Waiting for each part of a 3D-printed project to finish, taking it out of the printer, and then installing it on location can be tedious for multi-part projects. What if there was a way for your printer to print its creation exactly where you needed it? That’s the promise of MobiPrint, a new 3D printing robot that can move around a room, printing designs directly onto the floor.

MobiPrint, designed by Daniel Campos Zamora at the University of Washington, consists of a modified off-the-shelf 3D printer atop a home vacuum robot. First it autonomously maps its space—be it a room, a hallway, or an entire floor of a house. Users can then choose from a prebuilt library or upload their own design to be printed anywhere in the mapped area. The robot then traverses the room and prints the design.

It’s “a new system that combines robotics and 3D printing that could actually go and print in the real world,” Campos Zamora says. He presented MobiPrint on 15 October at the ACM Symposium on User Interface Software and Technology.

Campos Zamora and his team started with a Roborock S5 vacuum robot and installed firmware that allowed it to communicate with the open source program Valetudo. Valetudo disconnects personal robots from their manufacturer’s cloud, connecting them to a local server instead. Data collected by the robot, such as environmental mapping, movement tracking, and path planning, can all be observed locally, enabling users to see the robot’s LIDAR-created map.

Campos Zamora built a layer of software that connects the robot’s perception of its environment to the 3D printer’s print commands. The printer, a modified Prusa Mini+, can print on carpet, hardwood, and vinyl, with maximum printing dimensions of 180 by 180 by 65 millimeters. The robot has printed pet food bowls, signage, and accessibility markers as sample objects.

MakeabilityLab/YouTube

Currently, MobiPrint can only “park and print.” The robot base cannot move during printing to make large objects, like a mobility ramp. Printing designs larger than the robot is one of Campos Zamora’s goals in the future. To learn more about the team’s vision for MobiPrint, Campos Zamora answered a few questions from IEEE Spectrum.

What was the inspiration for creating your mobile 3D printer?

Daniel Campos Zamora: My lab is focused on building systems with an eye towards accessibility. One of the things that really inspired this project was looking at the tactile surface indicators that help blind and low vision users find their way around a space. And so we were like, what if we made something that could automatically go and deploy these things? Especially in indoor environments, which are generally a little trickier and change more frequently over time.

We had to step back and build this entirely different thing, using the environment as a design element. We asked: how do you integrate the real world environment into the design process, and then what kind of things can you print out in the world? That’s how this printer was born.

What were some surprising moments in your design process?

Campos Zamora: When I was testing the robot on different surfaces, I was not expecting the 3D printed designs to stick extremely well to the carpet. It stuck way too well. Like, you know, just completely bonded down there.

I think there’s also just a lot of joy in seeing this printer move. When I was doing a demonstration of it at this conference last week, it almost seemed like the robot had a personality. A vacuum robot can seem to have a personality, but this printer can actually make objects in my environment, so I feel a different relationship to the machine.

Where do you hope to take MobiPrint in the future?

Campos Zamora: There’s several directions I think we could go. Instead of controlling the robot remotely, we could have it follow someone around and print accessibility markers along a path they walk. Or we could integrate an AI system that recommends objects be printed in different locations. I also want to explore having the robot remove and recycle the objects it prints.

Yesterday, NASA successfully launched the Europa Clipper, the largest spacecraft the agency has ever built for a planetary mission. Clipper is now successfully on its multi-year journey to Europa, bristling with equipment to study the Jovian moon’s potential to support life—but just a few months ago, the mission was almost doomed. In July, researchers at NASA found out that a group of Europa Clipper’s transistors would fail under Jupiter’s extreme radiation levels. They spent months testing devices, updating their flight trajectories, and ultimately adding a warning “canary box” to monitor the effects of radiation as the mission progresses.

The canary box “is a very logical engineering solution to a problem,” says Alan Mantooth, an IEEE Fellow and a professor of electrical engineering at the University of Arkansas. But ideally, it wouldn’t have been needed at all. If NASA had caught the issues with these transistors earlier or designed their circuits with built-in monitoring, this last minute scramble wouldn’t have occurred. “It’s a clever patch,” says Mantooth, “but it’s a patch.”

