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Robot-Beacon Distributed Range-Only SLAM for Resource-Constrained Operation.

Arturo Torres-González1, Jose Ramiro Martínez-de Dios2, Anibal Ollero3

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Summary
This summary is machine-generated.

This study introduces a cooperative Range-Only Simultaneous Localization and Mapping (RO-SLAM) system where sensor nodes actively participate. This approach enhances accuracy and efficiency for resource-constrained robots and sensor networks.

Keywords:
SLAMrobot-sensor network cooperationsensor networks

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Area of Science:

  • Robotics
  • Sensor Networks
  • Simultaneous Localization and Mapping (SLAM)

Background:

  • Existing Range-Only SLAM methods often treat sensor nodes (beacons) as passive, neglecting their capabilities.
  • Simultaneous Localization and Mapping is computationally intensive and faces resource limitations in many applications.
  • Resource constraints in robots and sensor nodes necessitate efficient SLAM algorithms.

Purpose of the Study:

  • To develop a scalable, distributed RO-SLAM scheme for resource-constrained environments.
  • To enhance SLAM accuracy by enabling robot-beacon cooperation.
  • To manage resource consumption by setting a bound on integrated measurements per iteration.

Main Methods:

  • A Sparse Extended Information Filter (SEIF) SLAM approach is employed.
  • Beacons actively gather and integrate robot-beacon and inter-beacon measurements.
  • A distributed, information-driven measurement allocation tool dynamically selects measurements to balance accuracy and resource use.

Main Results:

  • The proposed scheme achieves significant estimation accuracies.
  • Demonstrates high resource-consumption efficiency and scalability.
  • Experimental validation on an octocopter Unmanned Aerial System (UAS) in 3D outdoor environments showed robustness and advantages over existing methods.

Conclusions:

  • The cooperative, distributed RO-SLAM scheme effectively addresses resource constraints.
  • Beacon participation in measurement selection, gathering, and integration improves SLAM performance.
  • The system offers a robust and scalable solution for real-world applications, particularly on Unmanned Aerial Systems.