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# 基于scan context和CNN的重定位研究
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#1-Day Learning, 1-Year Localization: Long-Term LiDAR Localization Using Scan Context Image
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2019 ICRA
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##SCI localization framework
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![](1.png)
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##SCI
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通过实验验证了与单通道图像训练相比的一点改 进。提出的sci比sc具有更高的分辨能力,是一种更适合cnn输入的格式。这个过程如图所示。我们注意到,进一步研究单色图像或彩色地图选择的网络调谐可以提高定位性能。
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![](2.png)
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Matlab使用colormap Jet 可以将灰度图像生成彩色的热度图,灰度值越高,色彩偏向暖色调。相反亦然。
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![](3.png)
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##CNN选择
cnn网络
![](4.png)
输入:
1.N-way SCI Augmentation
2.热编码向量指示类别
输出:
scorevector
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![](5.png)
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##Unseen place
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![](6.png)
新建文件(夹)
上传文件(夹)
scan context