An Attention-Based Odometry Framework for Multisensory Unmanned Ground Vehicles (UGVs)
An Attention-Based Odometry Framework for Multisensory Unmanned Ground Vehicles (UGVs)
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Basel: MDPI AG
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English
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Basel: MDPI AG
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Recently, deep learning methods and multisensory fusion have been applied to address odometry challenges in unmanned ground vehicles (UGVs). In this paper, we propose an end-to-end visual-lidar-inertial odometry framework to enhance the accuracy of pose estimation. Grayscale images, 3D point clouds, and inertial data are used as inputs to overcome...
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Full title
An Attention-Based Odometry Framework for Multisensory Unmanned Ground Vehicles (UGVs)
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TN_cdi_doaj_primary_oai_doaj_org_article_b4af5119bec54307ac1be5ced8ec3efb
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b4af5119bec54307ac1be5ced8ec3efb
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ISSN
2504-446X
E-ISSN
2504-446X
DOI
10.3390/drones7120699
