Publication:
Development of Deterministic Artificial Intelligence for Unmanned Underwater Vehicles (UUV)

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Authors
Sands, Timothy
Subjects
UUV
AUV
ROV
hydrodynamics
navigation system
dynamic positioning
underwater robotics
navigation
tracking
artificial intelligence
learning
physics
mathematics
stochastic
non-stochastic
deterministic
DAI
Advisors
Date of Issue
2020
Date
2020
Publisher
MDPI
Language
en_US
Abstract
The major premise of deterministic artificial intelligence (D.A.I.) is to assert deterministic self-awareness statements based in either the physics of the underlying problem or system identification to establish governing differential equations. The key distinction between D.A.I. and ubiquitous stochastic methods for artificial intelligence is the adoption of first principles whenever able (in every instance available). One benefit of applying artificial intelligence principles over ubiquitous methods is the ease of the approach once the re-parameterization is derived, as done here. While the method is deterministic, researchers need only understand linear regression to understand the optimality of both self-awareness and learning. The approach necessitates full (autonomous) expression of a desired trajectory. Inspired by the exponential solution of ordinary differential equations and Euler�s expression of exponential solutions in terms of sinusoidal functions, desired trajectories will be formulated using such functions. Deterministic self-awareness statements, using the autonomous expression of desired trajectories with buoyancy control neglected, are asserted to control underwater vehicles in ideal cases only, while application to real-world deleterious effects is reserved for future study due to the length of this manuscript. In totality, the proposed methodology automates control and learning merely necessitating very simple user inputs, namely desired initial and final states and desired initial and final time, while tuning is eliminated completely.
Type
Article
Description
The article of record as published may be found at�https://doi.org/10.3390/jmse8080578
Series/Report No
Department
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funder
Format
24 p.
Citation
Sands, Timothy. "Development of deterministic artificial intelligence for unmanned underwater vehicles (UUV)."�Journal of Marine Science and Engineering�8.8 (2020): 578.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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