Scientists have been “radiation hardening” electronics—designing them to function in a radioactive environment—since the 1960s. But as missions to space become more ambitious, radiation hardening techniques have had to evolve. “It’s kind of like cybersecurity,” says Mantooth. “You’re always trying to get better. There’s always a more harsh environment.”

With the rapid acceleration of companies like SpaceX, the space industry is at “a massive inflection point,” says Eric Faraci, an engineer at Infineon who works on aerospace and defense projects. “Everything we used to take for granted about how you do something, what’s accepted, best practices—everything’s been questioned.”

In future space exploration, we’ll see more systems made with alternative semiconductors like silicon carbide, specialized CMOS transistors, integrated photonics, and new kinds of radiation-resistant memory. Here’s your guide to the next generation of radiation hardened technology.

Silicon Carbide’s Ultra Wide Band Gap

Most power devices in spacecraft today use silicon as the semiconductor, but the next generation will use silicon carbide, says Enxia Zhang, a researcher at the University of Central Florida who has been developing radiation hard microelectronics for over 20 years. Silicon carbide is more resistant to radiation because of its wider band gap, which is the extra energy electrons need to transition from being bound to an atom’s nucleus to participating in conduction. Silicon has a band gap of 1.1 electron volts, while silicon carbide’s ranges from 3.3 to 3.4 eV. This means that more energy is required to disturb an electron of silicon carbide, so it’s less likely that a dose of stray radiation will manage to do it.

Silicon carbide chips are being manufactured right now, and NASA holds a weekly meeting to test them for space missions, says Zhang. NASA’s silicon carbide devices are expected to be used on missions to the Moon and Venus in the future.

“People are flying silicon carbide” devices right now, says Infineon’s Faraci. They are getting around a lack of standards by using them at parameters well below what they are designed for on Earth, a technique called derating.

Another semiconductor with a suitably wide band gap is gallium nitride (3.2 eV). Most commonly found in LEDs, it is also used in laptop chargers and other lower power consumer electronics. While it’s a “very exciting” material for space applications, it’s still a new material, which means it has to go through a lot of testing to be trusted, says Faraci.

Gallium nitride is best suited for cold temperatures, like on Mars or the dark side of the Moon, says Mantooth. But “if we’re doing something on Mercury or we’re doing something close to the Sun—any high temperature stuff … silicon carbide’s your winner.”

Silicon on Insulator Designs and FinFETs for Designing Radiation-Hardened CMOS

New materials aren’t the only frontier in radiation hardening; researchers are also exploring new ways of designing silicon transistors. Two CMOS production methods are already have a radiation hardened form: silicon on insulator (SOI), and fin field effect transistors (FinFETs). Both methods are designed to prevent a kind of radiation damage called single event effects, where a high energy particle hits an electronic device, jolting its electrons into places they shouldn’t be and flipping bits.

In ordinary bulk CMOS, current flows from the source to the drain through the channel, with a gate acting as a switch, blocking or allowing the current’s flow. These sit in the top layer of silicon. Radiation can excite charges deeper down in the silicon bypassing the gate’s control and allowing current to flow when it shouldn’t. Radiation hardening methods work by impeding the movement of these excited electrons.

SOI designs add a layer of an insulator like silicon oxide below the source and the drain, so that charges cannot flow as easily below the channel. FinFET designs raise the drain, source, and the channel between them into one or more 3D “fins”. Excited charges now have to flow down, around, and back up in order to bypass the gate. FinFETs are also naturally resistant to another form of radiation damage: the total ionizing dose, which occurs when a slow buildup of charged particles changes the properties of the insulating layer between the channel and gate of a device.

