Researchers at Stony Brook University have introduced a navigation system that enables robots to detect objects around corners using commercially available, lightweight sensors. The team presented their findings at ICRA 2025, demonstrating potential applications for improved safety in autonomous robots, self-driving vehicles, and delivery systems in complex environments.
The research utilizes single-photon LiDAR technology, which can sense minimal traces of light reflected from hidden areas. Akshat Dave, assistant professor of Computer Science at Stony Brook and former Postdoctoral Associate at MIT Media Lab, explained the concept: “We asked ourselves, what if a robot could use walls the same way — by turning walls into mirrors?” He added that convex mirrors at blind intersections inspired the approach.
Dave further stated: “We want to take this project beyond navigation, to challenges that pose real Non-Line-of-Sight problems, like teaching robots to lift hidden objects, exploring and mapping unreachable areas, and conducting search and rescue operations. These systems will be able to see the world in ways we do not.”
The project is titled Enhancing Autonomous Navigation by Imaging Hidden Objects using Single-Photon LiDAR. It is funded by the National Science Foundation (CMMI-2153855) and the NSF Graduate Research Fellowship.
More details are available on the AI Innovation Institute website.