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Imaging hidden objects with consumer LiDAR via motion-induced sampling
Siddharth Somasundaram1, Aaron Young2, Akshat Dave2
1Massachusetts Institute of Technology, Cambridge, MA, USA. sidsoma@media.mit.edu.
Nature
|May 20, 2026
Summary
Researchers developed a new method to enable non-line-of-sight (NLOS) imaging using consumer-grade Light-Detection and Ranging (LiDAR) devices. This breakthrough allows everyday users to capture images of hidden objects with affordable, off-the-shelf technology.
Area of Science:
- Computer Vision
- Optics
- Robotics
Background:
- Consumer Light-Detection and Ranging (LiDAR) sensors are increasingly used in various applications.
- Existing LiDAR technology faces challenges in non-line-of-sight (NLOS) imaging due to signal quality, motion, and resolution limitations.
Purpose of the Study:
- To develop a method for achieving NLOS imaging using consumer-grade LiDAR devices.
- To overcome the limitations of current consumer LiDAR for imaging hidden objects.
Main Methods:
- Proposed a multi-frame fusion strategy to enhance signal quality.
- Introduced a motion-induced aperture sampling model to unify object and camera motion effects.
- Utilized smartphone-grade LiDAR for demonstrations.
Main Results:
- Successfully demonstrated NLOS imaging capabilities on consumer LiDAR.
- Achieved three-dimensional reconstruction, object tracking, and camera localization using hidden objects.
- Showcased plug-and-play NLOS imaging with affordable, off-the-shelf hardware.
Conclusions:
- The developed method democratizes NLOS imaging, making it accessible for consumer applications.
- This advancement shifts NLOS imaging from specialized research hardware to readily available consumer devices.
- The findings pave the way for broader adoption of NLOS imaging in handheld, wearable, and robotic systems.
