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Towards stereo vision SLAM based pose estimation for ship hull inspection

机译:朝着基于立体视觉SLAM的姿态估计进行船体检查

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The introduction of foreign species imposes one of the greatest threats to any indigenous ecosystem. As the world's main means of transport of global goods, ships introduce the major part of unwanted marine organisms of which a significant part resides on the hull of ships. Before taking measures to clean these invading organisms, ship hull inspections are necessary. To this end, using autonomous underwater vehicles (AUV) is more desirable than sending divers, which has inherent problems in cost. For the AUV to operate, a pose (position and orientation) estimation system is required. This paper reports on the current development towards a real time, stereo camera and SLAM (Simultaneous Localization and Mapping) based localization system for underwater ship hull inspection. Based on underwater footage filmed at ship hull inspections, the development of the first-generation extended Kalman filter (EKF) SLAM system using a stereo camera and the employed landmark tracking techniques are presented. Serving as a basis for future development, an evaluation of the system's ship hull tracking capability, measurement precision and real-time performance is given by experiments. Preliminary results show that this on-board sensor based system has the potential to be a promising instrument for ship relative pose estimation.
机译:外来物种的引进对任何土著生态系统构成了最大的威胁之一。作为世界上全球货物运输的主要手段,船舶引入了有害的海洋生物的大部分,其中很大一部分位于船舶的船体上。在采取措施清洁这些入侵生物之前,必须对船体进行检查。为此,与派遣潜水员相比,更需要使用自动水下航行器(AUV),这在成本方面存在固有的问题。为了使AUV运行,需要一个姿势(位置和方向)估计系统。本文报道了当前的发展趋势,即基于实时摄像机和基于SLAM(同时定位和地图绘制)的水下船体检查定位系统。基于在船体检查中拍摄的水下录像,介绍了使用立体摄像机开发的第一代扩展卡尔曼滤波器(EKF)SLAM系统以及采用的地标跟踪技术。作为未来开发的基础,通过实验对系统的船体跟踪能力,测量精度和实时性能进行了评估。初步结果表明,这种基于船上传感器的系统有可能成为船舶相对姿态估计的有前途的工具。

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