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[Objective ] To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. [Method]On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. [Results]The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. [Conclusions]The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved. 相似文献
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针对道路交通环境中路面标志识别涉及的数据集较少和识别准确率不足的问题,研究了基于深度卷积生成对抗网络的道路表面指示标志的识别方法.在深度卷积生成对抗网络的结构基础上,根据具体应用修改生成网络和判别网络的损失函数,并用随机梯度下降算法替代原始的优化器,对指示标志的原始样本集进行样本生成,以增加样本数据量.基于Faster R-CNN算法进行路面标志的特征提取,实现路面指示标志的识别,并基于迁移学习对识别模型进行微调,将目标识别效果应用于实际道路环境中.实验结果表明,通过深度卷积生成对抗网络生成的样本图像有效地扩增了路面标志的数据集,增广后的多类目标识别的mAP提高了17.1%,小样本情况下的识别准确率随着样本量的增加和样本质量的改善而得到了明显的提高. 相似文献
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实时获取准确的长江在航船舶的交通流状态信息是长江海事监管智能化的基础。在分析长江流域航运监管交通流信息采集需求基础上,设计了多源信息融合的长江在航船舶交通流状态信息采集系统三层构架,其中由IC(Interated Circuitcard)卡子系统、GPS(Global Positioning System)子系统、CCTV(Closed Circuit Television)子系统、雷达子系统、AIS(Automatic Identification System)子系统、RFID(Radio Frequency Identification)子系统以及激光扫描子系统组成信息采集层,依托现有的长江航运信息网络与公共通信网络设施组成信息传输层,由交通流数据库、电子航道图以及信息处理系统组成信息处理层。同时,分析了AIS子系统、RFID子系统以及激光扫描子系统采集船舶交通流信息关键技术,并展望后续研究方向。 相似文献
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针对生产中实际问题,对现生产的CA6102发动机燃烧系统进行了改进设计,并在单缸机台架上采用CB-466发动机燃烧分析仪等测试仪器,对改进设计的燃烧系统燃烧过程进行了测试与分析。经改进设计,发动机燃烧过程得到较好的改善,动力性提高,燃油消耗率下降,且生产时无需更改加工设备,生产上易于实现。 相似文献
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