Implementation of a Multi-Robot Coverage Algorithm on a Two-Dimensional, Grid-Based Environment

Abstract

With the development and advancement in the technology of control and multi-robot systems, robot agents are likely to take over mine countermeasure (MCM) missions one day. The path planning coverage algorithm is an essential topic for research; the combination of an efficient algorithm and accurate sensors can save time and human lives. The objective of this work is to implement a path planning coverage algorithm for a multi-robot system in a two-dimensional, grid-based environment. We assess the applicability of a topology-based algorithm to the MCM mission. First, we provide an overview of multi-robot coverage algorithms. Second, we select one algorithm, analyze it, and test its performance. Then the algorithm is evaluated in nine experiments using different numbers of robots and obstacles. Finally, the results are assessed by how much time the steps took and how many free points are not visited when the algorithm is finished. The outcome indicates that efficiency decreases as the number of robots or obstacles increases. This thesis concludes with recommendations for ways to improve the efficiency of the algorithm as well as how to perform the experiments cost effectively in a real environment.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2017
Accession Number
AD1046411

Entities

People

  • Jo-wen Huang

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Autonomous Underwater Vehicles
  • Collision Avoidance
  • Control Systems
  • Efficiency
  • Environment
  • Monte Carlo Method
  • Motion Planning
  • Navigation
  • Robotic Swarms
  • Robotics
  • Robots
  • Simulations
  • Simulators
  • Topology
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Critical Infrastructure Protection in CBRN and WMD Threats.
  • Distributed Systems and Data Platform Development
  • Systems Analysis and Design

Technology Areas

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