Occupancy Grid Map Merging Using Feature Maps

Abstract

Multi-robot exploration and mapping studies have demonstrated that it is often more efficient to explore unknown areas in parallel rather than with a single agent. However, the question of how to integrate individual maps into a consistent global map remains an open research area. This problem, known as map merging, comprises the establishment of a frame of reference for multiple mobile robots, the identification of regions of map overlap, and the integration of individual maps to produce a global result. In this work, we build a hybrid map which integrates occupancy grid and feature data to solve this problem. This integrated representation permits fast and effective map merging. Experimental results are presented that demonstrate algorithm performance in a realistic scenario.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2010
Accession Number
ADA556018

Entities

People

  • Greg Hudas
  • James Overholt
  • Mark J. Paulik
  • Mohan Krishnan
  • Yasser Alnounou

Organizations

  • United States Army Tank Automotive Research, Development and Engineering Center

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Autonomous Navigation
  • Cartography
  • Computational Complexity
  • Computational Science
  • Engineering
  • Identification
  • Information Systems
  • Motion Planning
  • Multiagent Systems
  • Navigation
  • Probability
  • Robot Mapping
  • Robot Navigation
  • Robots
  • Software Development

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Vision.

Technology Areas

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