AUV docking experiments based on vision positioning using two cameras

Li, Ye; Jiang, Yanqing; Cao, Jian; Wang, Bo; Li, Yiming

doi:10.1016/j.oceaneng.2015.10.015

Cited by 100 publications

(50 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(3) A recent example of a system used in this research consists of four LED lights located at the inlet of the cone of the dock in the shape of a cross and a stereo camera located at the nose of the AUV. (4) Optical sensors are used as terminal guidance sensors because their range is limited in seawater.…”

Section: Previous Homing Sensors For Dockingmentioning

confidence: 99%

Concept of Autonomous Underwater Vehicle Docking Using 3D Imaging Sonar

Uchihori¹,

Yamamoto²,

Morinaga³

2019

Sensors and Materials

View full text Add to dashboard Cite

In this paper, we propose the concept of underwater docking of an autonomous underwater vehicle (AUV) for power supply and data transfer to conduct the continuous operation of the AUV without launch and recovery operations. Our basic concept of docking involves the use of a 3D imaging sonar as the autonomous homing sensor for AUV and a remotely operated vehicle (ROV) as the docking station, which has maneuverability to compensate for the homing error of the AUV. On the basis of this concept, we use a 3D imaging sonar as a homing sensor during docking. The 3D imaging sonar has a potential for advanced AUV operation and will be the versatile "eye" of the AUV.

show abstract

Section: Previous Homing Sensors For Dockingmentioning

confidence: 99%

Concept of Autonomous Underwater Vehicle Docking Using 3D Imaging Sonar

Uchihori¹,

Yamamoto²,

Morinaga³

2019

Sensors and Materials

View full text Add to dashboard Cite

show abstract

“…AUV can get energy supplies and provide data via the station. Howbeit it is hard to transfer energy to AUV through the traditional cable method in the underwater environment for high expenses and docking precision [2][3][4]. Wireless power transfer (WPT) technology has the advantages of safety, convenience, and long service life, it is very suitable for underwater energy supply and researchers have done lots of work to make use of WPT in the underwater environment.…”

Section: Introductionmentioning

confidence: 99%

Application of Shielding Coils in Underwater Wireless Power Transfer Systems

Wang

Song

Mao

2019

JMSE

View full text Add to dashboard Cite

Underwater wireless power transfer (WPT) technology can enhance the endurance of the autonomous underwater vehicles (AUV). WPT that based on electromagnetic theory will generate eddy current loss (ECL) in seawater. In this paper, we make use of shielding coils to weaken the electromagnetic field (EMF) in seawater, which can reduce ECL and improve the transfer efficiency. Simplified circuit models were proposed to provide an intuitive and comprehensive analysis of the transfer efficiency and the finite element analysis (FEA) was used to simulate the distribution of EMF. We learn that the system with shielding coils performs better when the operating frequency is relatively high by comparing the power transfer efficiency of the underwater WPT systems with and without the shielding, and its maximum efficiency is higher than the system without shielding. The effect of the shielding coils has the similar influence when compared with the metallic plate. While considering the efficiency and weight of coils, the results show that the shielding coils can be used in the underwater WPT system to improve the power transfer efficiency.

show abstract

“…The docking of an AUV onto a moving platform is investigated in [18]. On the other hand, many experimental studies have been conducted, which focus on the localisation of the AUV, the estimation of its relative position and orientation with respect to the docking station and the analysis of the acoustic and visual sensors that best enable these solutions [8][9][10][11][12][19][20][21][22]. In most of these studies, advanced simultaneous localisation and mapping (SLAM) computer-vision strategies are coupled with line-of-sight guidance and classical control algorithms, such as proportional-integral-derivative (PID) and sliding-mode (SM) control.…”

Section: Introductionmentioning

confidence: 99%

Docking Control of an Autonomous Underwater Vehicle Using Reinforcement Learning

2019

View full text Add to dashboard Cite

To achieve persistent systems in the future, autonomous underwater vehicles (AUVs) willneed to autonomously dock onto a charging station. Here, reinforcement learning strategies wereapplied for the first time to control the docking of an AUV onto a fixed platform in a simulationenvironment. Two reinforcement learning schemes were investigated: one with continuous stateand action spaces, deep deterministic policy gradient (DDPG), and one with continuous state butdiscrete action spaces, deep Q network (DQN). For DQN, the discrete actions were selected as stepchanges in the control input signals. The performance of the reinforcement learning strategies wascompared with classical and optimal control techniques. The control actions selected by DDPG sufferfrom chattering effects due to a hyperbolic tangent layer in the actor. Conversely, DQN presents thebest compromise between short docking time and low control effort, whilst meeting the dockingrequirements. Whereas the reinforcement learning algorithms present a very high computational costat training time, they are five orders of magnitude faster than optimal control at deployment time,thus enabling an on-line implementation. Therefore, reinforcement learning achieves a performancesimilar to optimal control at a much lower computational cost at deployment, whilst also presentinga more general framework.

show abstract

AUV docking experiments based on vision positioning using two cameras

Cited by 100 publications

References 6 publications

Concept of Autonomous Underwater Vehicle Docking Using 3D Imaging Sonar

Concept of Autonomous Underwater Vehicle Docking Using 3D Imaging Sonar

Application of Shielding Coils in Underwater Wireless Power Transfer Systems

Docking Control of an Autonomous Underwater Vehicle Using Reinforcement Learning

Contact Info

Product

Resources

About