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DGCM-Net: Dense Geometrical Correspondence Matching Network for Incremental Experience-Based Robotic Grasping
This article presents a method for grasping novel objects by learning from experience. Successful attempts are remembered and then used to guide future grasps such that more reliable grasping is achieved over time. To transfer the learned experience to unseen objects, we introduce the dense geometri...
Autores principales: | Patten, Timothy, Park, Kiru, Vincze, Markus |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805634/ https://www.ncbi.nlm.nih.gov/pubmed/33501286 http://dx.doi.org/10.3389/frobt.2020.00120 |
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