Bilal Wehbe
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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
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
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
Learning coupled dynamic models of underwater vehicles using support vector regression
B Wehbe, MM Krell
OCEANS 2017-Aberdeen, 1-7, 2017
Infuse: A comprehensive framework for data fusion in space robotics
S Govindaraj, J Gancet, M Post, R Dominguez, F Souvannavong
Infinite Study, 2017
A common data fusion framework for space robotics: architecture and data fusion methods
R Dominguez, S Govindaraj, J Gancet, M Post, R Michalec, N Oumer, ...
International Symposium on Artificial Intelligence, Robotics and Automation …, 2018
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
InFuse data fusion methodology for space robotics, awareness and machine learning
M Post, R Michalec, A Bianco, X Yan, A De Maio, S Lacroix, J Gancet, ...
69th International Astronautical Congress, 2018
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
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
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
Pre-trained Models for Sonar Images
M Valdenegro-Toro, A Preciado-Grijalva, B Wehbe
arXiv preprint arXiv:2108.01111, 2021
ROBOCADEMY—A European Initial Training Network for underwater robotics
T Vögele, B Wehbe, S Nascimento, F Kirchner, F Ferreira, G Ferri, ...
Oceans 2016-shanghai, 1-5, 2016
A First Step Towards Distribution Invariant Regression Metrics
MM Krell, B Wehbe
arXiv preprint arXiv:2009.05176, 2020
Long-Term Adaptive Modeling for Autonomous Underwater Vehicles
B Wehbe
Universität Bremen, 2020
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
Self-supervised Learning for Sonar Image Classification
A Preciado-Grijalva, B Wehbe, MB Firvida, M Valdenegro-Toro
arXiv preprint arXiv:2204.09323, 2022
Online Model Adaptation of Autonomous Underwater Vehicles with LSTM Networks
M Bande, B Wehbe
OCEANS 2021: San Diego–Porto, 1-6, 2021
Deep Reinforcement Learning for Continuous Docking Control of Autonomous Underwater Vehicles: A Benchmarking Study
M Patil, B Wehbe, M Valdenegro-Toro
arXiv preprint arXiv:2108.02665, 2021
Machine Learning and Dynamic Whole Body Control for Underwater Manipulation
J Gea Fernández, C Ott, B Wehbe
AI Technology for Underwater Robots, 107-115, 2020
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