Optimizing Systems with Conflicting Objectives Competing for a Limited Resource- Resubmission

Abstract

Decentralized and distributed autonomous sensing and control methods for networked sensor systems have many applications in surveillance, Internet of Things (IoT), autonomous cars, and UAV swarms. These decentralized autonomy methods are especially challenging when the network connecting the sensors is time varying. Moreover, when the network is large with 10s or even 100s of sensors connected, decision making for sensor resource management (e.g., decisions on sensor mobility - sensors mounted on UAVs) becomes computationally intensive, in fact, the complexity is exponential in the decision space and the number of sensors. To address these challenges, we developed an optimization framework called COLRO to optimize the limited sensing resources in a time-varying networked sensor system for a target tracking applicationwhile minimizing the computational effort.

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Document Details

Document Type
Technical Report
Publication Date
Dec 14, 2021
Accession Number
AD1155242

Entities

People

  • Hans D. Mittelmann

Organizations

  • Arizona State University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • C4I
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Collision Avoidance
  • Communication Systems
  • Computational Complexity
  • Control Systems
  • Detectors
  • Electrical Engineering
  • Internet Of Things
  • Motion Planning
  • Multiple Access
  • Multitarget Tracking
  • Random Variables
  • Signal Processing
  • Statistical Sampling
  • Unmanned Aerial Vehicles
  • Unmanned Vehicles
  • Wireless Communications

Fields of Study

  • Computer science

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Computer Networking
  • Systems Analysis and Design

Technology Areas

  • 5G
  • 5G - Internet of Things
  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers