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Decentralized Online Simultaneous Localization and Mapping for Multi-Agent Systems.

Andrés C Jiménez1,2, Vicente García-Díaz3, Rubén González-Crespo4

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This study introduces a decentralized Simultaneous Localization and Mapping (SLAM) system using wireless agents. This approach reduces memory and processing demands for robotic agents in new environments.

Keywords:
intelligent robotsmobile agentsmulti agent systemssimultaneous localization and mappingwireless sensor networks

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Robotic agents require environmental maps and self-localization for planning tasks.
  • Simultaneous Localization and Mapping (SLAM) is crucial for robots in unknown environments.
  • Traditional SLAM systems face challenges with memory, processing, energy, and cost.

Purpose of the Study:

  • To design a decentralized SLAM system to overcome limitations of centralized approaches.
  • To reduce memory and processing requirements for robotic agents during mapping.

Main Methods:

  • A decentralized SLAM system utilizing a network of wireless agents.
  • Agents collaboratively store and distribute map data as it's generated.
  • Implementation and validation in a 25 m² test environment.

Main Results:

  • Successful online generation of a topological map.
  • The system operated without reliance on external processing units.
  • Demonstrated reduced memory and processing load compared to traditional SLAM.

Conclusions:

  • Decentralized SLAM using wireless agents is a viable solution for robotic navigation.
  • The proposed system effectively addresses memory and processing constraints in SLAM.
  • This approach offers a cost-effective and energy-efficient alternative for robotic mapping.