Abstract
A critical challenge for autonomous underwater vehicles (AUVs) is the docking operation for applications such as sleeping under the mother ship, recharging batteries, transferring data, and new mission downloading. The final stage of docking at a unidirectional docking station requires the AUV to approach while keeping the pose (position and orientation) of the vehicle within an allowable range. The appropriate pose therefore demands a sensor unit and a control system that have high accuracy and robustness against disturbances existing in a real-world underwater environment. This paper presents a vision-based AUV docking system consisting of a 3D model-based matching method and Real-time Multi-step Genetic Algorithm (GA) for real-time estimation of the robot’s relative pose. Experiments using a remotely operated vehicle (ROV) with dual-eye cameras and a separate 3D marker were conducted in a small indoor pool. The experimental results confirmed that the proposed system is able to provide high homing accuracy and robustness against disturbances that influence not only the captured camera images but also the movement of the vehicle. A successful docking operation using stereo vision that is new and novel to the underwater vehicle environment was achieved and thus proved the effectiveness of the proposed system for AUV.
| Original language | English |
|---|---|
| Pages (from-to) | 1-28 |
| Number of pages | 28 |
| Journal | Journal of Intelligent and Robotic Systems: Theory and Applications |
| DOIs | |
| Publication status | Accepted/In press - Oct 13 2017 |
Fingerprint
Keywords
- Genetic algorithm
- Stereo vision
- Underwater docking
- Underwater vehicle
- Visual servoing
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering
Cite this
Dual-eyes Vision-based Docking System for Autonomous Underwater Vehicle : an Approach and Experiments. / Myint, Myo; Yonemori, Kenta; Lwin, Khin Nwe; Yanou, Akira; Minami, Mamoru.
In: Journal of Intelligent and Robotic Systems: Theory and Applications, 13.10.2017, p. 1-28.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Dual-eyes Vision-based Docking System for Autonomous Underwater Vehicle
T2 - an Approach and Experiments
AU - Myint, Myo
AU - Yonemori, Kenta
AU - Lwin, Khin Nwe
AU - Yanou, Akira
AU - Minami, Mamoru
PY - 2017/10/13
Y1 - 2017/10/13
N2 - A critical challenge for autonomous underwater vehicles (AUVs) is the docking operation for applications such as sleeping under the mother ship, recharging batteries, transferring data, and new mission downloading. The final stage of docking at a unidirectional docking station requires the AUV to approach while keeping the pose (position and orientation) of the vehicle within an allowable range. The appropriate pose therefore demands a sensor unit and a control system that have high accuracy and robustness against disturbances existing in a real-world underwater environment. This paper presents a vision-based AUV docking system consisting of a 3D model-based matching method and Real-time Multi-step Genetic Algorithm (GA) for real-time estimation of the robot’s relative pose. Experiments using a remotely operated vehicle (ROV) with dual-eye cameras and a separate 3D marker were conducted in a small indoor pool. The experimental results confirmed that the proposed system is able to provide high homing accuracy and robustness against disturbances that influence not only the captured camera images but also the movement of the vehicle. A successful docking operation using stereo vision that is new and novel to the underwater vehicle environment was achieved and thus proved the effectiveness of the proposed system for AUV.
AB - A critical challenge for autonomous underwater vehicles (AUVs) is the docking operation for applications such as sleeping under the mother ship, recharging batteries, transferring data, and new mission downloading. The final stage of docking at a unidirectional docking station requires the AUV to approach while keeping the pose (position and orientation) of the vehicle within an allowable range. The appropriate pose therefore demands a sensor unit and a control system that have high accuracy and robustness against disturbances existing in a real-world underwater environment. This paper presents a vision-based AUV docking system consisting of a 3D model-based matching method and Real-time Multi-step Genetic Algorithm (GA) for real-time estimation of the robot’s relative pose. Experiments using a remotely operated vehicle (ROV) with dual-eye cameras and a separate 3D marker were conducted in a small indoor pool. The experimental results confirmed that the proposed system is able to provide high homing accuracy and robustness against disturbances that influence not only the captured camera images but also the movement of the vehicle. A successful docking operation using stereo vision that is new and novel to the underwater vehicle environment was achieved and thus proved the effectiveness of the proposed system for AUV.
KW - Genetic algorithm
KW - Stereo vision
KW - Underwater docking
KW - Underwater vehicle
KW - Visual servoing
UR - http://www.scopus.com/inward/record.url?scp=85031426177&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85031426177&partnerID=8YFLogxK
U2 - 10.1007/s10846-017-0703-6
DO - 10.1007/s10846-017-0703-6
M3 - Article
SP - 1
EP - 28
JO - Journal of Intelligent and Robotic Systems: Theory and Applications
JF - Journal of Intelligent and Robotic Systems: Theory and Applications
SN - 0921-0296
ER -