L*—An index for evaluating long range performance of autonomous underwater vehicles (AUVs)
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
L*—An index for evaluating long range performance of autonomous underwater vehicles (AUVs) ; volume:12 ; number:10 ; day:20 ; month:7 ; year:2024 ; pages:2205-2221 ; date:10.2024
Friction ; 12, Heft 10 (20.7.2024), 2205-2221, 10.2024
- Creator
-
Zhu, Manfu
Ma, Liran
Luo, Jianbin
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1007/s40544-023-0842-7
- URN
-
urn:nbn:de:101:1-2411052102580.976068638163
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:37 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Zhu, Manfu
- Ma, Liran
- Luo, Jianbin
- SpringerLink (Online service)
Other Objects (12)
Long-Term Adaptive Modeling for Autonomous Underwater Vehicles
Simulation model for energy consumption and acoustic underwater communication of autonomous underwater vehicles
Effective Turning Motion Control of Internally Actuated Autonomous Underwater Vehicles
A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles
Semi-supervised Visual Tracking of Marine Animals Using Autonomous Underwater Vehicles
Using Augmented State Kalman filter to localize multi autonomous underwater vehicles
Adaptive autonomous underwater vehicles for littoral surveillance : The GLINT10 field trial results
Autonomous Underwater Vehicle „ABYSS“
Learning, Evaluating and Optimizing Behavior Policies for Autonomous Vehicles
Autonomous robot vehicles
On-line path planning and robust adaptive path following for underactuated autonomous underwater vehicles
Deep-Sea Model-Aided Navigation Accuracy for Autonomous Underwater Vehicles Using Online Calibrated Dynamic Models
Long-Term Adaptive Modeling for Autonomous Underwater Vehicles
Simulation model for energy consumption and acoustic underwater communication of autonomous underwater vehicles
Effective Turning Motion Control of Internally Actuated Autonomous Underwater Vehicles
A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles
Semi-supervised Visual Tracking of Marine Animals Using Autonomous Underwater Vehicles
Using Augmented State Kalman filter to localize multi autonomous underwater vehicles
Adaptive autonomous underwater vehicles for littoral surveillance : The GLINT10 field trial results
Autonomous Underwater Vehicle „ABYSS“
Learning, Evaluating and Optimizing Behavior Policies for Autonomous Vehicles
Autonomous robot vehicles
On-line path planning and robust adaptive path following for underactuated autonomous underwater vehicles
Deep-Sea Model-Aided Navigation Accuracy for Autonomous Underwater Vehicles Using Online Calibrated Dynamic Models
Long-Term Adaptive Modeling for Autonomous Underwater Vehicles
Simulation model for energy consumption and acoustic underwater communication of autonomous underwater vehicles
Effective Turning Motion Control of Internally Actuated Autonomous Underwater Vehicles
A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles
Semi-supervised Visual Tracking of Marine Animals Using Autonomous Underwater Vehicles
Using Augmented State Kalman filter to localize multi autonomous underwater vehicles
Adaptive autonomous underwater vehicles for littoral surveillance : The GLINT10 field trial results
Autonomous Underwater Vehicle „ABYSS“
Learning, Evaluating and Optimizing Behavior Policies for Autonomous Vehicles
Autonomous robot vehicles
On-line path planning and robust adaptive path following for underactuated autonomous underwater vehicles