The techniques to produce SOI devices and FinFETs have existed for decades. In the 2000s, they weren’t used as much in radiation hardening, because circuit designers could still use ordinary, bulk CMOS devices, mitigating radiation risks in their circuit design and layout, according to Hugh Barnaby, a professor of electrical engineering at Arizona State University. But lately, as CMOS devices have gotten smaller and therefore more vulnerable to radiation, there’s been renewed interest in producing these naturally radiation hard varieties of CMOS devices, even if they are more specialized and expensive.

Barnaby is working with a team on improving radiation hardness in FinFETs. They found that adding more fins increased the device’s ability to control current, but reduced its radiation hardness. Now they are working to rearrange where the fins are to maximize the effectiveness of radiation resistant circuits. “We haven’t done this quite yet,” says Barnaby, “but I’m sure it will work.”

Photonic Systems for High Bandwidth, Faster Data Transfer

Photonic systems use light instead of electrons to transfer information over long distances with little energy. For example, the Internet uses optical fibers to quickly transfer large amounts of data. Within the last decade, researchers have developed silicon photonics integrated circuits which are currently used for high bandwidth information transmission in data centers, but would also enable us to move high volumes of data around in spacecraft, according to John Cressler, a professor of electronics at Georgia Tech.

“If you think of some of the systems that are up in space, either maybe they’re remote sensing or communication,” says Cressler, “they have a lot of data that they’re gathering or moving and that’s much easier to do in photonics.”

The best part? Photonics integrated circuits are naturally radiation hard, because their data transfer is done using photons instead of electrons. A high energy dose of radiation won’t disrupt a photon as it would an electron, because photons are not electrically charged.

Cressler anticipates that integrated photonics will be used in spacecraft in the next two years. “NASA and the [U.S. Department of Defense] and even commercial space [companies] are very interested in photonics,” he says.

Nonvolatile Memory in Space

Another promising area of research for radiation hardness in space is new kinds of nonvolatile memory. Computers usually use static random access memory (SRAM) or dynamic random access memory (DRAM). These are volatile memories, which means once the power is off, they cannot store their state. But nonvolatile memories are able to remember their state. They don’t require continuous power, and therefore reduce power consumption needs.

There are two front-runners in nonvolatile memory for use in space: Magnetoresistive-RAM (MRAM), and Resistive-RAM (ReRAM). MRAM uses magnetic states to store data, and ReRAM uses a quality called memristance. Both technologies are radiation hard simply by how they are designed; radiation won’t affect the magnetic fields of MRAM or the resistances of ReRAM.

“Resistive RAM is one of the technologies that has the potential to get to neuromorphic, low energy computing,” says Michael Alles, the director of the Institute for Space and Defense Electronics at Vanderbilt University, referring to a form of computing inspired by how brains work. Satellites usually are not equipped with the ability to process much of their own data, and have to send it back to Earth. But with the lower power consumption of memristor-based circuits, satellites could do computations onboard, saving communications bandwidth and time.

Though still in the research phases, Zhang predicts we will see nonvolatile memory in space in the next 10 to 15 years. Last year, the U.S. Space Force contracted Western Digital $35 million dollars to develop nonvolatile radiation hardened memory.

A Note of Caution and Hope

Alles cautions, however, that the true test for these new technologies will not be how they do on their own, but rather how they can be integrated to work as a system. You always have to ask: “What’s the weak link?” A powerful and radiation hard memory device could be for naught, if it depends on a silicon transistor that fails under radiation.

As space exploration and satellite launches continue to ramp up, radiation hardening will only become more vital to our designs. “What’s exciting is that as we advance our capabilities, we’re able to go places we haven’t been able to go before and stay there longer,” says Mantooth. “We can’t fly electronics into the Sun right now. But one day, maybe we will.”

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

In space, high-energy gamma radiation can change the properties of semiconductors, altering how they work or rendering them completely unusable. Finding devices that can withstand radiation is important not just to keep astronauts safe but also to ensure that a spacecraft lasts the many years of its mission. Constructing a device that can easily measure radiation exposure is just as valuable. Now, a globe-spanning group of researchers has found that a type of memristor, a device that stores data as resistance even in the absence of a power supply, can not only measure gamma radiation but also heal itself after being exposed to it.

