Sensor Network-Mediated Multi-Robot Task Allocation

Abstract

We address the Online Multi-Robot Task Allocation (OMRTA) problem. Our approach relies on a computational and sensing fabric of networked sensors embedded into the environment. This sensor network acts as a distributed sensor and computational platform which computes a solution to OMRTA and directs robots to the vicinity of tasks. We term this Distributed In-Network Task Allocation (DINTA). We describe DINTA, and show its application to multi-robot task allocation in simulation, laboratory, and field settings. We establish that such network-mediated task allocation scales well, and is especially amenable to simple, heterogeneous robots.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2005
Accession Number
ADA575682

Entities

People

  • Gaurav S. Sukhatme
  • Maxim A. Batalin

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Autonomous Navigation
  • Computations
  • Computer Science
  • Detectors
  • Embedded Systems
  • Energy Consumption
  • Environment
  • Navigation
  • Networks
  • Probability
  • Probability Distributions
  • Robot Navigation
  • Robotics
  • Robots
  • Sensor Networks
  • Simulations

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Marine Ecological Systems Migration
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control