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pro vyhledávání: '"Panchetti, Lorenzo"'
Learning from demonstrations (LfD) enables humans to easily teach collaborative robots (cobots) new motions that can be generalized to new task configurations without retraining. However, state-of-the-art LfD methods require manually tuning intrinsic
Externí odkaz:
http://arxiv.org/abs/2209.06940
Adaptive control for real-time manipulation requires quick estimation and prediction of object properties. While robot learning in this area primarily focuses on using vision, many tasks cannot rely on vision due to object occlusion. Here, we formula
Externí odkaz:
http://arxiv.org/abs/2110.04634
State-of-the-art learning from demonstration (LfD) methods for collaborative robots—skill transfer and generalization through a set of demonstrations—require manually tuning intrinsic parameters. Hence, LfD cannot be used readily in industrial co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc83ba01a086351c3b2c34f9c9ae9e5f
Adaptive control for real-time manipulation requires quick estimation and prediction of object properties. While robot learning in this area primarily focuses on using vision, many tasks cannot rely on vision due to object occlusion. Here, we formula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1da7364bd4f568a9ac6087699931809
https://infoscience.epfl.ch/record/298862
https://infoscience.epfl.ch/record/298862