共查询到16条相似文献,搜索用时 46 毫秒
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协同定位是共融机器人研究领域的重要问题.协同定位方案的制定受限于机器人间信息交互的能力.针对长时间通讯中断时多自治水下航行器(AUV)协同定位精度明显下降的问题,借鉴同时定位与制图(SLAM)方法,提出了基于FastSLAM框架的同时定位与跟踪(SLAT)算法.将主AUV视为非合作目标,在从AUV上建立起一个关于主AUV的运动估计器,利用从AUV上声呐传感器实时获取的相对量测信息,在对主AUV运动状态估计的同时,完成对从AUV自定位精度的提升.仿真实验结果表明,在长时间通讯中断发生的条件约束下,相比于传统的航位推算方法,所提出的SLATF1.0和2.0算法能够有效减小定位误差,2.0算法对于探测精度变化等因素的影响具有更好适应性. 相似文献
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融合无人水下航行器(UUV)内部航位递推估计和外部量测信息的协同定位方法是一种提高只配备低精度自定位装置的UUV定位精度的有效手段。当协同系统结构固定时,滤波器的选择就决定了精度提高的幅度。针对扩展卡尔曼滤波(EKF)在处理非线性系统时具有较大的截断误差和繁琐的计算,提出了使用sigma点卡尔曼滤波(SPKF)的协同定位方法。与EKF相比,无味卡尔曼滤波(UKF)和中心差分卡尔曼滤波(CDKF)具有更好的鲁棒性,在没有增加计算复杂度的基础上进一步提高了UUV的定位精度。仿真比较了采用不同滤波算法的协同定位方法提高定位精度的效果,验证了利用sigma点卡尔曼滤波的多UUV协同定位方法的有效性和一致性。 相似文献
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利用多个体之间的相对信息提高个体的定位精度的协同导航是一个很值得探讨的问题。自治水下航行器(AUV)在移动长基线(MLBL)网络中获取各应答器的位置信息并解算出相对各应答器的距离量测后,再通过贝叶斯滤波算法集中式提高其定位精度。但是,集中式利用量测的方法没有考虑由于水下环境的宽广性和水下传感器的限制导致的声信号在AUV和应答器间的往返时间内AUV的移动和应答器间位置的差异所带来的影响。首先以并行滤波的形式总结了集中式扩展卡尔曼滤波(EKF)协同导航方法,并针对集中式利用量测的不利因素,提出了按照异时量测的产生顺序即时更新AUV状态的更有效的序贯EKF协同导航算法,最后在仿真中将两种处理方法进行了比较。 相似文献
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无人水下航行器(UUV)在复杂多变的海洋环境中作业时,推进器的故障可阻挠使命的执行,严重时还可能造成UUV的丢失与损毁。为增强UUV的安全保障能力,针对UUV多台推进器的故障定位问题,采用基于几何相关性分析的方法,设计了UUV同一平面多推进器的故障定位算法,并提出了故障定位约束条件,通过仿真实验验证了所提算法的有效性。 相似文献
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在移动长基线(MLBL)定位结构中,虽可利用基于水声传播延迟(TOF)原理获取的量测信息和贝叶斯滤波器(如扩展卡尔曼滤波(EKF))提高低自定位能力无人水下航行器(UUV)的定位精度,但较高的测量误差会降低这种提高的幅度.根据水声通信的特点提出了一种相关性假设并构建了误差修正算法(ECA),在设定条件下利用误差间的相关性减小量测误差,从而实现量测的粗估计.仿真结果表明,先粗估计量测值再结合贝叶斯滤波器,可显著提高配备低精度自定位传感器的UUV的定位精度. 相似文献
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水下航行器动力定位是通过对水下航行器的多个螺旋桨推进器的转速、推力进行控制调节以抵御外界环境扰动,体现了水下航行器在外界环境扰动下执行各种任务的能力.通过对随机波浪扰动下的水下航行器前向动力定位进行建模仿真,分析得到各个状态特性与环境扰动分量对水下航行器动力定位性能的影响.进行了水下航行器的运动方程和螺旋桨动力学特性的精确建模;再针对波频扰动下的变参数问题以及控制器的鲁棒性和自适应性要求,建立了水下航行器动力定位滑模控制器;最后,将PM谱的随机波浪扰动应用于动力定位仿真研究,仿真结果显示,螺旋桨的动力学特性、幅值限制以及波浪的流速与加速度信息直接影响了水下航行器的动力定位性能. 相似文献
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随着极区经济利益和战略意义日益凸显,水下航行器在极区作战使用的需求逐步清晰。基于极区特殊的气候条件和地理环境,指出了水下航行器在高纬度及跨极区航行时,需要重点考虑导航、控制、仿真试验等多个问题。仿真试验结果验证了基于格网导航算法的水下航行器跨极区控制和导航策略及仿真方法的可行性。 相似文献
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基于主-从系统状态同步的思想,提出了母艇在平面运动中回收自治水下航行器(Autonomous underwater vehicle,AUV)的一种控制方法. 在给出母艇和自治水下航行器的动力学模型基础上,建立了自治水下航行器(从系统)接收母艇(主系统)的状态信息并控制自身接近母艇的主从控制方案,使母艇自主回收水下航行器的问题转化为两者的运动状态同步问题. 利用有限时间稳定性理论,设计了一种在常值海流扰动影响下,自治水下航行器能够在有限时间内被母艇回收的滑模控制器,理论证明和仿真实例证实了该控制器的有效性. 相似文献
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洋流影响下基于运动矢径的AUV协同定位方法 总被引:1,自引:0,他引:1
针对水下自主航行器(AUV)协同定位受水下未知定常洋流影响的问题,给出一种洋流影响下基于运动矢径的AUV协同定位方法.利用AUV的运动学方程和基于运动矢径的量测方程,建立AUV的导航模型;通过扩展的卡尔曼滤波,设计了协同定位滤波算法;利用该算法对洋流速度进行估计,以补偿AUV定位误差.仿真结果表明,该算法能有效估计未知定常洋流速度的大小,并对AUV定位误差进行实时补偿,显著提高了AUV的定位精度. 相似文献
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Supun Randeni Toby Schneider EeShan C. Bhatt Oscar A. Víquez Henrik Schmidt 《野外机器人技术杂志》2023,40(2):346-367
