3D Ensemble-Based Online Oceanic Flow Field Estimation for Underwater Glider Path Planning
University of Technology Sydney（悉尼科技大学）；Australian Bureau of Meteorology（澳大利亚气象局）；Defence Science and Technology Group, Department of Defence, Australia（澳大利亚国防部国防科学技术集团）
Felix H. Kong, K. Y. Cadmus To, Gary Brassington, Stuart Anstee, Robert Fitch
Estimating ocean flow fields in 3D is a critical step in enabling the reliable operation of underwater gliders and other small, low-powered autonomous marine vehicles. Existing methods produce depth-averaged 2D layers arranged at discrete vertical intervals, but this type of estimation can lead to severe navigation errors. Based on the observation that real-world ocean currents exhibit relatively low velocity vertical components, we propose an accurate 3D estimator that extends our previous work in estimating 2D flow fields as a linear combination of basis flows. The proposed algorithm uses data from ensemble forecasting to build a set of 3D basis flows, and then iteratively updates basis coefficients using point measurements of underwater currents. We report results from experiments using actual ensemble forecasts and synthetic measurements to compare the performance of our method to the direct 3D extension of the previous work. These results show that our method produces estimates with dramatically lower error metrics, with and without measurement noise.
Online Navigation Planning for Long-term Autonomous Operation of Underwater Gliders
Oxford Robotics Institute（牛津机器人研究所）；Department of Engineering Science, University of Oxford（牛津大学工程科学系）；Optiver（Optiver公司）；Stateful Robotics（Stateful Robotics公司）；National Oceanography Centre（国家海洋研究中心）；School of Environmental Sciences, University of East Anglia（东安格利亚大学环境科学学院）；Scottish Association for Marine Science（苏格兰海洋科学协会）
Parallelization of Path Planning Algorithms for AUVs Concepts, Opportunities, and Program-Technical Implementation
现代自主水下航行器（AUV）具有先进的传感能力，包括声纳，摄像头，声学通信和各种生物传感器。AUV可以利用收集到的信息来了解其环境，而不仅仅是感知其环境并存储数据用于任务后检查，并基于这种理解自主调整其行为以提高其任务的整体有效性。许多这样的任务是高度计算密集型的。本文介绍了一个案例研究的结果，说明了一个能源感知，众核计算架构的有效性，在电池供电的AUV进行板载路径规划。先前发布的路径规划算法被移植到SCC上，SCC是英特尔开发的实验性48核单芯片系统。针对不同的内核数量和其他系统参数，测量了应用程序的性能、功耗和能耗。该案例研究表明，计算密集型任务可以在主要依赖于电池电源的AUV内执行。未来的计划包括在Teledyne Webb Research Slocum滑翔机内部署和测试SCC系统。
Georgia Institute of Technology（佐治亚理工学院）；Purdue University（普渡大学）；University of South Florida（南佛罗里达大学）；Skidaway Institute of Oceanography, University of Georgia（佐治亚大学斯基德韦海洋研究所）；University of Georgia（佐治亚大学）
ReefGlider: A highly maneuverable vectored buoyancy engine based underwater robot
Woods Hole Oceanographic Institution (WHOI)（伍兹霍尔海洋研究所）；University of Wisconsin-Madison（威斯康星大学麦迪逊分校）；Massachusetts Institute of Technology（麻省理工学院）；Massachusetts Institute of Technology and Woods Hole Oceanographic Institution Joint Program（麻省理工学院与伍兹霍尔海洋研究所联合项目）
Fish-inspired tracking of underwater turbulent plumes
Graduate Aerospace Laboratories, California Institute of Technology（加州理工学院研究生航空实验室）；Mechanical and Civil Engineering, California Institute of Technology（加州理工学院机械与土木工程系）
