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pro vyhledávání: '"agricultural robotics"'
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Autor:
Philippe, Florian, Laconte, Johann, Lapray, Pierre-Jean, Spisser, Matthias, Lauffenburger, Jean-Philippe
In this paper, we introduce a novel method for safe navigation in agricultural robotics. As global environmental challenges intensify, robotics offers a powerful solution to reduce chemical usage while meeting the increasing demands for food producti
Externí odkaz:
http://arxiv.org/abs/2410.03370
Simultaneous Localization and Mapping (SLAM) is essential for mobile robotics, enabling autonomous navigation in dynamic, unstructured outdoor environments without relying on external positioning systems. In agricultural applications, where environme
Externí odkaz:
http://arxiv.org/abs/2408.01716
Autor:
Magistri, Federico, Läbe, Thomas, Marks, Elias, Nagulavancha, Sumanth, Pan, Yue, Smitt, Claus, Klingbeil, Lasse, Halstead, Michael, Kuhlmann, Heiner, McCool, Chris, Behley, Jens, Stachniss, Cyrill
As the world population is expected to reach 10 billion by 2050, our agricultural production system needs to double its productivity despite a decline of human workforce in the agricultural sector. Autonomous robotic systems are one promising pathway
Externí odkaz:
http://arxiv.org/abs/2407.13304
Akademický článek
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Akademický článek
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TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards
Autor:
Cheng, Derek, Ojeda, Fernando Cladera, Prabhu, Ankit, Liu, Xu, Zhu, Alan, Green, Patrick Corey, Ehsani, Reza, Chaudhari, Pratik, Kumar, Vijay
Data collection for forestry, timber, and agriculture currently relies on manual techniques which are labor-intensive and time-consuming. We seek to demonstrate that robotics offers improvements over these techniques and accelerate agricultural resea
Externí odkaz:
http://arxiv.org/abs/2310.02162
Autor:
Smitt, Claus, Halstead, Michael, Zimmer, Patrick, Läbe, Thomas, Guclu, Esra, Stachniss, Cyrill, McCool, Chris
Precise scene understanding is key for most robot monitoring and intervention tasks in agriculture. In this work we present PAg-NeRF which is a novel NeRF-based system that enables 3D panoptic scene understanding. Our representation is trained using
Externí odkaz:
http://arxiv.org/abs/2309.05339
Autor:
Roggiolani, Gianmarco, Magistri, Federico, Guadagnino, Tiziano, Weyler, Jan, Grisetti, Giorgio, Stachniss, Cyrill, Behley, Jens
Agricultural robots have the prospect to enable more efficient and sustainable agricultural production of food, feed, and fiber. Perception of crops and weeds is a central component of agricultural robots that aim to monitor fields and assess the pla
Externí odkaz:
http://arxiv.org/abs/2303.12499