A popular heart scan may be unnecessary for many patients but valuable for those whose risk is difficult to judge. Coronary artery calcium scanning has become an increasingly accessible way to refine estimates of heart attack and stroke risk. Yet a Northwestern Medicine study involving more than 6,000 adults suggests the quick, relatively inexpensive test [...]
A new image of the Helix Nebula reveals how dying stars return material to the galaxy. The Helix Nebula offers a rare look at what happens after a dying star releases its outer layers into space. New observations show fragments of that material colliding with surrounding gas, breaking apart, and beginning their return to the [...]
An oral GLP-1 drug showed promising weight loss results in a phase II trial. A pill-based approach to GLP-1 treatment helped adults with obesity or overweight lose as much as 12 percent of their body weight over 36 weeks, according to a randomized phase II clinical trial published in Nature Medicine. The study tested aleniglipron, [...]
Researchers achieved the first real-world demonstration of quantum entanglement over a busy telecommunications fiber network. A single photon carrying quantum information had to travel more than 24 kilometers through an optical fiber already crowded with powerful internet signals. Despite the noise, it reached downtown Chicago still entangled with its partner at Northwestern University’s Evanston campus. [...]
An innovative new drone dubbed the “Phantom Twist” can seemingly disappear from view, in a major new robotics advancement offering a close-to-invisible aerial platform.
Its name describes the drone’s rapid spinning motion, which rotates 25 times per second—too fast for the human eye to resolve—thereby acting as a sort of cloak shielding it from visible detection.
The Northwestern University engineering team behind the Phantom Twist revealed their drone during a recent talk at the Sydney, Australia, Robotics: Science and Systems 2026 conference on July 16.
“Most efforts to hide drones focus on making them look like their surroundings,” said Northwestern’s Michael Rubenstein, who led the work. “Instead, we asked whether we could design the drone itself around the way humans perceive motion. This idea of low visibility through persistent motion is something few people have explored.”
Hiding drones is not a new idea. Other engineers have attempted a variety of techniques, including camouflage, transparent materials, and light-bending to obscure the presence of drones and robots. However, all of those focused on the material the drone’s exterior was constructed from, allowing it to blend into the background. The Northwestern team’s innovation was in how the object moves.
To our eyes, fan blades disappear because they are moving so fast that our eyes cannot track them. The “motion blur” created at these speeds allows the Phantom Twist to almost disappear, leaving only a faint apparition perceptible to the eye.
While several military applications are immediately obvious, the team instead says their work could be useful in developing noninvasive wildlife and environmental monitoring. Loud drones can scare wildlife, disrupting them as they scatter, but by blending in, the Phantom Twist could capture a much more accurate picture of natural behaviors.
Their perception-based design eschews the traditional quadcopter design for a single propeller, with a body that spins in the opposite direction, creating the optical illusion that the drone essentially disappears.
“For a typical quadrotor drone, the propellers are spinning, but the robot is stationary,” Rubenstein said. “So, you still see its body. For our drone, the whole thing is rotating, so there are no stationary parts.”
Using AI and optimization algorithms, the Northwestern team began by generating 20,000 different arrangements of a drone’s propeller, motor, circuit board, and other necessary components. Eventually, the algorithm landed on the most promising configurations, after which the researchers simulated and superimposed them onto real-world backgrounds.
Another computer model mimicked human perception, allowing the engineers to assign a perception score for how visible each design would be to human eyes. An algorithm then optimized those designs by moving components to minimize the visibility score even further.
“The design process was fully automated,” Rubenstein said. “Then, when we were confident that a drone met all our criteria, we built it.”
The key feature of this design is that the individual components are at such varying heights and angles that they do not overlap as it spins, maximizing the motion-blur effect and creating the appearance of a faint cloud rather than a solid object.
“The human eye takes time to accumulate signals, roughly analogous to the exposure time of a camera,” said Alexander, an expert in computer vision. “When an object spins quickly, we perceive it as blurring out and losing distinct features. Because this new drone is almost entirely transparent, its few opaque components are visually averaged with the background for an overall appearance of a slight haze.”
