CAMBRIDGE, MA – Teledyne Gavia, a global leader in the manufacture of autonomous underwater vehicles (AUVs), has introduced Charles River Analytics’ AutoTRap Onboard™ AI-based object detection software as a new capability onboard their Gavia marine vehicles. As underwater operations become more complex and dangerous, AI tech has emerged as the clear solution for delivering the consistent and accurate results that have proven elusive until now due to the challenges of ever-changing marine environments. Enter AutoTRap Onboard—a smart, real-time automated target recognition (ATR) app offered by Charles River Analytics.
The new partnership with Teledyne Gavia expands the boundaries for underwater unmanned sonar operation. Now, operators can acquire Teledyne Gavia’s best-in-class 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.”
In environments that are challenging for target detection, 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.
AI software must perform as expected despite constant variations in the deployment environment. AutoTRap Onboard has been designed with a versatile architecture that is robust across different environments, new sensor types, and changing mission goals.
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 imag
AutoTRap is part of the rich suite of ATR products offered by Charles River Analytics.
“Our commercial partners and customers—like Teledyne GAVIA—have various autodetection and recognition needs. Some must locate and classify objects on the seafloor (e.g., shipping containers lost at sea), while others must find or track objects on the ground, in the sky, or in space,” explained Dr. Elaine B. Coleman, Vice President of Commercialization at Charles River Analytics. To detect the wide range of objects relevant to ocean surveys, AutoTrap Onboard can learn new objects by training on new target profiles as they are added to the Target Library.
Charles River Analytics develops leading-edge software by combining agile innovation with robust engineering, applying experience derived from decades of designing solutions for austere environments. Our ATR app is developed, integrated, and deployed on market-leading AUVs offered by Teledyne Gavia. Customers can now leverage our joint expertise.
Contact Elaine Coleman at Charles River or Melissa Rossi at Teledyne for more information.
Teledyne Gavia provides turnkey survey solutions for military, commercial, and scientific applications. The Gavia AUV carries an array of sensors and custom payload modules, making it perfect for monitoring or surveillance tasks where autonomy, cost, and ease of deployment matter. Its modular design allows for rapid sensor reconfiguration and battery replacement.
Charles River Analytics
Charles River Analytics uniquely combines agile innovation and leading-edge research with a decades-long track record of hardened engineering in austere environments to create best-in-class solutions to diverse, challenging problems.