Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Alessandro Devo"'
Publikováno v:
IEEE Robotics and Automation Letters. 7:5031-5038
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60de9c1e1cf133d1f8b0b8974943faa6
https://doi.org/10.1109/lra.2022.3154019
https://doi.org/10.1109/lra.2022.3154019
Publikováno v:
IEEE Transactions on Robotics. 36:1546-1561
Among the main challenges in robotics, target-driven visual navigation has gained increasing interest in recent years. In this task, an agent has to navigate in an environment to reach a user specified target, only through vision. Recent fruitful app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb90ff012bcfacb0ab962031997a060a
https://doi.org/10.1109/tro.2020.2994002
https://doi.org/10.1109/tro.2020.2994002
In the last decades, visual target tracking has been one of the primary research interests of the Robotics research community. The recent advances in Deep Learning technologies have made the exploitation of visual tracking approaches effective and po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2825cf190873a87f020faa88d68b3f66
Deep Reinforcement Learning for Instruction Following Visual Navigation in 3D Maze-Like Environments
In this work, we address the problem of visual navigation by following instructions. In this task, the robot must interpret a natural language instruction in order to follow a predefined path in a possibly unknown environment. Despite different appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03bd66a3ed3fa2152d988d649f68bf27
http://hdl.handle.net/11391/1458050
http://hdl.handle.net/11391/1458050
Autor:
Gabriele Costante, Mario Luca Fravolini, Paolo Valigi, Thomas A. Ciarfuglia, Alessandro Devo, Silvia Cascianelli
Natural Language Video Description (NLVD) has recently received strong interest in the Computer Vision, Natural Language Processing (NLP), Multimedia, and Autonomous Robotics communities. The State-of-the-Art (SotA) approaches obtained remarkable res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::984386524d24187bc517f58a6659d804
https://hdl.handle.net/11380/1200034
https://hdl.handle.net/11380/1200034
In this work, we address generalization in targetdriven visual navigation by proposing a novel architecture composed by two networks, both exclusively trained in simulation. The first one has the objective of exploring the environment, while the othe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71d7124822d3dd100d11f9c3c6f3a7fe