Endurance Extension Of Oceanographic Sensor Platforms Through Crowdsourced, Optimized Path Planning Algorithms

Abstract

Endurance Extension Of Oceanographic Sensor Platforms Through Crowdsourced, Optimized Path Planning Algorithms;(1) Investigate public oceanographic data sets such as the Argo repository for suitability for using statistical approaches such as machine learning to develop optimized path planning algorithms for the sensor platforms that produce it, with a specific goal of extending the endurance of these platforms.(2) Develop a structure for an online virtual competition that encourages and enables participants (primarily university engineering students) to perform a similar analysis and develop and test their own algorithms for optimized path planning and platform life extension.(3) Provide the opportunity to aggregate the decisions of the diverse group of competitors into measures of possible maximum optimized longevity of underwater sensor platforms (the best that can be expected from intelligent planning in the dynamic ocean environment), thus capitalizing on the wisdom of the crowd.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 11, 2020
Source ID
N000142012678

Entities

People

  • Zoz Brooks

Organizations

  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Economics
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms