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Autonomous Lunar Rover Localization while Fully Scanning a Bounded Obstacle-Rich Workspace.

Jonghoek Kim1

  • 1System Engineering Department, Sejong University, Seoul 05006, Republic of Korea.

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|October 16, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel scanning path strategy for a three-rover team exploring dark outer space. The method ensures complete workspace coverage without detection holes while managing rover localization errors by periodically returning to a known base station.

Keywords:
Lidarbase stationcoverage path plandark outer space roverlocation estimate fixrover localizationscanning path planspace robot

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Area of Science:

  • Robotics and Autonomous Systems
  • Space Exploration Technology
  • Path Planning Algorithms

Background:

  • Outer space exploration presents unique challenges, including darkness and lack of satellite navigation.
  • Rover teams require robust strategies for autonomous exploration and accurate localization in unknown environments.
  • Simultaneous camera and light activation is necessary for rovers to scan limited, dark spaces.

Purpose of the Study:

  • To develop a scanning path plan strategy for a multi-rover team in unknown, dark outer space environments.
  • To ensure complete coverage of a bounded, obstacle-rich workspace without detection holes.
  • To address and bound the accumulating localization error of a lead rover (hauler) in the absence of Global Navigation Satellite System (GNSS).

Main Methods:

  • A three-rover team configuration is proposed, with one hauler rover responsible for localization using stereo cameras and Inertial Measurement Unit (IMU).
  • Other rovers follow the hauler, relying on its localization.
  • Localization error is corrected by the hauler periodically returning to a known base station and using Lidar for relative positioning.

Main Results:

  • The proposed strategy enables a rover team to fully scan a bounded, obstacle-rich workspace.
  • The scanning process ensures no detection holes remain.
  • The hauler's localization error is effectively bounded through periodic returns to the base station.
  • Simulations in MATLAB demonstrate the efficacy of the scanning and localization strategy.

Conclusions:

  • The developed scanning path plan strategy allows for efficient and complete exploration of challenging outer space environments by rover teams.
  • The novel approach successfully integrates full workspace coverage with robust localization error management.
  • This research contributes a viable solution for autonomous deep space exploration missions requiring precise mapping and navigation.