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A Review on Map-Merging Methods for Typical Map Types in Multiple-Ground-Robot SLAM Solutions.

Shuien Yu1, Chunyun Fu1, Amirali K Gostar2

  • 1State Key Laboratory of Mechanical Transmissions, School of Automotive Engineering, Chongqing University, Chongqing 400044, China.

Sensors (Basel, Switzerland)
|December 10, 2020
PubMed
Summary
This summary is machine-generated.

Map merging is crucial for multi-robot simultaneous localization and mapping (SLAM). This review classifies and elaborates on map-merging methods for occupancy grid, feature-based, and topological maps to guide future solutions.

Keywords:
feature-based mapmap mergingmulti-robot SLAMoccupancy grid maptopological map

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Vision

Background:

  • Multi-robot systems require integrated environmental representations.
  • Simultaneous Localization and Mapping (SLAM) is essential for robot navigation.
  • Merging local maps from individual robots improves global map accuracy.

Purpose of the Study:

  • To review and classify map-merging methods for multi-robot SLAM.
  • To analyze common map types: occupancy grid, feature-based, and topological maps.
  • To provide guidance for future multi-robot SLAM development.

Main Methods:

  • Classification of map-merging approaches based on mechanism and features.
  • Elaboration on the concepts and characteristics of various map-merging techniques.
  • Review of methods applicable to occupancy grid, feature-based, and topological maps.

Main Results:

  • Identified key map-merging methods for different map representations.
  • Categorized approaches by their underlying principles and feature handling.
  • Detailed explanation of the strengths and weaknesses of each method.

Conclusions:

  • Effective map merging is critical for successful multi-robot SLAM.
  • Understanding different map-merging strategies is vital for system performance.
  • This review offers a foundational resource for researchers and developers in multi-robot mapping.