New Wave Media

September 21, 2020

Next-Gen AI Capability for Teledyne Gavia AUVs

Teledyne Gavia introduced Charles River Analytics’ AutoTRap Onboard AI-based object detection software as a new capability onboard its Gavia marine vehicles. 

AI has emerged as a solution for delivering consistent and accurate results for underwater vehicles, led by developments such as AutoTRap Onboard, designed to be a smart, real-time automated target recognition (ATR) app offered from Charles River Analytics.

The new partnership with Teledyne Gavia expands the boundaries for underwater unmanned sonar operation. Now, operators can acquire Teledyne Gavia’s unmanned underwater vehicles with AutoTRap Onboard software inside.

"AutoTRap Onboard automatically detects and identifies target objects in real time,” said Dr. Arjuna Balasuriya, Senior Scientist at Charles River Analytics. “This product saves time and money— operators don’t have to bring the vehicle to the surface, download its data, and then send it back down for further investigation (if necessary). With Teledyne Gavia, we offer our customers a better experience, giving them confidence that the area is clear and it’s safe to operate.”

Bob Melvin, Vice President of Engineering at Teledyne Marine Systems, added, “Our customers have been asking us for a reliable way to carry out seafloor surveys, such as mine hunting. AutoTRap Onboard makes finding these targets of interest much easier and builds higher levels of confidence in AI systems.”

AutoTRap Onboard has demonstrated excellent detection rates and false positive rates; identifying truncated conical objects on a rocky volcanic seafloor with a 90% probability of detection. AutoTRap Onboard includes:

  • Target Detector and Target Classifier – Novel machine learning algorithms that process sonar images to detect, classify, and localize targets of interest.
  • Target Library – Collection of trained targets. The Target Detector searches for these targets in the sonar image.

Read an "AUV Case Study" here: https://www.marinetechnologynews.com/news/study-marine-roboticists-turning-604888



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