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Researchers have demonstrated a caterpillar-like soft robot that can move forward, backward, and dip under narrow spaces.
The caterpillar-bot’s movement is driven by a novel pattern of silver nanowires that use heat to control the way the robot bends, allowing users to steer the robot in either direction.
“A caterpillar’s movement is controlled by local curvature of its body—its body curves differently when it pulls itself forward than it does when it pushes itself backward,” says Yong Zhu, professor of mechanical and aerospace engineering at North Carolina State University and corresponding author of a paper on the work.
“We’ve drawn inspiration from the caterpillar’s biomechanics to mimic that local curvature, and use nanowire heaters to control similar curvature and movement in the caterpillar-bot.
“Engineering soft robots that can move in two different directions is a significant challenge in soft robotics,” Zhu says.
“The embedded nanowire heaters allow us to control the movement of the robot in two ways. We can control which sections of the robot bend by controlling the pattern of heating in the soft robot. And we can control the extent to which those sections bend by controlling the amount of heat being applied.”
The caterpillar-bot consists of two layers of polymer, which respond differently when exposed to heat. The bottom layer shrinks, or contracts, when exposed to heat. The top layer expands when exposed to heat. A pattern of silver nanowires is embedded in the expanding layer of polymer. The pattern includes multiple lead points where researchers can apply an electric current. The researchers can control which sections of the nanowire pattern heat up by applying an electric current to different lead points, and can control the amount of heat by applying more or less current.
“We demonstrated that the caterpillar-bot is capable of pulling itself forward and pushing itself backward,” says postdoctoral researcher Shuang Wu, first author of the paper.
“In general, the more current we applied, the faster it would move in either direction. However, we found that there was an optimal cycle, which gave the polymer time to cool—effectively allowing the ‘muscle’ to relax before contracting again. If we tried to cycle the caterpillar-bot too quickly, the body did not have time to ‘relax’ before contracting again, which impaired its movement.”
The researchers also demonstrated that the caterpillar-bot’s movement could be controlled to the point where users were able steer it under a very low gap—similar to guiding the robot to slip under a door. In essence, the researchers could control both forward and backward motion as well as how high the robot bent upwards at any point in that process.
“This approach to driving motion in a soft robot is highly energy efficient, and we’re interested in exploring ways that we could make this process even more efficient,” Zhu says.
“Additional next steps include integrating this approach to soft robot locomotion with sensors or other technologies for use in various applications—such as search-and-rescue devices.”
The paper appears in Science Advances.
Support for the work came from the National Science Foundation and the National Institutes of Health.
Source: NC State
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A new forensic science study sheds light on how the bones of infants and children decay.
The findings will help forensic scientists determine how long a young person’s remains were at a particular location, as well as which bones are best suited for collecting DNA and other tissue samples that can help identify the deceased.
“Crimes against children are truly awful, and all too common,” says Ann Ross, a professor of biological sciences at North Carolina State University and coauthor of the study in the journal Biology.
“It is important to be able to identify their remains and, when possible, understand what happened to them. However, there is not much research on how the bones of infants and children break down over time. Our work here is a significant contribution that will help the medical legal community bring some closure to these young people and, hopefully, a measure of justice.”
For the study, the researchers used the remains of domestic pigs, which are widely used as an analogue for human remains in forensic research. Specifically, the researchers used the remains of 31 pigs, ranging in size from 1.8 kilograms (4 pounds) to 22.7 kilograms (50 pounds). The smaller remains served as surrogates for infant humans, up to one year old. The larger remains served as surrogates for children between the ages of one and nine.
The surrogate infants were left at an outdoor research site in one of three conditions: placed in a plastic bag, wrapped in a blanket, or fully exposed to the elements. Surrogate juveniles were either left exposed or buried in a shallow grave.
The researchers assessed the remains daily for two years to record decomposition rate and progression. The researchers also collected environmental data, such as temperature and soil moisture, daily.
Following the two years of exposure, the researchers brought the skeletal remains back to the lab. The researchers cut a cross section of bone from each set of remains and conducted a detailed inspection to determine how the structure of the bones had changed at the microscopic level.
The researchers found that all of the bones had degraded, but the degree of the degradation varied depending on the way that the remains were deposited. For example, surrogate infant remains wrapped in plastic degraded at a different rate from surrogate infant remains that were left exposed to the elements. The most significant degradation occurred in juvenile remains that had been buried.
“This is because the bulk of the degradation in the bones that were aboveground was caused by the tissue being broken down by microbes that were already in the body,” says corresponding author and PhD candidate Amanda Hale. “Buried remains were degraded by both internal microbes and by microbes in the soil.”
Hale is a research scientist at SNA International working for the Defense POW/MIA Accounting Agency.
The researchers also used statistical tools that allowed them to better assess the degree of bone degradation that took place at various points in time.