We developed an environmentally adaptive under-ice navigation framework that was deployed in the Arctic Beaufort Sea during the United States Navy Ice Exercise in March 2020 (ICEX20). This navigation framework contained two subsystems developed from the ground up: (1) an on-board hydrodynamic model-aided navigation (HydroMAN) engine, and (2) an environmentally and acoustically adaptive integrated communication and navigation network (ICNN) that provided acoustic navigation aiding to the former. The HydroMAN synthesized measurements from an inertial navigation system (INS), ice-tracking Doppler velocity log (DVL), ICNN and pressure sensor into its self-calibrating vehicle flight dynamic model to compute the navigation solution. The ICNN system, which consisted of four ice buoys outfitted with acoustic modems, trilaterated the vehicle position using the one-way-travel-times (OWTT) of acoustic datagrams transmitted by the autonomous underwater vehicle (AUV) and received by the ice buoy network. The ICNN digested salinity and temperature information to provide model-assisted real-time OWTT range conversion to deliver accurate acoustic navigation updates to the HydroMAN. To decouple the contributions from the HydroMAN and ICNN subsystems towards a stable navigation solution, this article evaluates them separately: (1) HydroMAN was compared against DVL bottom-track aided INS during pre-ICEX20 engineering trials where both systems provided similar accuracy; (2) ICNN was evaluated by conducting a static experiment in the Arctic where the ICNN navigation updates were compared against GPS with ICNN error within low tens of meters. The joint HydroMAN-ICNN framework was tested during ICEX20, which provided a nondiverging high-resolution navigation solution—with the majority of error below 15 m—that facilitated a successful AUV recovery through a small ice hole after an 11 km untethered run in the upper and mid-water column. 相似文献
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This paper studies the localization problem of autonomous underwater vehicles (AUVs) constrained by limited size, power and payload. Such AUVs cannot be equipped with heavy sensors which makes their underwater localization problem difficult. The proposed cooperative localization algorithm is performed by using a single surface mobile beacon which provides range measurement to bound the localization error. The main contribution of this paper is twofold: 1) The observability of single beacon based localization is first analyzed in the context of nonlinear discrete time system, deriving a sufficient condition on observability. It is further compared with observability of linearized system to verify that a nonlinear state estimation is necessary. 2) Moving horizon estimation is integrated with extended Kalman filter (EKF) for three dimensional localization using single beacon, which can alleviate the computational complexity, impose various constraints and make use of several previous range measurements for each estimation. The observability and improved localization accuracy of the localization algorithm are verified by extensive numerical simulation compared with EKF. 相似文献
