Biography
Nived joined the ORI as a post-doctoral research assistant in 2021. He is working with the Dynamic Robot Systems Group on navigation and mapping tasks for field robots.
During his Ph.D. at the University of Bonn, Nived worked on techniques for localization and mapping for robots in agricultural fields. His research focus has been on developing robust registration techniques for SLAM systems using vision and LiDAR data acquired over long time intervals. Prior to that, Nived received his master's degree in Robotics from Ecole Centrale de Nantes (ECN), France, and the University of Genoa, Italy in 2015.
Nived is also passionate about teaching and has given lectures in M.Sc. courses on Mobile Sensing and Robotics, and Techniques for Self-Driving Cars.
Research
Research Groups
Related Academics
Recent Publications
Towards real-time forest inventory using handheld LiDAR
Proudman A, Ramezani M, Digumarti S, Chebrolu N & Fallon M (2022), Robotics and Autonomous Systems, 157
BibTeX
@article{towardsrealtime-2022/8,
title={Towards real-time forest inventory using handheld LiDAR},
author={Proudman A, Ramezani M, Digumarti S, Chebrolu N & Fallon M},
journal={Robotics and Autonomous Systems},
volume={157},
number={104240},
publisher={Elsevier},
year = "2022"
}
An efficient locally reactive controller for safe navigation in visual teach and repeat missions
Mattamala M, Chebrolu N & Fallon M (2022), IEEE Robotics and Automation Letters, 7(2), 2353-2360
BibTeX
@article{anefficientloca-2022/1,
title={An efficient locally reactive controller for safe navigation in visual teach and repeat missions},
author={Mattamala M, Chebrolu N & Fallon M},
journal={IEEE Robotics and Automation Letters},
volume={7},
pages={2353-2360},
publisher={IEEE},
year = "2022"
}
Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution
Pretto A, Aravecchia S, Burgard W, Chebrolu N, Dornhege C et al. (2021), IEEE Robotics and Automation Magazine, 28(3), 29-49
BibTeX
@article{buildinganaeria-2021/9,
title={Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution},
author={Pretto A, Aravecchia S, Burgard W, Chebrolu N, Dornhege C et al.},
journal={IEEE Robotics and Automation Magazine},
volume={28},
pages={29-49},
year = "2021"
}
Adaptive Robust Kernels for Non-Linear Least Squares Problems
Chebrolu N, Labe T, Vysotska O, Behley J & Stachniss C (2021), IEEE Robotics and Automation Letters, 6(2), 2240-2247
BibTeX
@article{adaptiverobustk-2021/4,
title={Adaptive Robust Kernels for Non-Linear Least Squares Problems},
author={Chebrolu N, Labe T, Vysotska O, Behley J & Stachniss C},
journal={IEEE Robotics and Automation Letters},
volume={6},
pages={2240-2247},
year = "2021"
}
Registration of spatio-temporal point clouds of plants for phenotyping.
Chebrolu N, Magistri F, Läbe T & Stachniss C (2021), PloS one, 16(2), e0247243
BibTeX
@article{registrationofs-2021/2,
title={Registration of spatio-temporal point clouds of plants for phenotyping.},
author={Chebrolu N, Magistri F, Läbe T & Stachniss C},
journal={PloS one},
volume={16},
pages={e0247243},
year = "2021"
}
Robust long-term registration of UAV images of crop fields for precision agriculture
Chebrolu N, Labe T & Stachniss C (2018), IEEE Robotics and Automation Letters, 3(4), 3097-3104
BibTeX
@article{robustlongtermr-2018/10,
title={Robust long-term registration of UAV images of crop fields for precision agriculture},
author={Chebrolu N, Labe T & Stachniss C},
journal={IEEE Robotics and Automation Letters},
volume={3},
pages={3097-3104},
year = "2018"
}
