Enhancing Rover Teleoperation on the Moon With Proprioceptive Sensors and Machine Learning Techniques

Geological formations, environmental conditions, and soil mechanics frequently generate undesired effects on rovers' mobility, such as slippage or sinkage. Underestimating these undesired effects may compromise the rovers' operation and lead to a premature end of the mission. Minimizing mo...

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Bibliographic Details
Published in:IEEE robotics and automation letters Vol. 7; no. 4; pp. 11434 - 11441
Main Authors: Coloma, Sofia, Martinez, Carol, Yalcn, Bars Can, Olivares-Mendez, Miguel A.
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:2377-3766, 2377-3766
Online Access:Get full text
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Summary:Geological formations, environmental conditions, and soil mechanics frequently generate undesired effects on rovers' mobility, such as slippage or sinkage. Underestimating these undesired effects may compromise the rovers' operation and lead to a premature end of the mission. Minimizing mobility risks becomes a priority for colonising the Moon and Mars. However, addressing this challenge cannot be treated equally for every celestial body since the control strategies may differ; e.g. the low latency Earth-Moon communication allows constant monitoring and controls, something not feasible on Mars. This letter proposes a Hazard Information System (HIS) that estimates the rover's mobility risks (e.g. slippage) using proprioceptive sensors and Machine Learning (supervised and unsupervised). A Graphical User Interface was created to assist human-teleoperation tasks by presenting mobility risk indicators. The system has been developed and evaluated in the lunar analogue facility (LunaLab) at the University of Luxembourg. A real rover and eight participants were part of the experiments. Results demonstrate the benefits of the HIS in the decision-making processes of the operator's response to overcome hazardous situations.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2022.3198794