, we can still provide  protection by mitigating and even quantifying the maximum amount of damage that can be done by the adversary.”

Hold your ground

In their paper, the researchers consider a problem known as “coverage,” in which robots position themselves to distribute some service across a geographic area — communication links, monitoring, or the like. In this case, each robot’s “vote” is simply its report of its position, which the other robots use to determine their own.

The paper includes a theoretical analysis that compares the results of a common coverage algorithm under normal circumstances and the results produced when the new system is actively thwarting a spoofing attack. Even when 75 percent of the robots in the system have been infiltrated by such an attack, the robots’ positions are within 3 centimeters of what they should be. To verify the theoretical predictions, the researchers also implemented their system using a battery of distributed Wi-Fi transmitters and an autonomous helicopter.

“This generalizes naturally to other types of algorithms beyond coverage,” Rus says.

The new system grew out of an earlier project involving Rus, Gil, Dina Katabi — who is the other Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT — and Swarun Kumar, who earned master’s and doctoral degrees at MIT before moving to Carnegie Mellon University. That project sought to use Wi-Fi signals to determine transmitters’ locations and to repair ad hoc communication networks. On the new paper, the same quartet of researchers is joined by MIT Lincoln Laboratory’s Mark Mazumder.

Typically, radio-based location determination requires an array of receiving antennas. A radio signal traveling through the air reaches each of the antennas at a slightly different time, a difference that shows up in the phase of the received signals, or the alignment of the crests and troughs of their electromagnetic waves. From this phase information, it’s possible to determine the direction from which the signal arrived.

Space vs. time

A bank of antennas, however, is too bulky for an autonomous helicopter to ferry around. The MIT researchers found a way to make accurate location measurements using only two antennas, spaced about 8 inches apart. Those antennas must move through space in order to simulate measurements from multiple antennas. That’s a requirement that autonomous robots meet easily. In the experiments reported in the new paper, for instance, the autonomous helicopter hovered in place and rotated around its axis in order to make its measurements.

When a Wi-Fi transmitter broadcasts a signal, some of it travels in a direct path toward the receiver, but much of it bounces off of obstacles in the environment, arriving at the receiver from different directions. For location determination, that’s a problem, but for radio fingerprinting, it’s an advantage: The different energies of signals arriving from different directions give each transmitter a distinctive profile.

There’s still some room for error in the receiver’s measurements, however, so the researchers’ new system doesn’t completely ignore probably fraudulent transmissions. Instead, it discounts them in proportion to its certainty that they have the same source. The new paper’s theoretical analysis shows that, for a range of reasonable assumptions about measurement ambiguities, the system will thwart spoofing attacks without unduly punishing valid transmissions that happen to have similar fingerprints.

“The work has important implications, as many systems of this type are on the horizon — networked autonomous driving cars, Amazon delivery drones, et cetera,” says David Hsu, a professor of computer science at the National University of Singapore. “Security would be a major issue for such systems, even more so than today’s networked computers. This solution is creative and departs completely from traditional defense mechanisms.”

If you enjoyed this article from CSAIL, you might also be interested in:

• Mind control: Correcting robot mistakes using EEG brain signals
• MIT CSAIL’s 6-foot-tall NASA humanoid robot has landed
• Researchers add a splash of human intuition to planning algorithms
• Wearable AI that can detect the tone of a conversation
• Ingestible robots, glasses-free 3-D, and computers that explain themselves

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.