Memristors have demonstrated the ability to self-heal under radiation before, says Firman Simanjuntak, a professor of materials science and engineering at the University of Southampton, in England, whose team developed this memristor. But until recently, no one really understood how they healed—or how best to apply the devices. Recently, there’s been “a new space race,” he says, with more satellites in orbit and more deep-space missions on the launchpad, so “everyone wants to make their devices…tolerant towards radiation.” Simanjuntak’s team has been exploring the properties of different types of memristors since 2019, but now wanted to test how their devices change when exposed to blasts of gamma radiation.

Normally, memristors set their resistance according to their exposure to high-enough voltage. One voltage boosts the resistance, which then remains at that level when subject to lower voltages. The opposite voltage decreases the resistance, resetting the device. The relationship between voltage and resistance depends on the previous voltage, which is why the devices are said to have a memory.

The hafnium oxide memristor used by Simanjuntak is a type of memristor that cannot be reset, called a WORM (write once, read many) device, suitable for permanent storage. Once it is set with a negative or positive voltage, the opposing voltage does not change the device. It consists of several layers of material: first conductive platinum, then aluminum doped hafnium oxide (an insulator), then a layer of titanium, then a layer of conductive silver at the top.

When voltage is applied to these memristors, a bridge of silver ions forms in the hafnium oxide, which allows the current to flow through, setting its conductance value. Unlike in other memristors, this device’s silver bridge is stable and fixes in place, which is why once the device is set, it usually can’t be returned to a rest state.

That is, unless radiation is involved. The first discovery the researchers made was that under gamma radiation, the device acts as a resettable switch. They believe that the gamma rays break the bond between the hafnium and oxygen atoms, causing a layer of titanium oxide to form at the top of the memristor, and a layer of platinum oxide to form at the bottom. The titanium oxide layer creates an extra barrier for the silver ions to cross, so a weaker bridge is formed, one that can be broken and reset by a new voltage.

The extra platinum oxide layer caused by the gamma rays also serves as a barrier to incoming electrons. This means a higher voltage is required to set the memristor. Using this knowledge, the researchers were able to create a simple circuit that measured amounts of radiation by checking the voltage that was required to set the memristor. A higher voltage meant the device had encountered more radiation.

From a regular state, the hafnium oxide memristor forms a stable conductive bridge. Under radiation, a thicker layer of titanium oxide creates a slower-forming, weaker conductive bridge.OM Kumar et al./IEEE Electron Device Letters

But the true marvel of these hafnium oxide memristors is their ability to self-heal after a big dose of radiation. The researchers treated the memristor with 5 megarads of radiation—500 times as much as a lethal dose in humans. Once the gamma radiation was removed, the titanium oxide and platinum oxide layers gradually dissipated, the oxygen atoms returning to form hafnium oxide again. After 30 days, instead of still requiring a higher-than-normal voltage to form, the devices that were exposed to radiation required the same voltage to form as untouched devices.

“It’s quite exciting what they’re doing,” says Pavel Borisov, a researcher at Loughborough University, in England, who studies how to use memristors to mimic the synapses in the human brain. His team conducted similar experiments with a silicon oxide based memristor, and also found that radiation changed the behavior of the device. In Borisov’s experiments, however, the memristors did not heal after the radiation.

Memristors are simple, lightweight, and low power, which already makes them ideal for use in space applications. In the future, Simanjuntak hopes to use memristors to develop radiation-proof memory devices that would enable satellites in space to do onboard calculations. “You can use a memristor for data storage, but also you can use it for computation,” he says, “So you could make everything simpler, and reduce the costs as well.”

This research was accepted for publication in a future issue of Electron Device Letters.

