Bilal Wehbe
Title
Cited by
Cited by
Year
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
172017
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
122014
Infuse: A comprehensive framework for data fusion in space robotics
S Govindaraj, J Gancet, M Post, R Dominguez, F Souvannavong
Infinite Study, 2017
112017
Learning coupled dynamic models of underwater vehicles using support vector regression
B Wehbe, MM Krell
OCEANS 2017-Aberdeen, 1-7, 2017
102017
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
102017
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
72017
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
52018
Novel three-dimensional optimal path planning method for vehicles with constrained pitch and yaw
B Wehbe, S Bazzi, E Shammas
Robotica 35 (11), 2157, 2017
52017
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
52015
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
42018
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
22016
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
12019
A First Step Towards Distribution Invariant Regression Metrics
MM Krell, B Wehbe
arXiv preprint arXiv:2009.05176, 2020
2020
Long-Term Adaptive Modeling for Autonomous Underwater Vehicles
B Wehbe
Universität Bremen, 2020
2020
Machine Learning and Dynamic Whole Body Control for Underwater Manipulation
J de Gea Fernández, C Ott, B Wehbe
AI Technology for Underwater Robots, 107-115, 2020
2020
Results from the Robocademy ITN: Autonomy, Disturbance Rejection and Perception for Advanced Marine Robotics
M Valdenegro-Toro, MDL Alvarez, M Dmitrieva, B Wehbe, G Salavasidis, ...
arXiv preprint arXiv:1910.13144, 2019
2019
Learning of Multi-Context Models for Autonomous Underwater Vehicles
B Wehbe, O Arriaga, MM Krell, F Kirchner
2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV), 1-6, 2018
2018
InFuse: infusing perception and data fusion into space robotics with open building blocks
M Post, F Souvannavong, S Govinderaj, J Gancet, V Bissonnette, ...
Informatics in Control, Automation and Robotics, 2017
2017
The European Marie-Curie Training Network ROBOCADEMY
T Vögele, B Wehbe, S Nascimento, T Runge, F Kirchner
IFAC-PapersOnLine 49 (23), 426-429, 2016
2016
Dynamic modeling of a hybrid autonomous underwater vehicle with efficient three dimensional path planning methods
BI Wehbe
Theses, Dissertations, and Projects, 2014
2014
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