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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Vydáno v:	IEEE robotics and automation letters Ročník 7; číslo 4; s. 11434 - 11441
Hlavní autoři:	Coloma, Sofia, Martinez, Carol, Yalcn, Bars Can, Olivares-Mendez, Miguel A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 01.10.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Decision making Graphical user interface Graphical user interfaces Lunar communication Machine learning Machine learning for robot control Mars Moon Sensors Soil Soil conditions Soil mechanics space robotics and automation telerobotics and teleoperation Wheels
ISSN:	2377-3766, 2377-3766
On-line přístup:	Získat plný text
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