“In practical terms, this is one more tool in our toolbox,” Ross says. “Given available data on temperature, weather, and other environmental factors where the remains were found, we can use the condition of the skeletal remains to develop a rough estimate of when the remains were deposited at the site. And all of this is informed by how the remains were found. For example, whether the remains were buried, wrapped in a plastic tarp, and so on.
“Any circumstance where forensic scientists are asked to work with unidentified juvenile remains is a tragic one. Our hope is that this work will help us better understand what happened to these young people.”
Source: NC State
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Wheeled robots can accurately measure the angle of leaves on corn plants in the field, report researchers.
“The angle of a plant’s leaves, relative to its stem, is important because the leaf angle affects how efficient the plant is at performing photosynthesis,” says Lirong Xiang, first author of a paper on the work and an assistant professor of biological and agricultural engineering at North Carolina State University.
“For example, in corn, you want leaves at the top that are relatively vertical, but leaves further down the stalk that are more horizontal. This allows the plant to harvest more sunlight. Researchers who focus on plant breeding monitor this sort of plant architecture because it informs their work.
“However, conventional methods for measuring leaf angles involve measuring leaves by hand with a protractor—which is both time-consuming and labor-intensive,” Xiang says. “We wanted to find a way to automate this process—and we did.”
The new technology—called AngleNet—has two key components: the hardware and the software.
The hardware, in this case, is a robotic device that is mounted on wheels. The device is steered manually, and is narrow enough to navigate between crop rows that are spaced 30 inches apart –the standard width farmers use. The device itself consists of four tiers of cameras, each of which is set to a different height to capture a different level of leaves on the surrounding plants. Each tier includes two cameras, allowing it to capture a stereoscopic view of the leaves and enable 3D modeling of plants.
As the device is steered down a row of plants, it is programmed to capture multiple stereoscopic images, at multiple heights, of every plant it passes.
All of this visual data goes into a software program that then computes the leaf angle for the leaves of each plant at different heights.
“For plant breeders, it’s important to know not only what the leaf angle is, but how far those leaves are above the ground,” Xiang says. “This gives them the information they need to assess the leaf angle distribution for each row of plants. This, in turn, can help them identify genetic lines that have desirable traits—or undesirable traits.”
To test the accuracy of AngleNet, the researchers compared leaf angle measurements done by the robot in a corn field to leaf angle measurements made by hand using conventional techniques.
“We found that the angles measured by AngleNet were within 5 degrees of the angles measured by hand, which is well within the accepted margin of error for purposes of plant breeding,” Xiang says.
“We’re already working with some crop scientists to make use of this technology, and we’re optimistic that more researchers will be interested in adopting the technology to inform their work. Ultimately, our goal is to help expedite plant breeding research that will improve crop yield.”
The paper appears in the Journal of Field Robotics. Coauthors are from Iowa State University and Auburn University. The work had support from the National Science Foundation and the Plant Sciences Institute at Iowa State.
Source: NC State
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A “white light” added to traffic signals could enable self-driving vehicles to help control traffic flow—and let human drivers know what’s going on.
In computational simulations, the new approach significantly improves travel time through intersections and reduces fuel consumption.
“This concept we’re proposing for traffic intersections, which we call a ‘white phase,’ taps into the computing power of autonomous vehicles (AVs) themselves,” says Ali Hajbabaie, an associate professor of civil, construction, and environmental engineering at North Carolina State University, and corresponding author of the paper in IEEE Transactions on Intelligent Transportation Systems.
“The white phase concept also incorporates a new traffic signal, so that human drivers know what they are supposed to do. Red lights will still mean stop. Green lights will still mean go. And white lights will tell human drivers to simply follow the car in front of them.”
The white phase concept rests on the fact that it is possible for AVs to communicate wirelessly with both each other and the computer controlling the traffic signal. When enough AVs are approaching the intersection, this would activate the white light.
The white light is a signal that AVs are coordinating their movement to facilitate traffic through the intersection more efficiently. Any non-automated vehicles—those being driven by a person—would simply be required to follow the vehicle in front of them: if the car in front of them stops, they stop; if the car in front of them goes through the intersection, they go through the intersection.
When too many vehicles approaching the intersection are being controlled by drivers, rather than AVs, the traffic light would revert to the conventional green-yellow-red signal pattern.
“Granting some of the traffic flow control to the AVs is a relatively new idea, called the mobile control paradigm,” Hajbabaie says. “It can be used to coordinate traffic in any scenario involving AVs. But we think it is important to incorporate the white light concept at intersections because it tells human drivers what’s going on, so that they know what they are supposed to do as they approach the intersection.
“And, just to be clear, the color of the ‘white light’ doesn’t matter. What’s important is that there be a signal that is clearly identifiable by drivers.”
