共查询到20条相似文献，搜索用时 125 毫秒
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搭载侧扫声呐(side-scan sonar,SSS)的自主水下航行器(autonomous underwater vehicle,AUV) 执行大规模海上搜救(search and rescue,SAR)任务时通常采用区域覆盖路径规划(coverage path planning, CPP)技术。由于任务失败的可能性很大,因此实现完全覆盖的同时,优先搜索目标可能存在的区域并提高侧扫声呐的数据质量十分必要。针对以上问题,提出了一种面向操作的全覆盖路径规划方法 SAS-A*,通过生成全覆盖路径,有效提高目标可能存在区域的覆盖速度和声呐数据的质量。该方法基于救援专家预测的目标位置和轨迹,采用二维高斯分布建立目标存在的概率模型,作为路径规划的先验信息。提出的 SAS-A*算法将下一个路径点选择策略转化为多目标决策问题,采用加权度量法来进行多目标优化,使 AUV 以更短路程、更少的转弯优先搜索目标可能出现的区域。仿真结果表明：SAR- A*路径规划方法适用于大规模搜救任务,可快速提高目标的搜索概率。 相似文献
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为实现自主水下潜器(Autonomous Underwater Vehicle,简称 AUV)的自主目标探测识别与定位任务,以侧扫声呐数据为依据,考虑到扫描式声呐成像的特点,针对金属球类目标,基于 Darknet 框架设计了一种轻量化深度学习目标识别模型,并结合人工特征进行目标特性分析。同时对声呐图像设计了有效的图像增强方法。实验表明：上述目标识别方法在保证目标识别准确率的同时,具有较高的目标识别速率,适于低功耗嵌入式平台部署。 相似文献
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侧扫声呐回波信号是形成侧扫声呐图像的基础,是侧扫声呐系统对水下目标的最直接观测量, 将一维小波变换与非线性增强方法相结合,提出了一种基于小波变换的侧扫声呐回波信号非线性增强算法, 用以改善侧扫声呐图像对比度低、噪声强度大的问题。首先利用改进的 Bayes 阈值对侧扫声呐 ping 信号进行一维小波分解,提取信号特征信息;然后利用 2 种不同的非线性函数对高、低频小波系数进行处理;最后利用小波反变换重构信号,形成增强后的侧扫声呐图像。实测数据验证结果表明：利用该算法对侧扫声呐 ping 信号进行处理,实现了侧扫声呐图像对比度的增强和对噪声的抑制,可以获取较好的图像视觉效果。 相似文献
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韩恩权 《数字海洋与水下攻防》2021,4(4):264-268
针对自主式潜航器航行中自主规避障碍物传统算法存在的障碍物区域探测精度低、障碍物识别不准确、潜航器航路不最优等问题,采用三维成像声呐和深度学习算法开展了自主规避障碍物优化技术研究, 并通过仿真和漳河水库试验测试了本算法的有效性,可有效提高航行器规避障碍物的成功率和精度,以及 AUV 航行路径优化。 相似文献
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胡红波 《数字海洋与水下攻防》2019,2(5):1-6
针对侧扫声呐图像噪声干扰严重、分辨率低、目标轮廓模糊等特点，提出了一种基于LOG算子的侧扫声呐图像水下小目标检测算法。首先，根据侧扫声呐图像中水下小目标成像特点，对声呐图像进行滤波及聚类分割，大幅降低图像中噪声；然后，采用斑点检测思想，提取侧扫声呐图像中疑似目标区域；最后，基于自动阈值分割算法对声呐图像进行分割，获取目标区域二值图像，使用二阶矩估计目标尺度，剔除虚假目标，最终实现水下小目标准确检测。实验结果表明：该方法计算速度快、检测成功率高，对侧扫声呐图像中的水下小目标具有良好的检测效果。 相似文献
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侧扫声呐图像受混响效应影响导致侧扫声呐图像斑点噪声强,边缘模糊,纹理较弱,严重时还会掩盖海底地貌。噪声方差是许多侧扫声呐图像变换域去噪算法的必要参数。指出了侧扫声呐图像在乘性噪声的影响下灰度值溢出的问题,并且以侧扫声呐图像中乘性噪声为背景,考虑灰度值范围对乘性噪声的抑制作用,提出了一种基于弱纹理块的噪声估计方法。算法主要根据噪声的散射模型,将侧扫声呐图像经过幂变换和对数变换,将服从瑞利分布的乘性斑点噪声变换为高斯白噪声,基于变换图像的梯度协方差矩阵和弱纹理块的动态选择,以迭代的方式确定噪声方差。实验结果表明:该算法能够去除灰度值溢出现象对噪声估计的影响,在高亮区域及背景区域的噪声估计结果稳定准确。 相似文献
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程文博 《数字海洋与水下攻防》2023,6(3):353-358
由于受到复杂水声信道影响，侧扫声呐生成图像一般存在分辨率低、细节模糊等问题，这给基于侧扫声呐图像的小目标检测与识别过程带来了一定难度。常见的图像超分辨率处理算法大致可以分为插值算法、稀疏表示的重建算法等。传统插值算法存在图像边缘模糊、细节不清楚的问题，因此提出了一种改进型超分辨率生成对抗网络(SRGAN)结构。该结构可在保留图像中的小目标细节的基础上提升细节特征显示度，并且可使目标边缘更加清晰，可为后续的小目标检测和识别在一定程度上提供技术支持。 相似文献
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基于MRF场的侧扫声呐图像分割方法 总被引：1，自引：0，他引：1
为了利用侧扫声呐进行水下目标自动探测和识别,首先必须将声呐图像分为目标高亮区、海底混响区和目标阴影区.由于声呐图像有强背景噪声,传统的图像分割方法显得无能为力,故采用基于MRF场的图像分割方法来准确地分割.根据侧扫声呐目标的成像特点,建立了分割的约束条件;利用阴影与目标的灰度均值比很小这一特点进行初始分割,然后根据分割后目标与阴影的宽度差来剔除虚假目标,由初始分割的结果求得MRF模型初始参数,再采用迭代条件估计得到最终的模型参数和准确的分割结果.由于考虑了相邻像素间的依赖关系,具有抗噪性强、分割效果好的优点,从理论上说是合理的.实测数据分析也证明了这种算法的优越性. 相似文献
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A randomized kinodynamic path planning algorithm based on the incremental sampling-based method is proposed here as the state-of-the-art in this field applicable in an autonomous underwater vehicle. Designing a feasible path for this vehicle from an initial position and velocity to a target position and velocity in three-dimensional spaces by considering the kinematic constraints such as obstacles avoidance and dynamic constraints such as hard bounds and non-holonomic characteristic of AUV are the main motivation of this research. For this purpose, a closed-loop rapidly-exploring random tree (CL-RRT) algorithm is presented. This CL-RRT consists of three tightly coupled components: a RRT algorithm, three fuzzy proportional-derivative controllers for heading and diving control and a six degree-of-freedom nonlinear AUV model. The branches of CL-RRT are expanded in the configuration space by considering the kinodynamic constraints of AUV. The feasibility of each branch and random offspring vertex in the CL-RRT is checked against the mentioned constraints of AUV. Next, if the planned branch is feasible by the AUV, then the control signals and related vertex are recorded through the path planner to design the final path. This proposed algorithm is implemented on a single board computer (SBC) through the xPC Target and then four test-cases are designed in 3D space. The results of the processor-in-the-loop tests are compared by the conventional RRT and indicate that the proposed CL-RRT not only in a rapid manner plans an initial path, but also the planned path is feasible by the AUV. 相似文献
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针对海底侧扫声纳图像对比度低、纹理弱、噪声严重等问题,提出了一种基于第二代Curvelet变换的声纳图像增强算法。首先对原始声纳图像进行多尺度、多方向的Curvelet变换分解,得到低频子带和高频子带;然后引入非线性S型函数对低频系数进行处理,提高图像整体的对比度;采用一种可以避免过度增强的新型非线性函数对各尺度的高频子带系数进行处理,提高图像整体的对比度,增强图像边缘和纹理细节,并通过估计噪声水平设定阈值进行阈值降噪。最后经Curvelet逆变换得到增强图像。实验表明,该方法不仅改善了海底侧扫声纳图像对比度低的问题,而且降低了噪声,突出了声纳图像的边缘和纹理细节。 相似文献
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Pan-Mook Lee Seok-Won Hong Yong-Kon Lim Chong-Moo Lee Bong-Hwan Jeon Jong-Won Park 《Oceanic Engineering, IEEE Journal of》1999,24(3):388-395
