Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Cladera, Fernando"'
Autor:
Lei, Jiuzhou, Prabhu, Ankit, Liu, Xu, Cladera, Fernando, Mortazavi, Mehrad, Ehsani, Reza, Chaudhari, Pratik, Kumar, Vijay
Automated persistent and fine-grained monitoring of orchards at the individual tree or fruit level helps maximize crop yield and optimize resources such as water, fertilizers, and pesticides while preventing agricultural waste. Towards this goal, we
Externí odkaz:
http://arxiv.org/abs/2409.19786
Traditionally, unmanned aerial vehicles (UAVs) rely on CMOS-based cameras to collect images about the world below. One of the most successful applications of UAVs is to generate orthomosaics or orthomaps, in which a series of images are integrated to
Externí odkaz:
http://arxiv.org/abs/2409.18120
Neural Radiance Fields (NeRFs) have shown significant promise in 3D scene reconstruction and novel view synthesis. In agricultural settings, NeRFs can serve as digital twins, providing critical information about fruit detection for yield estimation a
Externí odkaz:
http://arxiv.org/abs/2409.15487
Publikováno v:
IEEE Transactions on Field Robotics (2024)
Mapping and navigation have gone hand-in-hand since long before robots existed. Maps are a key form of communication, allowing someone who has never been somewhere to nonetheless navigate that area successfully. In the context of multi-robot systems,
Externí odkaz:
http://arxiv.org/abs/2407.09902
Autor:
Cladera, Fernando, Miller, Ian D., Ravichandran, Zachary, Murali, Varun, Hughes, Jason, Hsieh, M. Ani, Taylor, C. J., Kumar, Vijay
One common and desirable application of robots is exploring potentially hazardous and unstructured environments. Air-ground collaboration offers a synergistic approach to addressing such exploration challenges. In this paper, we demonstrate a system
Externí odkaz:
http://arxiv.org/abs/2405.07169
Autor:
Bhattacharya, Anish, Madaan, Ratnesh, Cladera, Fernando, Vemprala, Sai, Bonatti, Rogerio, Daniilidis, Kostas, Kapoor, Ashish, Kumar, Vijay, Matni, Nikolai, Gupta, Jayesh K.
We present EvDNeRF, a pipeline for generating event data and training an event-based dynamic NeRF, for the purpose of faithfully reconstructing eventstreams on scenes with rigid and non-rigid deformations that may be too fast to capture with a standa
Externí odkaz:
http://arxiv.org/abs/2310.02437
Autor:
Cladera, Fernando, Ravichandran, Zachary, Miller, Ian D., Hsieh, M. Ani, Taylor, C. J., Kumar, Vijay
Multi-robot collaboration in large-scale environments with limited-sized teams and without external infrastructure is challenging, since the software framework required to support complex tasks must be robust to unreliable and intermittent communicat
Externí odkaz:
http://arxiv.org/abs/2309.15975
Autor:
Tao, Yuezhan, Wu, Yuwei, Li, Beiming, Cladera, Fernando, Zhou, Alex, Thakur, Dinesh, Kumar, Vijay
We address the problem of efficient 3-D exploration in indoor environments for micro aerial vehicles with limited sensing capabilities and payload/power constraints. We develop an indoor exploration framework that uses learning to predict the occupan
Externí odkaz:
http://arxiv.org/abs/2209.11034
Autor:
Liu, Xu, Prabhu, Ankit, Cladera, Fernando, Miller, Ian D., Zhou, Lifeng, Taylor, Camillo J., Kumar, Vijay
Publikováno v:
ICRA 2023 (2023 International Conference on Robotics and Automation)
Traditional approaches for active mapping focus on building geometric maps. For most real-world applications, however, actionable information is related to semantically meaningful objects in the environment. We propose an approach to the active metri
Externí odkaz:
http://arxiv.org/abs/2209.08465
In this work, we present an end-to-end heterogeneous multi-robot system framework where ground robots are able to localize, plan, and navigate in a semantic map created in real time by a high-altitude quadrotor. The ground robots choose and deconflic
Externí odkaz:
http://arxiv.org/abs/2206.14289