Zobrazeno 1 - 10
of 291
pro vyhledávání: '"Chowdhary, Girish"'
Autonomous under-canopy navigation faces additional challenges compared to over-canopy settings - for example the tight spacing between the crop rows, degraded GPS accuracy and excessive clutter. Keypoint-based visual navigation has been shown to per
Externí odkaz:
http://arxiv.org/abs/2411.14092
Autor:
Gasparino, Mateus Valverde, Higuti, Vitor Akihiro Hisano, Sivakumar, Arun Narenthiran, Velasquez, Andres Eduardo Baquero, Becker, Marcelo, Chowdhary, Girish
Small robots that can operate under the plant canopy can enable new possibilities in agriculture. However, unlike larger autonomous tractors, autonomous navigation for such under canopy robots remains an open challenge because Global Navigation Satel
Externí odkaz:
http://arxiv.org/abs/2411.10974
Centralized learning requires data to be aggregated at a central server, which poses significant challenges in terms of data privacy and bandwidth consumption. Federated learning presents a compelling alternative, however, vanilla federated learning
Externí odkaz:
http://arxiv.org/abs/2411.04112
Autor:
Sivakumar, Arun N., Magistri, Federico, Gasparino, Mateus V., Behley, Jens, Stachniss, Cyrill, Chowdhary, Girish
Under-canopy agricultural robots can enable various applications like precise monitoring, spraying, weeding, and plant manipulation tasks throughout the growing season. Autonomous navigation under the canopy is challenging due to the degradation in a
Externí odkaz:
http://arxiv.org/abs/2410.12411
Autor:
Wang, Tixian, Chang, Heng-Sheng, Kim, Seung Hyun, Guo, Jiamiao, Akcal, Ugur, Walt, Benjamin, Biskup, Darren, Halder, Udit, Krishnan, Girish, Chowdhary, Girish, Gazzola, Mattia, Mehta, Prashant G.
A neural network-based framework is developed and experimentally demonstrated for the problem of estimating the shape of a soft continuum arm (SCA) from noisy measurements of the pose at a finite number of locations along the length of the arm. The n
Externí odkaz:
http://arxiv.org/abs/2409.12443
In visual Reinforcement Learning (RL), learning from pixel-based observations poses significant challenges on sample efficiency, primarily due to the complexity of extracting informative state representations from high-dimensional data. Previous meth
Externí odkaz:
http://arxiv.org/abs/2409.02714
Autor:
Sivakumar, Arun N., Thangeda, Pranay, Fang, Yixiao, Gasparino, Mateus V., Cuaran, Jose, Ornik, Melkior, Chowdhary, Girish
Under-canopy agricultural robots require robust navigation capabilities to enable full autonomy but struggle with tight row turning between crop rows due to degraded GPS reception, visual aliasing, occlusion, and complex vehicle dynamics. We propose
Externí odkaz:
http://arxiv.org/abs/2408.03059
Tracking plant features is crucial for various agricultural tasks like phenotyping, pruning, or harvesting, but the unstructured, cluttered, and deformable nature of plant environments makes it a challenging task. In this context, the recent advancem
Externí odkaz:
http://arxiv.org/abs/2407.16829
Autor:
Schreiber, Andre, Sivakumar, Arun N., Du, Peter, Gasparino, Mateus V., Chowdhary, Girish, Driggs-Campbell, Katherine
Successful deployment of mobile robots in unstructured domains requires an understanding of the environment and terrain to avoid hazardous areas, getting stuck, and colliding with obstacles. Traversability estimation--which predicts where in the envi
Externí odkaz:
http://arxiv.org/abs/2406.02822
Autor:
Ahmed, Md. Toukir, Ahmed, Md Wadud, Monjur, Ocean, Emmert, Jason Lee, Chowdhary, Girish, Kamruzzaman, Mohammed
Publikováno v:
Smart Agricultural Technology,Volume 9 , December 2024
As the demand for food surges and the agricultural sector undergoes a transformative shift towards sustainability and efficiency, the need for precise and proactive measures to ensure the health and welfare of livestock becomes paramount. In the cont
Externí odkaz:
http://arxiv.org/abs/2405.13843