Did that rock move, or is it a squirrel crossing the road? Tracking objects that look a lot like their surroundings is a big problem for many autonomous vision systems. AI algorithms can solve this camouflage problem, but they take time and computing power. A new camera designed by researchers in South Korea provides a faster solution. The camera takes inspiration from the eyes of a cat, using two modifications that let it distinguish objects from their background, even at night.

“In the future … a variety of intelligent robots will require the development of vision systems that are best suited for their specific visual tasks,” says Young Min Song, a professor of electrical engineering and computer science at Gwangju Institute of Science and Technology and one of the camera’s designers. Song’s recent research has been focused on using the “perfectly adapted” eyes of animals to enhance camera hardware, allowing for specialized cameras for different jobs. For example, fish eyes have wider fields of view as a consequence of their curved retinas. Cats may be common and easy to overlook, he says, but their eyes actually offer a lot of inspiration.

This particular camera copied two adaptations from cats’ eyes: their vertical pupils and a reflective structure behind their retinas. Combined, these allowed the camera to be 10 percent more accurate at distinguishing camouflaged objects from their backgrounds and 52 percent more efficient at absorbing incoming light.

Using a vertical pupil to narrow focus

While conventional cameras can clearly see the foreground and background of an image, the slitted pupils of a cat focus directly on a target, preventing it from blending in with its surroundings. Kim et al./Science Advances

In conventional camera systems, when there is adequate light, the aperture—the camera’s version of a pupil—is small and circular. This structure allows for a large depth of field (the distance between the closest and farthest objects in focus), clearly seeing both the foreground and the background. By contrast, cat eyes narrow to a vertical pupil during the day. This shifts the focus to a target, distinguishing it more clearly from the background.

The researchers 3D printed a vertical slit to use as an aperture for their camera. They tested the vertical slit using seven computer vision algorithms designed to track moving objects. The vertical slit increased contrast between a target object and its background, even if they were visually similar. It beat the conventional camera on five of the seven tests. For the two tests it performed worse than the conventional camera, the accuracies of the two cameras were within 10 percent of each other.

Using a reflector to gather additional light

Cats can see more clearly at night than conventional cameras due to reflectors in their eyes that bring extra light to their retinas.Kim et al./Science Advances

Cat eyes have an in-built reflector, called a tapetum lucidum, which sits behind the retina. It reflects light that passes through the retina back at it, so it can process both the incoming light and reflected light, giving felines superior night vision. You can see this biological adaptation yourself by looking at a cat’s eyes at night: they will glow.

The researchers created an artificial version of this biological structure by placing a silver reflector under each photodiode in the camera. Photodiodes without a reflector generated current when more than 1.39 watts per square meter of light fell on them, while photodiodes with a reflector activated with 0.007 W/m² of light. That means the photodiode could generate an image with about 1/200th the light.

Each photodiode was placed above a reflector and joined by metal electrodes to create a curved image sensor.Kim et al./Science Advances

To decrease visual aberrations (imperfections in the way the lens of the camera focuses light), Song and his team opted to create a curved image sensor, like the back of the human eye. In such a setup, a standard image sensor chip won’t work, because it’s rigid and flat. Instead it often relies on many individual photodiodes arranged on a curved substrate. A common problem with such curved sensors is that they require ultrathin silicon photodiodes, which inherently absorb less light than a standard imager’s pixels. But reflectors behind each photodiode in the artificial cat’s eye compensated for this, enabling the researchers to create a curved imager without sacrificing light absorption.

Together, vertical slits and reflectors led to a camera that could see more clearly in the dark and isn’t fooled by camouflage. “Applying these two characteristics to autonomous vehicles or intelligent robots could naturally improve their ability to see objects more clearly at night and to identify specific targets more accurately,” says Song. He foresees this camera being used for self-driving cars or drones in complex urban environments.

Song’s lab is continuing to work on using biological solutions to solve artificial vision problems. Currently, they are developing devices that mimic how brains process images, hoping to one day combine them with their biologically-inspired cameras. The goal, says Song, is to “mimic the neural systems of nature.”

Song and his colleague’s work was published this week in the journal Science Advances.