Maritime Search and Rescue via Multiple Coordinated UAS

Abstract

The advent of Unmanned Aerial Systems (UAS) has created opportunities for expensive capital assets to be replaced by these small, yet capable, platforms. Tasks that are identified as able to be performed by UAS may also benefit from the ability of a collection of UAS to operate in a cooperative and parallel manner. Parallelization also means that several parts of the search area can be covered at the same time, reducing the overall task completion time. In this paper we investigate how to divide the maritime search and rescue task in a way that it can be performed by a set of UAS. Our investigation covers the detection of multiple mobile objects by a heterogeneous collection of UAS. Three methods (two that are not informed by object location probabilities and one that is) for dividing the space are proposed, and their relative strengths and weaknesses investigated. To facilitate simulation a model for object detection by an aerial camera is proposed. The topic is approached holistically to account for contingencies such as airspace deconfliction. Results are produced using simulation to verify the capability of the proposed method and to compare the various partitioning methods. Results from this simulation show that great gains in search efficiency can be made when the search space is partitioned using a method based on object location probability. For search areas of 3km x 3km detection probability gains of 40 percent are achievable. For larger areas these gains can approach 80 percent.

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Document Details

Document Type
Technical Report
Publication Date
Jun 12, 2017
Accession Number
AD1035043

Entities

People

  • Dieter W. Schuldt
  • Joel A. Kurucar

Organizations

  • MIT Lincoln Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Aspect Ratio
  • Coast Guard
  • Cognitive Systems Engineering
  • Collision Avoidance Systems
  • Detection
  • Normal Distribution
  • Probability
  • Probability Distributions
  • Search And Rescue
  • Simulations
  • Standards
  • United States
  • Unmanned Aerial Systems
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Operations Research
  • Systems Analysis and Design
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy
  • Autonomy - UAVs
  • Space
  • Space - Space Objects