Design and Experiment for an Offshore Nuclear Radiation Emergent Observation System based on an Unmanned Surface Vehicle

Jin, Jiucai; Zhang, Jie; Liu, Deqing; Wang, Dong; Shi, Junnan; Li, Fangxu

doi:10.2112/si90-005.1

Cited by 6 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The sea experiments were executed at Nanjiang dock in Qingdao City, China, on 16-31 July, 2018. During the sea experiments, the hardware system, autonomous control and data acquisition for nuclear radiation were tested [30], and the sea experiments for the USV are shown in Figure 11.…”

Section: Results Of Sea Experimentsmentioning

confidence: 99%

“…In addition, some novelty methods have been applied in the guidance law, such as bioinspired neural [25], deep reinforcement learning methods [26] and vector field [27]. The twin-propeller and twin-hull USV (TPTH-USV) is a usual vehicle for applications due to its good stability and high load [28], such as 'Springer' [29], 'JiuHang-490' [30].…”

Section: Related Workmentioning

confidence: 99%

“…The other integrated sensors contained a gamma detector for nuclear radiation observation, a CTD (Conductivity, Temperature and Depth), a camera and an ultrasonic weather station. More details can be seen in [30]. the USV.…”

Section: 'Jiuhang 490' Usvmentioning

confidence: 99%

“…In Equation (30), at Section 3.3.3, the transformation function of the course was couple with the speed of the USV, and the USV could be seen as a cascade system. Since their relationship is linear, the controllers could be designed by a twin-PID controller, and the diagram for the autonomous control of the USV is shown in Figure 10.…”

Section: Controllersmentioning

confidence: 99%

See 3 more Smart Citations

A Practical Trajectory Tracking Scheme for a Twin-Propeller Twin-Hull Unmanned Surface Vehicle

Jin

Liu

Wang

et al. 2021

JMSE

Self Cite

View full text Add to dashboard Cite

Trajectory tracking is a basis of motion control for Unmanned Surface Vehicles (USVs), which has been researched well for common USVs. The twin-propeller and twin-hull USV (TPTH-USV) is a special vehicle for applications due to its good stability and high load. We propose a three-layered architecture of trajectory tracking for the TPTH-USV which explicitly decomposes into trajectory guidance, a motion limitator and controller. The trajectory guidance transforms an expected trajectory into an expected speed and expected course in a kinematic layer. The motion limitator describes some restriction for motion features of the USV in the restriction layer, such as the maximum speed and maximum yaw rate. The controller is to control the speed and course of the USV in the kinetic layer. In the first layer, an adaptive line-of-sight guidance law is designed by regulating the speed and course to track a curved line considering the sideslip angle. In the second layer, the motion features are extracted from an identified speed and course coupled model. In the last layer, the course and speed controller are designed based on a twin-PID controller. The feasibility and practicability of the proposed trajectory tracking scheme is validated in sea experiments by a USV called ‘Jiuhang 490’.

show abstract

Section: Results Of Sea Experimentsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: 'Jiuhang 490' Usvmentioning

confidence: 99%

Section: Controllersmentioning

confidence: 99%

See 2 more Smart Citations

A Practical Trajectory Tracking Scheme for a Twin-Propeller Twin-Hull Unmanned Surface Vehicle

Jin

Liu

Wang

et al. 2021

JMSE

Self Cite

View full text Add to dashboard Cite

show abstract

“…The vision-based target tracking experiment was carried out using our USV called as 'Jiuhang 490' USV at the Nanjiang port in Qingdao, China from July 17 to August 1, 2018 [23], and a rubber boat was taken as the target vessel, and they were shown in Fig. 3.…”

Section: A Tracking Experimentsmentioning

confidence: 99%

Vision-Based Target Tracking for Unmanned Surface Vehicle Considering Its Motion Features

et al. 2020

Self Cite

View full text Add to dashboard Cite

Target tracking is a key task for maintenance of maritime rights and interests in the coastal countries, which mainly depends on the cruises of large official ships, and their deficiencies are high cost and less stealth. USVs(Unmanned Surface Vehicles) have been gradually employed in maritime ISR(Intelligence, Surveillance and Reconnaissance) due to autonomy, safety and flexibility. In this paper, a target tracking algorithm for USV's vision is proposed, which considers motion features of the USV, such as velocity, pitch and heading. Firstly, a CM(Centroid Matching) method for the target detection is proposed based on FT(Frequency-Tuned) saliency method, which can remove environment disturbances. Secondly, a fDSST(fast Discriminative Scale Space Tracker) is improved for target tracking by considering motion information of the USV from aboard GPS and IMU(Inertial Measurement Unit), where the learning rates of the correlation filters are adjusted adaptively according to variety of the velocity, pitch and heading of the USV. Lastly, the modified target detection and tracking are integrated to acquire a robust tracking result. Based on our USV called as 'Jiuhang 490', sea tracking trials for rubber boat in four encountering scenes are executed at Nanjiang port in Qingdao city, China in July 2018. The favorable performance of the proposed algorithm is quantitatively validated comparing to the original fDSST algorithm in the accuracy of position, scale of the target and the tracking speed. INDEX TERMSTarget tracking, vision tracking, unmanned surface vehicle, target detection JIUCAI JIN received his B.S. and M.S. degrees in physics from Inner Mongolia University, Hohhot, China, in 2001 and 2005 respectively, and Ph.D. degree in physical oceanography from Institute of Oceanology, Chinese Academy of Sciences, in 2011. He is currently an associate researcher at First Institute of Oceanography, Ministry of Natural Resources. His research interests include autonomous control, obstacle avoidance, target detection and tracking, development for Unmanned Surface Vehicle, and applications of USV. JIE ZHANG received his B.S. and M.S. degrees in Inner Mongolia University, China, in 1984 and 1987 respectively, and then stayed in this university as a lecturer until 1990. Then he received his Ph.D. degree in Tsinghua University, China. He is now a researcher of the First Institute of Oceanography, Ministry of Natural Resources. His research interests include surveillance technology and equipment for maritime targets, research and development of autonomous satellite remote sensing technology, coastal high-resolution remote sensing technology and application.

show abstract

Wide baseline stereovision based obstacle detection for unmanned surface vehicles

Jin,

Liu,

et al. 2024

SIViP

View full text Add to dashboard Cite

Design and Experiment for an Offshore Nuclear Radiation Emergent Observation System based on an Unmanned Surface Vehicle

Cited by 6 publications

References 0 publications

A Practical Trajectory Tracking Scheme for a Twin-Propeller Twin-Hull Unmanned Surface Vehicle

A Practical Trajectory Tracking Scheme for a Twin-Propeller Twin-Hull Unmanned Surface Vehicle

Vision-Based Target Tracking for Unmanned Surface Vehicle Considering Its Motion Features

Wide baseline stereovision based obstacle detection for unmanned surface vehicles

Contact Info

Product

Resources

About