| 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 | 352 | 2017 |
| 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 | 125 | 2020 |
| 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 | 108 | 2021 |
| 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 | 100 | 2018 |
| 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 | 99 | 2020 |
| 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 | 94 | 2018 |
| 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 | 82 | 2021 |
| 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 | 79 | 2020 |
| 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 | 77 | 2021 |
| 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 | 65 | 2023 |
| 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 | 55 | 2020 |
| 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 | 54 | 2019 |
| Registration of spatio-temporal point clouds of plants for phenotyping N Chebrolu, F Magistri, T Läbe, C Stachniss PloS one 16 (2), e0247243, 2021 | 42 | 2021 |
| 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 | 39 | 2020 |
| 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 | 32 | 2022 |
| 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 | 27 | 2022 |
| 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 | 19 | 2024 |
| 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 | 17 | 2021 |
| 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 | 16 | 2015 |
| 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 | 10 | 2024 |
Cyrill StachnissProfessor for Photogrammetry & Robotics, University of BonnEmail verificata su igg.uni-bonn.de