This paper presents a discrete-time quasi-sliding mode controller for an autonomous underwater vehicle (AUV) in the presence of parameter uncertainties and a long sampling interval. The AUV, named VORAM, is used as a model for the verification of the proposed control algorithm. Simulations of depth control and contouring control are performed for a numerical model of the AUV with full nonlinear equations of motion to verify the effectiveness of the proposed control schemes when the vehicle has a long sampling interval. By using the discrete-time quasi-sliding mode control law, experiments on depth control of the AUV are performed in a towing tank. The controller makes the system stable in the presence of system uncertainties and even external disturbances without any observer nor any predictor producing high rate estimates of vehicle states. As the sampling interval becomes large, the effectiveness of the proposed control law is more prominent when compared with the conventional sliding mode controller 相似文献
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《中国海洋工程》2021,(3)
In recent decades, path planning for unmanned surface vehicles(USVs) in complex environments, such as harbours and coastlines, has become an important concern. The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with multiple dynamic obstacles. In this study,we developed a novel path planning method based on the D* lite algorithm for real-time path planning of USVs in complex environments. The proposed method has the following advantages:(1) the computational time for replanning is reduced significantly owing to the use of an incremental algorithm and a new method for modelling dynamic obstacles;(2) a constrained artificial potential field method is employed to enhance the safety of the planned paths; and(3) the method is practical in terms of vehicle performance. The performance of the proposed method was evaluated through simulations and compared with those of existing algorithms. The simulation results confirmed the efficiency of the method for real-time path planning of USVs in complex environments. 相似文献
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针对海洋环境下自主水下机器人（AUV）的路径规划问题，提出了一种基于框架四叉树的改进量子粒子群算法（QPSO），首先使用框架四叉树的方法对障碍物建模，该方法提高了建模的精度且对后续算法的效率也有极大的改进，之后设计改进的量子粒子群算法，并且结合水下环境的特殊性设计适应度函数，综合考虑航线路径长度、偏转角度以及海流影响，使得算法可以在水下环境中寻得能耗最短的解路径。最后通过仿真试验验证，相比于传统的栅格法和粒子群算法，改进量子粒子群算法的运算时间更短，收敛速度更快，其独特的适应度函数可以使AUV能更好适应水下多变的环境，且能利用海流设计能耗更小的路径，具有很大的实用价值。 相似文献
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This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow (underwater acoustic images) is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust. 相似文献
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针对UUV避碰声呐探测障碍物过程中自主选择分割阈值进行障碍物检测的问题,提出了基于分区自适应阈值的障碍物检测算法。首先将避碰声呐图像均匀分为相同大小的图像块,对每个图像块基于最大类间方差算法确定该区域障碍物图像分割的高低阈值,然后对检测到的障碍物进行形态学处理去除孤立噪声点,对目标区域进行连通性分析及内部空洞处理,最终得到完整的障碍物轮廓信息。通过湖试数据验证表明了该方法对声呐障碍物检测的有效性。 相似文献