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Please wait a minute... For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails Select Research status and development trend of unmanned surface vehicle Yan PENG, Lei GE, Xiaomao LI, Yuxuan ZHONG, Xin ZHANG Journal of Shanghai University（Natural Science Edition）    2019, 25 (5): 645-654.   DOI: 10.12066/j.issn.1007-2861.2041 Abstract （3472）   HTML （382）    PDF（pc） （894KB）（2175）       Knowledge map    Save Unmanned surface vehicle (USV), as an important branch of marine robotics, is a vehicle that operates on the surface of the water automatically, and it can be used for a wide range of military and civil purposes. Compared to other unmanned systems like unmanned aerial vehicle, unmanned ground vehicle and etc., research on USV is more challenging because of the harsh ocean environment and the special motion model of USV, such as high nonlinearity, strong time delay and time varying. This paper summarizes the research status and main achievements of unmanned ships from the aspects of situation awareness, path planning and guidance, and control, and it also describes at some length different development trends of unmanned ships at home and abroad. Finally, forecast on the development and application of unmanned ships in the future is made. Table and Figures | Reference | Related Articles | Metrics | Comments（0） Select Dynamic collision avoidance for unmanned surface vessels under the uncertainty of obstacle velocity Dong QU, Yan PENG, Huayan PU, Jun LUO, Chengyi HUANG, Jun KE Journal of Shanghai University（Natural Science Edition）    2019, 25 (5): 655-667.   DOI: 10.12066/j.issn.1007-2861.2164 Abstract （2610）   HTML （2786）    PDF（pc） （16079KB）（223）       Knowledge map    Save The stability of collision avoidance is directly relate to the safety of unmanned surface vehicle (USV). However, the uncertainty of perception about the velocity of moving obstacles seriously undermine the stability of collision avoidance. Thus, an uncertain velocity obstacle (UVO) method is proposed to solve this problem. In order to improve the stability of collision avoidance at the macro level, an adaptive threshold-based closest point of approach (CPA) is adopted to assess collision risk while a boundary buffer is used to calculate the type of International Regulations for Preventing Collisions at Sea (COLREGS). To prevent changes in collision avoidance strategy, the UVO is modeled in velocity space of the USV, and a gradient descent method is used to determine local optimization of the cost function. Contrast experiments in simulation platform between UVO and VO indicate that the UVO has better performance on three indicators: strategy changes, success rate, and safe distance. Typical encounters such as head-on, crossing, and overtaking are conducted in sea trials. The USV successfully avoids each moving obstacle in the experiment. The results demonstrate the stability and safety of the UVO method. Table and Figures | Reference | Related Articles | Metrics | Comments（0） Select Maritime ships detection for USV based on object proposals Wei CHEN, Yi YANG, Xiaomao LI, Yuan LIU, Xin ZHANG Journal of Shanghai University（Natural Science Edition）    2019, 25 (5): 668-678.   DOI: 10.12066/j.issn.1007-2861.1981 Abstract （1832）   HTML （1403）    PDF（pc） （10993KB）（141）       Knowledge map    Save Maritime ships detection is one of the main tasks in unmanned surface vehicle (USV)'s visual system. This paper proposes a kind of USV maritime ships detection algorithm based on object proposals. Firstly, a modified edge boxes algorithm is utilized to extract the edge information of the image, and an objectness score function is established to obtain object proposals. Secondly, a histogram of oriented gradient (HOG) feature model is built for the ship, and the support vector machine (SVM) is utilized to iteratively train a classifier by a bootstrap method. Finally, the feature descriptor of object proposals is fed into the classifier, and detecting the ship. In addition, the sea-sky line is utilized to further improve the detection performance of the algorithm based on the environment of USV. The experimental results show that the algorithm can rapidly and accurately detect the ship on the sea, and achieve a relatively high detection rate. And the algorithm has strong robustness to the change of the scale and the illumination conditions. Table and Figures | Reference | Related Articles | Metrics | Comments（0）