The researchers first introduced a “white phase” traffic intersection concept in 2020. However, that initial concept relied on a centralized computing approach, with the computer controlling the traffic light being responsible for receiving input from all approaching AVs, making the necessary calculations, and then telling the AVs how they should proceed through the intersection.
“We’ve improved on that concept, and this paper outlines a white phase concept that relies on distributed computing—effectively using the computing resources of all the AVs to dictate traffic flow,” Hajbabaie says.
“This is both more efficient, and less likely to fall prey to communication failures. For example, if there’s an interruption or time lag in communication with the traffic light, the distributed computing approach would still be able to handle traffic flow smoothly.”
To test the performance of the distributed computing white phase concept, the researchers made use of microscopic traffic simulators. These simulators are complex computational models designed to replicate real-world traffic, down to the behavior of individual vehicles. Using these simulators, the researchers were able to compare traffic behavior at intersections with and without the white phase, as well as how the number of AVs involved influences that behavior.
“The simulations tell us several things,” Hajbabaie says. “First, AVs improve traffic flow, regardless of the presence of the white phase. Second, if there are AVs present, the white phase further improves traffic flow. This also reduces fuel consumption, because there is less stop-and-go traffic. Third, the higher the percentage of traffic at a white phase intersection that is made up of AVs, the faster the traffic moves through the intersection and the better the fuel consumption numbers.”
When only 10-30% of the traffic at a white phase intersection was made up of AVs, the simulations found there were relatively small improvements in traffic flow. But as the percentage of AVs at white phase intersections increased, so did the benefits.
“That said, even if only 10% of the vehicles at a white phase intersection are autonomous, you still see fewer delays,” Hajbabaie says. “For example, when 10% of vehicles are autonomous, you see delays reduced by 3%. When 30% of vehicles are autonomous, delays are reduced by 10.7%.”
The researchers acknowledge that AVs are not ready to adopt the new distributed computing approach tomorrow, nor are governments going to install brand new traffic lights at every intersection in the immediate future.
“However, there are various elements of the white phase concept that could be adopted with only minor modifications to both intersections and existing AVs,” Hajbabaie says. “We also think there are opportunities to test drive this approach at specific locations.
“For example, ports see high volumes of commercial vehicle traffic, for which traffic flow is particularly important. Commercial vehicles seem to have higher rates of autonomous vehicle adoption, so there could be an opportunity to implement a pilot project in that setting that could benefit port traffic and commercial transportation.”
Source: NC State
The post Do traffic signals need a fourth light for self-driving cars? appeared first on Futurity.
A new technique uses liquid metal to create an elastic material that is impervious to both gases and liquids.
Applications for the material include flexible batteries and other packaging for high-value technologies that require protection from gases.
“This is an important step because there has long been a trade-off between elasticity and being impervious to gases,” says Michael Dickey, professor of chemical and biomolecular engineering at North Carolina State University.
“Basically, things that were good at keeping gases out tended to be hard and stiff. And things that offered elasticity allowed gases to seep through. We’ve come up with something that offers the desired elasticity while keeping gases out.”
The new technique makes use of a eutectic alloy of gallium and indium (EGaIn). Eutectic means that the alloy has a melting point that is lower than its constituent parts. In this case, the EGaIn is liquid at room temperature.
The researchers created a thin film of EGaIn, and encased it in an elastic polymer. The interior surface of the polymer was studded with microscale glass beads, which prevented the liquid film of EGaIn from pooling. The end result is essentially an elastic bag or sheath lined with liquid metal, which does not allow gases or liquids in or out.
The researchers tested the effectiveness of the new elastic material by assessing the extent to which it allowed liquid contents to evaporate, as well as the extent to which it allowed oxygen to leak out of a sealed container made of the material.
“We found that there was no measurable loss of either liquid or oxygen for the new material,” says Tao Deng, professor at Shanghai Jiao Tong University and co-corresponding author of the study in the journal Science.
The researchers are also conscious of costs associated with manufacturing the new material.
“The liquid metals themselves are fairly expensive,” Deng says. “However, we’re optimistic that we can optimize the technique—for example, making the EGaIn film thinner—in order to reduce the cost. At the moment, a single package would cost a few dollars, but we did not attempt to optimize for cost so there is a path forward to drive cost down.”
The researchers are currently exploring testing options to determine whether the material is actually an even more effective barrier than they’ve been able to show so far.
“Basically, we reached the limit of the testing equipment that we had available,” Dickey says.
“We’re also looking for industry partners to explore potential applications for this work. Flexible batteries for use with soft electronics is one obvious application, but other devices that either use liquids or are sensitive to oxygen will benefit from this technology.”
Additional coauthors are from Shanghai Jiao Tong University and NC State.
The National Science Foundation, the National Natural Science Foundation of China, the Innovation Program of the Shanghai Municipal Education Commission, and Shanghai Jiao Tong University supported the work.
Source: NC State
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