Boltzmann Entropy for Undersea Terrain Aided Navigation
Abstract
The ability to navigate accurately without Global Positioning Systems (GPS) or beacon systems remainsan elusive yet important capability for unmanned systems. Reliance on external beacon systems, like GPSand long baseline, create system vulnerabilities if those beacon systems are damaged or removed. Thisresearch explores the ability to improve Undersea Terrain Aided Navigation (UTAN) with respect tocoverage path planning and creates a robust coverage path planning algorithm utilizing a new paradigm inconfiguration entropy. It highlights a classic challenge in the path planning problem between explorationand exploitation. Exploration ensures complete coverage of the region, while exploitation utilizes terrainfeatures to reduce positional uncertainty of the Autonomous Underwater Vehicle (AUV). Using stochasticestimates of the vehicle location and map accuracy, it is possible to combine the variances of each togetherwith exploration and exploitation policies to develop a coverage plan for UTAN. To do so requiresdevelopment of a terrain entropy measure to influence the path planning algorithm. The thesis presents anew entropy measure that is a key architectural component for an information-theoretic framework todevelop near-optimal paths for the AUV coverage problem.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2020
- Accession Number
- AD1114637
Entities
People
- Jason Cash
Organizations
- Naval Postgraduate School