Experimental evaluation of various machine learning regression methods for model identification of autonomous underwater vehicles B Wehbe, M Hildebrandt, F Kirchner 2017 IEEE International Conference on Robotics and Automation (ICRA), 4885-4890, 2017 | 49 | 2017 |
Recent advances in ai for navigation and control of underwater robots L Christensen, J de Gea Fernández, M Hildebrandt, CES Koch, B Wehbe Current Robotics Reports 3 (4), 165-175, 2022 | 36 | 2022 |
Learning coupled dynamic models of underwater vehicles using support vector regression B Wehbe, MM Krell OCEANS 2017-Aberdeen, 1-7, 2017 | 31 | 2017 |
AUVx — A novel miniaturized autonomous underwater vehicle H Hanff, P Kloss, B Wehbe, P Kampmann, S Kroffke, A Sander, MB Firvida, ... OCEANS 2017-Aberdeen, 1-10, 2017 | 21 | 2017 |
Deep reinforcement learning for continuous docking control of autonomous underwater vehicles: a benchmarking study M Patil, B Wehbe, M Valdenegro-Toro OCEANS 2021: San Diego–Porto, 1-7, 2021 | 18 | 2021 |
Dynamic modeling and path planning of a hybrid autonomous underwater vehicle B Wehbe, E Shammas, J Zeaiter, D Asmar 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014 …, 2014 | 17 | 2014 |
Self-supervised learning for sonar image classification A Preciado-Grijalva, B Wehbe, MB Firvida, M Valdenegro-Toro Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 15 | 2022 |
Online model identification for underwater vehicles through incremental support vector regression B Wehbe, A Fabisch, MM Krell 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 14 | 2017 |
Spatial acoustic projection for 3d imaging sonar reconstruction S Arnold, B Wehbe 2022 International Conference on Robotics and Automation (ICRA), 3054-3060, 2022 | 11 | 2022 |
A framework for on-line learning of underwater vehicles dynamic models B Wehbe, M Hildebrandt, F Kirchner 2019 International Conference on Robotics and Automation (ICRA), 7969-7975, 2019 | 11 | 2019 |
Infuse: A comprehensive framework for data fusion in space robotics S Govindaraj, J Gancet, M Post, R Dominguez, F Souvannavong Infinite Study, 2017 | 11 | 2017 |
Pre-trained models for sonar images M Valdenegro-Toro, A Preciado-Grijalva, B Wehbe OCEANS 2021: San Diego–Porto, 1-8, 2021 | 9 | 2021 |
A common data fusion framework for space robotics: architecture and data fusion methods R Dominguez, R Michalec, NW Oumer, F Souvannavong, M Post, ... ESA, 2018 | 9 | 2018 |
Towards Robust Autonomous Underwater Docking for Long-Term Under-Ice Exploration T Creutz, B Wehbe, S Arnold, M Hildebrandt OCEANS 2023-Limerick, 1-8, 2023 | 5 | 2023 |
Under-Ice Field tests with an AUV in Abisko/Torneträsk M Hildebrandt, T Creutz, B Wehbe, M Wirtz, M Zipper OCEANS 2022, Hampton Roads, 1-7, 2022 | 5 | 2022 |
From epi-to bathypelagic: Transformation of a compact auv system for long-term deployments M Hildebrandt, S Arnold, P Kloss, B Wehbe, M Zipper 2020 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV), 1-6, 2020 | 5 | 2020 |
InFuse data fusion methodology for space robotics, awareness and machine learning M Post, R Michalec, A Bianco, X Yan, A De Maio, Q Labourey, S Lacroix, ... 69th International Astronautical Congress, 2018 | 5 | 2018 |
Novel three-dimensional optimal path planning method for vehicles with constrained pitch and yaw B Wehbe, S Bazzi, E Shammas Robotica 35 (11), 2157-2176, 2017 | 5 | 2017 |
A novel method to generate three-dimensional paths for vehicles with bounded pitch and yaw B Wehbe, E Shammas, D Asmar 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM …, 2015 | 5 | 2015 |
Long-term adaptive modeling for autonomous underwater vehicles B Wehbe Universität Bremen, 2020 | 4 | 2020 |