End-to-End Learning for Visual Navigation of Forest Environments

End-to-End Learning for Visual Navigation of Forest Environments

Off-road navigation in forest environments is a challenging problem in field robotics. Rovers are required to infer their traversability over a priori unknown and dynamically changing forest terrain using noisy onboard navigation sensors. The problem is compounded for small-sized rovers, such as tha...

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Bibliographic Details
Main Authors: Chaoyue Niu, Klaus-Peter Zauner, Danesh Tarapore
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Forests
Subjects:
off-road visual navigation
end-to-end learning
multiclass classification
low-viewpoint forest navigation
low-cost sensors
small-sized rovers
Online Access:https://www.mdpi.com/1999-4907/14/2/268

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https://www.mdpi.com/1999-4907/14/2/268

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