Scientists have developed a new 3D camera inspired by the vision system of jumping spiders. These new cameras use less than one watt of power and could help enable battery-powered robots, drones, wearable devices and other technologies that need to understand their surroundings.
SpiderCam: A Bio-Inspired Depth Sensor
The camera, called SpiderCam, was developed by researchers led by Emma Alexander at Northwestern University. The team presented the technology earlier this month at the Conference on Computer Vision and Pattern Recognition in Denver, Colorado.
According to a Popular Science report, the SpiderCam is based on how jumping spiders estimate distances. Unlike humans, who have a single retina in each eye, jumping spiders have multiple retinal layers that capture the same scene at different focal levels. By comparing these differences in sharpness, the spiders can determine how far away objects are using very little brainpower.
In a statement, Emma Alexander, a computer scientist at Northwestern University, explained, “They [spiders] see multiple levels of focus at all times. So, they are always collecting pairs of images. Then, their brains could compare these differences in sharpness to judge distance.”
Researchers used the same principle to create a depth-sensing camera designed for environments with limited power availability. “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, who is also a bio-inspired computer vision expert, added.
How the SpiderCam Works and Its Potential Use in Robots, Drones and Wearables
SpiderCam captures two versions of the same image with slightly different focus settings. A custom algorithm then compares blur differences between the images and converts that information into real-time depth measurements.
The algorithm runs on a customizable computer chip designed for energy-efficient processing. According to the researchers, the prototype generates depth maps at 32.5 frames per second while consuming just 624 milliwatts of power, which is less than a watt.
The low-power approach differs from many existing 3D camera systems, which often require additional hardware, greater computational resources and higher energy consumption to estimate depth. The research team believes the technology could be useful in devices that need to map and navigate their environments while operating on battery power.
“I’m very interested in settings where you’re very resource constrained and can’t just plug a camera into a wall. 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,” Alexander noted.
Researchers said the technology could eventually be integrated into assistive devices, wearable technologies, robots and drones. The team plans to continue refining the system and exploring its use in compact robotic platforms and wearable devices in future development efforts.
