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无人水面艇(USV):自主船开发与传感器集成系统用于水深测量。

An Unmanned Surface Vehicle (USV): Development of an Autonomous Boat with a Sensor Integration System for Bathymetric Surveys.

机构信息

Department of Electrical and Computer Engineering, University of Texas at El Paso, El Paso, TX 79968, USA.

Department of Earth, Environmental and Resource Sciences, University of Texas at El Paso, El Paso, TX 79968, USA.

出版信息

Sensors (Basel). 2023 Apr 30;23(9):4420. doi: 10.3390/s23094420.

Abstract

A reliable yet economical unmanned surface vehicle (USV) has been developed for the bathymetric surveying of lakes. The system combines an autonomous navigation framework, environmental sensors, and a multibeam echosounder to collect submerged topography, temperature, and wind speed and monitor the vehicle's status during prescribed path-planning missions. The main objective of this research is to provide a methodological framework to build an autonomous boat with independent decision-making, efficient control, and long-range navigation capabilities. Integration of sensors with navigation control enabled the automatization of position, orientation, and velocity. A solar power integration was also tested to control the duration of the autonomous missions. The results of the solar power compared favorably with those of the standard LiPO battery system. Extended and autonomous missions were achieved with the developed platform, which can also evaluate the danger level, weather circumstances, and energy consumption through real-time data analysis. With all the incorporated sensors and controls, this USV can make self-governing decisions and improve its safety. A technical evaluation of the proposed vehicle was conducted as a measurable metric of the reliability and robustness of the prototype. Overall, a reliable, economic, and self-powered autonomous system has been designed and built to retrieve bathymetric surveys as a first step to developing intelligent reconnaissance systems that combine field robotics with machine learning to make decisions and adapt to unknown environments.

摘要

已经开发出一种可靠且经济的无人水面艇(USV),用于湖泊的水深测量。该系统结合了自主导航框架、环境传感器和多波束回声测深仪,用于收集水下地形、温度和风速,并在预定的路径规划任务期间监测车辆的状态。本研究的主要目的是提供一个构建具有独立决策、高效控制和远程导航能力的自主船的方法框架。传感器与导航控制的集成实现了位置、方向和速度的自动化。还测试了太阳能集成以控制自主任务的持续时间。太阳能的结果与标准 LiPO 电池系统的结果相当。通过实时数据分析,使用开发的平台实现了扩展和自主任务,该平台还可以评估危险级别、天气情况和能耗。通过所有集成的传感器和控制,这种 USV 可以做出自主决策并提高其安全性。对所提出的车辆进行了技术评估,作为对原型可靠性和鲁棒性的可衡量指标。总体而言,已经设计和构建了一种可靠、经济且自供电的自主系统,以进行水深测量作为开发将现场机器人技术与机器学习相结合以做出决策和适应未知环境的智能侦察系统的第一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6065/10181514/1d0e3484be16/sensors-23-04420-g001.jpg

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