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Updated: Aug 2, 2025

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
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REALMS: Resilient exploration and lunar mapping system.

D van der Meer1, L Chovet1, A Bera1

  • 1Space Robotics (SpaceR) Research Group, Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg City, Luxembourg.

Frontiers in Robotics and AI
|April 17, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a resilient lunar mapping system for semi-autonomous robots. It enhances exploration efficiency and system robustness through multi-rover coordination and advanced mapping techniques.

Keywords:
VSLAMdelay invariantexplorationlunarmappingmulti-masterresilience

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Area of Science:

  • Robotics and Space Exploration
  • Artificial Intelligence
  • Geospatial Information Science

Background:

  • Space resource utilization, including lunar water ice and oxygen extraction, is driving new space programs like ARTEMIS.
  • Moon exploration requires highly autonomous robots for efficiency and reduced Earth-based control.
  • Multi-robot systems enhance mission success through increased resilience, robustness, and redundancy.

Purpose of the Study:

  • To introduce the Resilient Exploration and Lunar Mapping System (REALMS).
  • To develop a scalable architecture for semi-autonomous lunar mapping using multiple rovers.
  • To implement resilience mechanisms for robust lunar exploration.

Main Methods:

  • Leveraging Visual Simultaneous Localization and Mapping (VSLAM) techniques on multiple rovers.
  • Implementing resilience mechanisms: two-agent redundancy, delay-invariant communications, multi-master architecture, and varied control modes.
  • Testing and validation in a lunar analogue facility and during the ESA Space Resources Challenge.

Main Results:

  • Demonstrated the efficiency of REALMS with two robots in mapping lunar environments.
  • Showcased the system's scalability for larger numbers of robots, increasing map coverage and redundancy.
  • Validated the system's performance in realistic lunar analogue conditions.

Conclusions:

  • REALMS provides an efficient solution for semi-autonomous lunar mapping.
  • Multi-robot systems significantly benefit lunar exploration through enhanced resilience and redundancy.
  • The developed system supports the advancement of robotic capabilities for future space missions.