Unmanned underwater vehicle autonomous decision control method based on visual depth estimation
The invention discloses an unmanned underwater vehicle autonomous decision control method based on visual depth estimation. The method comprises the following steps: extracting a video image shot by an underwater vehicle in real time, framing the video image, inputting the framed video image into a...
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| creator | ZHU PENGLI ZHANG ZHENRUI YAO SHUHAN LIU YANCHENG XU CHEN ZHAO YOUTAO LYU YINXIN MA CHUAN |
| description | The invention discloses an unmanned underwater vehicle autonomous decision control method based on visual depth estimation. The method comprises the following steps: extracting a video image shot by an underwater vehicle in real time, framing the video image, inputting the framed video image into a geometric analysis depth estimation network for processing, extracting depth features of the image to obtain distance and contour feature information between the underwater vehicle and an obstacle, and synthesizing the distance and contour feature information into a depth image; and inputting the continuous multi-frame depth images into an autonomous decision control network, extracting depth features of the integrated depth images by adopting a convolutional neural network, inputting the depthfeatures as state information into a reinforcement learning network for training, and obtaining a linear velocity and an angular velocity corresponding to the underwater vehicle through continuous iterative optimization.
本发明公 |
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本发明公</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2020</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyzEKwkAQheE0FqLeYTyAYIhI2hAUKyutw7g7koXdmZCZjdd3Cw9g9eDne-tqeHJCZvKQ2dP8QaMZFhqDiwSYTViSZAVPLmgQBidss0RIZKN4eKGWb-lL0IyxuMlGILWQ0IrfVqs3RqXdbzfV_np59LcDTTKQTuiIyYb-Xtd1czq257Zr_jFfC6096Q</recordid><startdate>20200626</startdate><enddate>20200626</enddate><creator>ZHU PENGLI</creator><creator>ZHANG ZHENRUI</creator><creator>YAO SHUHAN</creator><creator>LIU YANCHENG</creator><creator>XU CHEN</creator><creator>ZHAO YOUTAO</creator><creator>LYU YINXIN</creator><creator>MA CHUAN</creator><scope>EVB</scope></search><sort><creationdate>20200626</creationdate><title>Unmanned underwater vehicle autonomous decision control method based on visual depth estimation</title><author>ZHU PENGLI ; ZHANG ZHENRUI ; YAO SHUHAN ; LIU YANCHENG ; XU CHEN ; ZHAO YOUTAO ; LYU YINXIN ; MA CHUAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN111340868A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2020</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>ZHU PENGLI</creatorcontrib><creatorcontrib>ZHANG ZHENRUI</creatorcontrib><creatorcontrib>YAO SHUHAN</creatorcontrib><creatorcontrib>LIU YANCHENG</creatorcontrib><creatorcontrib>XU CHEN</creatorcontrib><creatorcontrib>ZHAO YOUTAO</creatorcontrib><creatorcontrib>LYU YINXIN</creatorcontrib><creatorcontrib>MA CHUAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ZHU PENGLI</au><au>ZHANG ZHENRUI</au><au>YAO SHUHAN</au><au>LIU YANCHENG</au><au>XU CHEN</au><au>ZHAO YOUTAO</au><au>LYU YINXIN</au><au>MA CHUAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Unmanned underwater vehicle autonomous decision control method based on visual depth estimation</title><date>2020-06-26</date><risdate>2020</risdate><abstract>The invention discloses an unmanned underwater vehicle autonomous decision control method based on visual depth estimation. The method comprises the following steps: extracting a video image shot by an underwater vehicle in real time, framing the video image, inputting the framed video image into a geometric analysis depth estimation network for processing, extracting depth features of the image to obtain distance and contour feature information between the underwater vehicle and an obstacle, and synthesizing the distance and contour feature information into a depth image; and inputting the continuous multi-frame depth images into an autonomous decision control network, extracting depth features of the integrated depth images by adopting a convolutional neural network, inputting the depthfeatures as state information into a reinforcement learning network for training, and obtaining a linear velocity and an angular velocity corresponding to the underwater vehicle through continuous iterative optimization.
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Unmanned underwater vehicle autonomous decision control method based on visual depth estimation |
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