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随着海洋科技发展, 自主水下航行器(AUVs)协作执行任务技术被广泛应用, AUVs的准确定位是实现AUV集群协同作业的基础技术要求. 然而, 在协同定位系统中, AUVs间的异步时钟会影响测距精度, 并且惯性测量系统推算的速度有较大误差. 本文针对AUV集群系统中的协同定位问题, 提出了利用距离测量和多普勒频移测量进行误差修正的方法. 该方法首先针对时钟异步问题对距离测量的影响, 利用泰勒算法对时钟参数进行估计, 解决了异步时钟问题; 然后, 建立以位置和速度为变量节点和以距离测量和多普勒频移测量为函数节点的因子图模型, 利用因子图的消息传递计算变量的边缘分布, 得到位置和速度的估计; 最后, 针对线性化过程带来的误差, 提出根据变量的协方差矩阵构造自适应因子调整置信度, 从而改变对变量节点的估计. 仿真结果表明, 所提时钟参数能够得到良好估计, 所提算法能够有效抑制惯性导航系统的累积误差. 相似文献
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This paper addresses the problem of decentralized position and velocity estimation in formations of autonomous vehicles. A limited number of vehicles in the formation have access to absolute position measurements, while the rest must rely on range measurements to neighboring agents, local sensor data, and limited communication capabilities to estimate their own position and velocity. The contribution is threefold: (i) a method for designing local state observers for each agent in the formation that rely only on locally available information is presented; (ii) the stability of the continuous‐time linear time‐varying Kalman filter subject to exponentially decaying perturbations in some variables is studied; and (iii) the stability of the error dynamics of the resulting decentralized state observer is analyzed for acyclic formations with fixed topologies, and it is shown that the error converges exponentially fast to the origin for all initial conditions. Simulation results are presented and discussed to validate the proposed solution, as well as assessing its performance under the influence of measurement noise. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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Seonghun Hong Dongha Chung Jinwhan Kim Youngji Kim Ayoung Kim Hyeon Kyu Yoon 《野外机器人技术杂志》2019,36(3):531-546
Underwater visual inspection is an important task for checking the structural integrity and biofouling of the ship hull surface to improve the operational safety and efficiency of ships and floating vessels. This paper describes the development of an autonomous in‐water visual inspection system and its application to visual hull inspection of a full‐scale ship. The developed system includes a hardware vehicle platform and software algorithms for autonomous operation of the vehicle. The algorithms for vehicle autonomy consist of the guidance, navigation, and control algorithms for real‐time and onboard operation of the vehicle around the hull surface. The environmental perception of the developed system is mainly based on optical camera images, and various computer vision and optimization algorithms are used for vision‐based navigation and visual mapping. In particular, a stereo camera is installed on the underwater vehicle to estimate instantaneous surface normal vectors, which enables high‐precision navigation and robust visual mapping, not only on flat areas but also over moderately curved hull surface areas. The development process of the vehicle platform and the implemented algorithms are described. The results of the field experiment with a full‐scale ship in a real sea environment are presented to demonstrate the feasibility and practical performance of the developed system. 相似文献