Currently impeding the drone from being even more imperceptible to the eye are the wires and support rods that remain visible, as well as the engine noise it produces, which is readily discernible. Going forward, the team plans to continue improving Phantom Twist in future iterations to incorporate more transparent materials and reduce the noise it produces.
Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.
Northwestern University engineers have unveiled an extremely energy-efficient 3D camera, called SpiderCam, inspired by how jumping spiders judge depth before making a calculated leap.
The research team behind the novel device said their technology could help engineers build wearable technologies, assistive devices, robots, drones, and other futuristic technologies that benefit from quickly and efficiently gauging their surroundings.
According to a statement announcing SpiderCam, 3D cameras typically estimate image depth in two ways. The first approach involves captured images from multiple viewpoints and comparing them, and the second involves projecting a light source, often an infrared (IR) laser, and then measuring the reflection.
Although both methods can produce realistic three-dimensional images, they can require significant computing power, additional operational energy, and often expensive hardware such as lasers.
Fortunately, millions of years of evolution have resulted in a creature that possesses a hyper-efficient way of estimating depth: the jumping spider.
“Jumping spiders jump to catch prey, to avoid predators and to get around, and that requires excellent vision,” said Northwestern’s Emma Alexander, the study’s corresponding author and an expert in bio-inspired computer vision. However, the researcher notes that their brains are extremely small, requiring the ability to calculate distances in an energy- and computationally efficient way.
According to Alexander, jumping spider eyes have multiple layers of retinas in each eye, rather than just one as in human eyes. When measuring distance, each retina focuses on an image at a slightly different distance, resulting in some images being blurrier than others.
“They see multiple levels of focus at all times,” Alexander explained. “So, they are always collecting pairs of images.”
After collecting these images in real time, the fly’s poppyseed-sized brain compares their sharpness, yielding a surprisingly accurate depth estimate, as evidenced by the creature’s ability to jump with precision.
Inspired by nature’s hyper-efficient, extremely accurate depth estimation method, Alexander’s team decided to build a 3D camera using the same basic approach.
“We wanted to understand whether we could borrow some of the same principles to create an extremely energy-efficient depth sensor that could be used in resource-constrained situations where users don’t have unlimited access to power,” Alexander explained.
Instead of capturing images at multiple distances, as the jumping spider’s eye does, the Northwestern team’s initial design captures two images of the same scene at different focal lengths. Next, the system uses a custom algorithm to analyze the sharpness of the edges and textures captured in each image. The team said this analysis acts as a “translator between blur and distance” in the fly’s brain, resulting in “depth measurements in real time.”
To best approximate the naturally evolved energy efficiency of a jumping spider’s eye, Alexander’s team built the algorithm directly into a customizable computer chip specifically optimized for energy efficiency called a field-programmable gate array (FPGA).
The final prototype integrating the team’s dual-lens system generates depth maps at 32.5 frames per second. Critically, it generates this level of accurate 3D maps while consuming 624 milliwatts of power. For comparison, the team notes that 624 milliwatts is “less energy than used by a standard nightlight.”
Although the team said that the current version of the SpiderCam is the “first passive FPGA-based 3D camera system to operate below one watt,” they hope to improve its optics and expand its field of view. Once they have a commercial-grade version, the team hopes to integrate SpiderCam into wearable devices and small robots.
Beyond proposed applications, the Northwestern team said that they “envision” a future, ultra-energy-efficient version of the chip capable of “bringing 3D vision to applications where conventional depth sensors are impractical.”
“I’m very interested in settings where you’re very resource constrained and can’t just plug a camera into a wall,” Alexander explained. “For example, it could be deployed in field settings with limited power.”
“Separately, I also think it’s particularly exciting for applications like augmented reality where you’re interfacing with the physical world and need to know the locations of objects around you,” the researcher added.
The study’s co-first authors, Marcos Ferreira and Tianao Li, presented this work at the Computer Vision Foundation’s Conference on Computer Vision and Pattern Recognition (CVPR) in Denver. Complimentary registration is available for members of the media.
Christopher Plain is a Science Fiction and Fantasy novelist and Head Science Writer at The Debrief. Follow and connect with him on X, learn about his books at plainfiction.com, or email him directly at christopher@thedebrief.org.
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