Projects

New machine learning methods capture statistical features within sonar data to distinguish between sound sources.

New navigation and vehicle autonomy algorithms consider which tasks humans and autonomous systems respectively do best, with the goal of improving search path planning and object classification in underwater environments.

With the goal of enabling navigation in environments where GPS is unavailable or unreliable, researchers are developing algorithms to fuse information across a network of small, low-power radio-frequency devices.

Undersea vision-based navigation and pose determination will enable divers and robots to collaboratively solve complex tasks in an inherently unstructured environment.

An aging weatherproof enclosure protecting one of the space surveillance radars on Kwajalein Atoll is replaced.

Robust, trustworthy, and safe machine learning algorithms that operate in resource-constrained environments will improve missile defense and other target recognition and mission planning systems.

A deployable navigation network of small, low-cost radio transponders can help track the locations of first responders during rescue operations.

A small, low-cost system that leverages long-length fibers embedded with electronics could provide persistent monitoring of the undersea environment.

We are developing a sensor network to improve our understanding and monitoring of sea ice breakup in the rapidly changing Arctic region.

We developed new distributed coordination algorithms for deploying multiple autonomous systems from a single set of operator commands.