Low-cost Underwater Inspection Robot Based on Deep Learning

Zichen Guo, Changming Zhang
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Abstract

This paper develops a professional underwater inspection equipment that aims to shorten the time required for pipeline inspection, solve the problems of low intelligence and poor inspection efficiency of the current traditional underwater inspection equipment, and can quickly and accurately complete the underwater inspection. A local area network is established between robots through LoRa wireless communication technology, and data is uploaded to the management and scheduling platform. Data processing and information display are performed by the platform to improve the efficiency of underwater inspection, and the robot is used to replace manual labor and large-scale equipment to reduce inspection costs. The robot uses deep learning to process camera data to further achieve autonomous search and high-precision identification.
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基于深度学习的低成本水下检测机器人
本文开发的专业水下检测设备,旨在缩短管道检测所需的时间,解决目前传统水下检测设备智能化程度低、检测效率差的问题,能够快速、准确地完成水下检测。通过LoRa无线通信技术在机器人之间建立局域网,并将数据上传到管理调度平台。通过平台进行数据处理和信息显示,提高水下检测效率,用机器人代替人工和大型设备,降低检测成本。该机器人利用深度学习技术处理摄像头数据,进一步实现自主搜索和高精度识别。
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