NURP: Stochastic inference and optimization for UUV guidance and control
Abstract
Improved autonomy of unmanned undersea vehicles (UUVs) is an important component of the mission of the Office of Naval Research (ONR). The undersea environment presents unique challenges compared to aerial environments, with particular limitations on the type of signals that can be received. These unique limitations prevent many of the advances on unmanned aerial vehicles (UAVs) from directly transferring to the UUV case. Lack of available data is a particularlysalient challenge which may be ameliorated by algorithms for collaborative systems of UUVs. This project will devise novel stochastic inference and data assimilation algorithms for automated control of distributed networks of UUVs. The mathematical tools involve stochastic inference algorithms and optimization techniques for computing optimal solution trajectories for datainformed objectives. Algorithms for network communication to accelerate completion of anobjective or goal is also under the scope of this project. Data from real UUV and related networks will be collected in order to test, hone, validate, and ultimately demonstrate the guidance algorithms developed in this project.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 07, 2019
- Source ID
- N000141912046
Entities
People
- Akil C. Narayan
Organizations
- Office of Naval Research
- United States Navy
- University of Utah