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Nived Chebrolu
Nived Chebrolu
Oxford Robotics Institute, University of Oxford
Bestätigte E-Mail-Adresse bei robots.ox.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields
N Chebrolu, P Lottes, A Schaefer, W Winterhalter, W Burgard, C Stachniss
The International Journal of Robotics Research 36 (10), 1045-1052, 2017
3402017
Building an aerial–ground robotics system for precision farming: an adaptable solution
A Pretto, S Aravecchia, W Burgard, N Chebrolu, C Dornhege, T Falck, ...
IEEE Robotics & Automation Magazine 28 (3), 29-49, 2020
1212020
Poisson surface reconstruction for LiDAR odometry and mapping
I Vizzo, X Chen, N Chebrolu, J Behley, C Stachniss
2021 IEEE international conference on robotics and automation (ICRA), 5624-5630, 2021
1012021
Robust joint stem detection and crop‐weed classification using image sequences for plant‐specific treatment in precision farming
P Lottes, J Behley, N Chebrolu, A Milioto, C Stachniss
Journal of Field Robotics 37 (1), 20-34, 2020
952020
Joint stem detection and crop-weed classification for plant-specific treatment in precision farming
P Lottes, J Behley, N Chebrolu, A Milioto, C Stachniss
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
932018
Robust long-term registration of UAV images of crop fields for precision agriculture
N Chebrolu, T Läbe, C Stachniss
IEEE Robotics and Automation Letters 3 (4), 3097-3104, 2018
902018
Pheno4D: A spatio-temporal dataset of maize and tomato plant point clouds for phenotyping and advanced plant analysis
D Schunck, F Magistri, RA Rosu, A Cornelißen, N Chebrolu, S Paulus, ...
Plos one 16 (8), e0256340, 2021
742021
Visual servoing-based navigation for monitoring row-crop fields
A Ahmadi, L Nardi, N Chebrolu, C Stachniss
2020 IEEE International Conference on Robotics and Automation (ICRA), 4920-4926, 2020
732020
Adaptive robust kernels for non-linear least squares problems
N Chebrolu, T Läbe, O Vysotska, J Behley, C Stachniss
IEEE Robotics and Automation Letters 6 (2), 2240-2247, 2021
712021
Fast traversability estimation for wild visual navigation
J Frey, M Mattamala, N Chebrolu, C Cadena, M Fallon, M Hutter
arXiv preprint arXiv:2305.08510, 2023
572023
Segmentation-based 4D registration of plants point clouds for phenotyping
F Magistri, N Chebrolu, C Stachniss
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
512020
Robot localization based on aerial images for precision agriculture tasks in crop fields
N Chebrolu, P Lottes, T Läbe, C Stachniss
2019 international conference on robotics and automation (ICRA), 1787-1793, 2019
502019
Registration of spatio-temporal point clouds of plants for phenotyping
N Chebrolu, F Magistri, T Läbe, C Stachniss
PloS one 16 (2), e0247243, 2021
412021
Spatio-Temporal Non-Rigid Registration of 3D Point Clouds of Plants
N Chebrolu, T Läbe, C Stachniss
Proceedings of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2020
382020
An efficient locally reactive controller for safe navigation in visual teach and repeat missions
M Mattamala, N Chebrolu, M Fallon
IEEE Robotics and Automation Letters 7 (2), 2353-2360, 2022
302022
Towards real-time forest inventory using handheld LiDAR
A Proudman, M Ramezani, ST Digumarti, N Chebrolu, M Fallon
Robotics and Autonomous Systems 157, 104240, 2022
262022
Towards in-field phenotyping exploiting differentiable rendering with self-consistency loss
F Magistri, N Chebrolu, J Behley, C Stachniss
2021 IEEE International Conference on Robotics and Automation (ICRA), 13960 …, 2021
172021
Collaborative visual slam framework for a multi-robot system
N Chebrolu, D Marquez-Gamez, P Martinet
7th Workshop on Planning, Perception and Navigation for Intelligent Vehicles, 2015
162015
PhenoBench: A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain
J Weyler, F Magistri, E Marks, YL Chong, M Sodano, G Roggiolani, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
132024
SiLVR: Scalable Lidar-Visual Reconstruction with Neural Radiance Fields for Robotic Inspection
Y Tao, Y Bhalgat, LFT Fu, M Mattamala, N Chebrolu, M Fallon
arXiv preprint arXiv:2403.06877, 2024
72024
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