A new system combines sonar and image-matching algorithms to help underwater vehicles navigate through murky waters by providing real-time mapping, enhancing safety and efficiency in seafloor operations.
<p>When remotely operated vehicles settle on the seafloor or dig through a sand bed, they can kick up clouds of sediment that onboard cameras struggle to see through. Often, the only thing to do is wait until the dust settles. But a new system developed by Amy Phung, SM ’23, PhD ’26, and her advisor Richard Camilli, SM ’00, PhD ’03, of the Woods Hole Oceanographic Institution (WHOI), offers a solution. </p>
<p>In this technique, the vehicle first uses sonar to quickly map its surroundings. That technology doesn’t provide detailed resolution, but it works equally well in cloudy and clear water. And it allows a vehicle to safely get close enough to specific objects for cameras to visualize them more carefully. To speed up the processing so the mapping can be done in real time, the researchers combined the sonar tech with an image-matching algorithm developed by researchers in France that quickly estimates the relative depth of each pixel in a 2D scene.</p>
<p>“An analogy would be if you were to go into a china shop in the dark, and try to pick your way around to find a specific coffee mug without knocking things over,” Camilli says of their new technique. “This would allow you to do that.” He and Phung say applications could include scientific exploration, underwater construction and maintenance, and handling of unexploded undersea mines. </p>
# Seeing through murky waters
Source: [https://www.technologyreview.com/2026/08/25/1140955/seeing-through-murky-waters](https://www.technologyreview.com/2026/08/25/1140955/seeing-through-murky-waters)
When remotely operated vehicles settle on the seafloor or dig through a sand bed, they can kick up clouds of sediment that onboard cameras struggle to see through\. Often, the only thing to do is wait until the dust settles\. But a new system developed by Amy Phung, SM ’23, PhD ’26, and her advisor Richard Camilli, SM ’00, PhD ’03, of the Woods Hole Oceanographic Institution \(WHOI\), offers a solution\.
In this technique, the vehicle first uses sonar to quickly map its surroundings\. That technology doesn’t provide detailed resolution, but it works equally well in cloudy and clear water\. And it allows a vehicle to safely get close enough to specific objects for cameras to visualize them more carefully\. To speed up the processing so the mapping can be done in real time, the researchers combined the sonar tech with an image\-matching algorithm developed by researchers in France that quickly estimates the relative depth of each pixel in a 2D scene\.
“An analogy would be if you were to go into a china shop in the dark, and try to pick your way around to find a specific coffee mug without knocking things over,” Camilli says of their new technique\. “This would allow you to do that\.” He and Phung say applications could include scientific exploration, underwater construction and maintenance, and handling of unexploded undersea mines\.
MIT Lincoln Laboratory is developing algorithms and hardware for human-AUV teaming to improve underwater navigation and perception in murky conditions for military missions.
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CogSENet introduces a blind image deblurring framework inspired by eagle vision, using semantic-aware modules and frequency decomposition to improve restoration quality and structural fidelity, outperforming state-of-the-art methods.