Mobility Performance Characterization of Transformable Nano Rover for Lunar Exploration

In January 2024, a Japanese lunar lander successfully touched down on the moon as part of the Smart Lander for Investigating Moon (SLIM) mission. Accompanying the SLIM on its journey were two small rovers named lunar excursion vehicles (LEV-1 and 2). LEV-2, a transformable nano rover, was particularly designed to capture images of the SLIM on the lunar surface. During the mission, LEV-2 successfully maneuvered and captured images of the lander. Understanding the mobility characteristics of LEV-2 was crucial for the success of this task. This study analyzed the mobility characteristics of LEV-2 through numerical simulation and traveling tests. In the numerical simulation, a dynamics model of LEV-2 was first developed. Subsequently, the motion behaviors of LEV2 were analyzed by utilizing the discrete element method. Traveling tests were then conducted using the LEV-2 engineering model on various terrains covered with a lunar regolith simulant. The results of both the numerical simulations and experiments revealed consistent trends across different moving modes of LEV-2. Furthermore, the simulation results indicated no significant deterioration in the mobility performance of LEV-2 on the moon when compared to that on the Earth. Based on the characteristics predicted from the simulation and the quantitative data obtained from the experiments, it was concluded that LEV-2 is supposed to travel at least 15<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">◦</sup> slopes on the moon.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802179
Citations
1
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
0.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mobility Performance Characterization of Transformable Nano Rover for Lunar Exploration

Daichi Hirano, Hirotaka Sawada, Masataku Sutoh, Yuta Kawai et al.
1 citations
Planetary Science and Exploration
0.33
article

Mobility Performance Characterization of Transformable Nano Rover for Lunar Exploration

Daichi Hirano, Hirotaka Sawada, Masataku Sutoh, Yuta Kawai, Mariko Inazawa
article en
1 citations

Abstract

In January 2024, a Japanese lunar lander successfully touched down on the moon as part of the Smart Lander for Investigating Moon (SLIM) mission. Accompanying the SLIM on its journey were two small rovers named lunar excursion vehicles (LEV-1 and 2). LEV-2, a transformable nano rover, was particularly designed to capture images of the SLIM on the lunar surface. During the mission, LEV-2 successfully maneuvered and captured images of the lander. Understanding the mobility characteristics of LEV-2 was crucial for the success of this task. This study analyzed the mobility characteristics of LEV-2 through numerical simulation and traveling tests. In the numerical simulation, a dynamics model of LEV-2 was first developed. Subsequently, the motion behaviors of LEV2 were analyzed by utilizing the discrete element method. Traveling tests were then conducted using the LEV-2 engineering model on various terrains covered with a lunar regolith simulant. The results of both the numerical simulations and experiments revealed consistent trends across different moving modes of LEV-2. Furthermore, the simulation results indicated no significant deterioration in the mobility performance of LEV-2 on the moon when compared to that on the Earth. Based on the characteristics predicted from the simulation and the quantitative data obtained from the experiments, it was concluded that LEV-2 is supposed to travel at least 15<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">◦</sup> slopes on the moon.

Japan Aerospace Exploration Agency (JP)
Affordable and clean energy
Openalex Percentile: Top 32%
Planetary Science and Exploration
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.