| Name |
Format |
Description |
Link |
|
33 |
This research aims to develop a comprehensive framework for modeling the hydrodynamics of a WEC-AUV dock system, optimizing the AUV homing and docking trajectory, and predicting the power status of a docking station and AUV. |
https://mhkdr.openei.org/files/456/A%20Framework%20for%20Wave-to-Wire%20Simulation%20of%20Wave%20Energy.pdf |
|
33 |
Provides a brief description of the WEC-AUV-DOCK co-design. |
https://mhkdr.openei.org/files/456/Model%20summary.pdf |
|
57 |
This contains the vehicle data that was recorded during the autonomous docking operations. |
https://mhkdr.openei.org/files/456/rosbags.zip |
|
21 |
This GitHub repository includes information on how to install Ubuntu, the python for the BlueROV2, usage, and other supporting technologies needed. More information in the README. |
https://github.com/rakeshv24/bluerov2_dock |
|
57 |
ProtueusDs and WAMIT models of FOSWEC2 (Oscillating Flap wave energy converter) |
https://mhkdr.openei.org/files/456/FOSWEC2_Model.zip |
|
57 |
Videos of autonomous underwater docking from year 2 testing. |
https://mhkdr.openei.org/files/456/Hinsdale%20Videos%202023.zip |
|
57 |
Videos of autonomous underwater docking from year 1 testing. |
https://mhkdr.openei.org/files/456/Videos.zip |
|
33 |
Achieving autonomous docking in challenging conditions, including strong ocean currents and wave forces, remains an active area of research. Therefore, we present a docking framework that incorporates flow state estimation into the design of a model predictive controller (MPC) for achieving autonomous underwater docking with a WEC in diverse ocean conditions. Furthermore, this framework adequately addresses the influence of wave forces on the AUV. |
https://mhkdr.openei.org/files/456/IROS_2023%20%281%29.pdf |
|
57 |
ProteusDS and WAMIT models for LUPA (self reacting point absorber WEC). |
https://mhkdr.openei.org/files/456/LUPA_Model.zip |
|
33 |
Presented is a navigation framework to perform
autonomous underwater docking to a WEC under various ocean conditions by incorporating flow
state estimation into the design of model predictive control (MPC). The simulation results demonstrate the robustness and reliability of the proposed framework for autonomous docking under various ocean conditions. |
https://mhkdr.openei.org/files/456/Autonomous%20Underwater%20Docking%20using%20Flow%20State%20Estimation.pdf |
|
33 |
We consider the underwater docking stations to be powered through a floating WEC, thereby enabling
on-site energy harvesting and power transfer. As a main contribution, we present a navigation framework that couples flow state estimation with model predictive control (MPC) to perform autonomous underwater docking with a WEC under
various ocean conditions. |
https://mhkdr.openei.org/files/456/Flow%20State%20Estimation%20and%20Optimal%20Control%20for%20Autonomous.pdf |