Development of the USV ‘JingHai-I’ and sea trials in the Southern Yellow Sea

Peng, Yan; Yang, Yi; Cui, Jianxiang; Li, Xiaomao; Pu, Huayan; Gu, Jason; Xie, Shaorong; Luo, Jun

doi:10.1016/j.oceaneng.2016.09.001

Cited by 81 publications

(41 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As SPM concentration increased, R rs gradually increased [23]. R rs curves in Figure 9b were consistent with those of the Honghu Lake in previous studies [7]. The spectrum in Figure 9d might have been influenced by substrates, such as aquatic plants, which absorb most of the light under the water, resulting in a decrease in R rs .…”

Section: Tests Of Water Quality and Meteorological Measurementssupporting

confidence: 87%

Design and Experiments of a Water Color Remote Sensing-Oriented Unmanned Surface Vehicle

Yong

Tian

et al. 2020

Sensors

View full text Add to dashboard Cite

Integrated and intelligent in situ observations are important for the remote sensing monitoring of dynamic water environments. To meet the field investigation requirements of ocean color remote sensing, we developed a water color remote sensing-oriented unmanned surface vehicle (WC-USV), which consisted of an unmanned surface vehicle platform with ground control station, data acquisition, and transmission modules. The WC-USV was designed with functions, such as remote controlling, status monitoring, automatic obstacle avoidance, and water and meteorological parameter measurement acquisition, transmission, and processing. The key data acquisition module consisted of four parts: A floating optical buoy (FOBY) for collecting remote sensing reflectance ( R r s ) via the skylight-blocked approach; a water sample autocollection system that can collect 12 1-L bottles for analysis in the laboratory; a water quality measurement system for obtaining water parameters, including Chlorophyll-a (Chl-a), turbidity, and water temperature, among others; and meteorological sensors for measuring wind speed and direction, air pressure, temperature, and humidity. Field experiments were conducted to validate the performance of the WC-USV on 23–28 March 2018 in the Honghu Lake, which is the seventh largest freshwater lake in China. The tests proved the following: (1) The WC-USV performed well in terms of autonomous navigation and obstacle avoidance; (2) the mounted FOBY-derived R r s showed good precision in terms of the quality assurance score (QAS), which was higher than 0.98; (3) the Chl-a and suspended matters (SPM) as ocean color parameters measured by the WC-USV were highly consistent with laboratory analysis results, with determination coefficients (R2) of 0.71 and 0.77, respectively; and (4) meteorological parameters could be continuously and stably measured by WC-USV. Results demonstrated the feasibility and practicability of the WC-USV for automatic in situ observations. The USV provided a new way of thinking for the future development of intelligent automation of the aquatic remote sensing ground verification system. It could be a good option to conduct field investigations for ocean color remote sensing and provide an alternative for highly polluted and/or shallow high-risk waters which large vessels have difficulty reaching.

show abstract

Section: Tests Of Water Quality and Meteorological Measurementssupporting

confidence: 87%

Design and Experiments of a Water Color Remote Sensing-Oriented Unmanned Surface Vehicle

Yong

Tian

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Future work will involve developing methods for automating this process such that a certain set of parameters could be identified for suitable USVs from sea-trials data using nonlinear system identification. Suitable USVs with a similar shape, configuration and hull form to Halcyon include Shanghai University's 'JingHai-I' [41] and ASV Global's 'C-Target' series [42].…”

Section: Discussionmentioning

confidence: 99%

Design and validation of an unmanned surface vehicle simulation model

Heins

Jones

Taunton

2017

Applied Mathematical Modelling

View full text Add to dashboard Cite

In this paper we present a multiphysics simulation model of Halcyon, an autonomous unmanned surface vehicle (USV). The simulation model presented in this paper has been developed to rapidly progress the design, development and validation of Halcyon's autonomy management system, particularly in challenging sea conditions. Using simulation for this purpose enables extensive testing across the full environmental operating envelope of the vessel, hence greatly reducing the need for real-world sea-trials. The simulator is comprised of a novel and comprehensive sea-surface wave environment model, a six degree of freedom nonlinear unified seakeeping and manoeuvring boat dynamics model, an actuation dynamics model, an autopilot and an interface with an autonomy management system. Results are presented that show good agreement between real-world and simulated sea-trials data.

show abstract

“…In the case of external disturbances and system parameter disturbances, Nomoto's equation is used as a dynamic mathematical model of USV plane motion [29,30]:…”

Section: Usv Motion Mathematical Modelmentioning

confidence: 99%

Optimized Radial Basis Function Neural Network Based Intelligent Control Algorithm of Unmanned Surface Vehicles

Wang

Li²,

Miao

2020

JMSE

View full text Add to dashboard Cite

To improve the tracking stability control of unmanned surface vehicles (USVs), an intelligent control algorithm was proposed on the basis of an optimized radial basis function (RBF) neural network. The design process was as follows. First, the adaptation value and mutation probability were modified to improve the traditional optimization algorithm. Then, the improved genetic algorithms (GA) were used to optimize the network parameters online to improve their approximation performance. Additionally, the RBF neural network was used to approximate the function uncertainties of the USV motion system to eliminate the chattering caused by the uninterrupted switching of the sliding surface. Finally, an intelligent control law was introduced based on the sliding mode control with the Lyapunov stability theory. The simulation tests showed that the intelligent control algorithm can effectively guarantee the control accuracy of USVs. In addition, a comparative study with the sliding mode control algorithm based on an RBF network and fuzzy neural network showed that, under the same conditions, the stabilization time of the intelligent control system was 33.33% faster, the average overshoot was reduced by 20%, the control input was smoother, and less chattering occurred compared to the previous two attempts.

show abstract

Development of the USV ‘JingHai-I’ and sea trials in the Southern Yellow Sea

Cited by 81 publications

References 15 publications

Design and Experiments of a Water Color Remote Sensing-Oriented Unmanned Surface Vehicle

Design and Experiments of a Water Color Remote Sensing-Oriented Unmanned Surface Vehicle

Design and validation of an unmanned surface vehicle simulation model

Optimized Radial Basis Function Neural Network Based Intelligent Control Algorithm of Unmanned Surface Vehicles

Contact Info

Product

Resources

About