A Novel Particle Filter Based SLAM Algorithm for Lunar Navigation and Exploration

Nu Nu Win, Kazuki Kida, Matsuhiro Ko, Suzuki Jiei, Sarah Cosentino, Hiroyuki Ishii, Atsuo Takanishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents a simultaneous localization and mapping (SLAM) system for lunar exploration. The proposed SLAM algorithm presents a significantly lower computational complexity compared to the state-of-the-art solutions, due the use of a Rao-Blackwellised particle filter with adaptive and compound resampling. The proposed SLAM sensor system consists of one light detecting and ranging sensor (LIDAR) and one IMU, to minimize illumination-dependent errors; as the lunar environment, and in particular the target exploration region around the Marius Hills hole, presents very variable illumination conditions. The system was tested via simulation, using existing environmental data from the mare tranquillitatis pit crater.

Original languageEnglish
Title of host publication2019 4th International Conference on Robotics and Automation Engineering, ICRAE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages74-78
Number of pages5
ISBN (Electronic)9781728147406
DOIs
Publication statusPublished - 2019 Nov
Event4th International Conference on Robotics and Automation Engineering, ICRAE 2019 - Singapore, Singapore
Duration: 2019 Nov 222019 Nov 24

Publication series

Name2019 4th International Conference on Robotics and Automation Engineering, ICRAE 2019

Conference

Conference4th International Conference on Robotics and Automation Engineering, ICRAE 2019
CountrySingapore
CitySingapore
Period19/11/2219/11/24

Keywords

  • lunar exploration
  • particle filter
  • resampling
  • rover
  • SLAM

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Control and Optimization

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