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Confocal Fluorescence Microscopy01:16

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Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
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深度压缩通信和应用在多机器人2D-Lidar中的SLAM:一个智能Huffman算法

Liang Zhang1, Jinghui Deng1

  • 1School of Electrical Engineering and Automation, Anhui University, Hefei 230093, China.

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概括

本研究介绍了使用压缩的2D地图进行多机器人同时定位和映射 (SLAM) 的有效通信框架. 这种新的方法显著减少了99%的带宽,同时保持了协作导航的地图质量.

关键词:
2D-lidar SLAM 2D-lidar SLAM 2D-lidar SLAM 2D-lidar SLAM 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar SLAM 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar 2D-lidar哈夫曼编码器的编码器通信有限的应用程序深度压缩网络深度压缩网络多机器人系统多机器人系统

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 计算机视觉 计算机视觉
  • 人工智能的人工智能

背景情况:

  • 多机器人同时定位和绘图 (SLAM) 系统对于在没有全球导航卫星系统 (GNSS) 覆盖的环境中进行导航至关重要.
  • 大规模多机器人SLAM的可扩展性问题源于对2D地图的高内存和通信带宽要求.
  • 数据压缩对于克服这些系统中的带宽限制至关重要.

研究的目的:

  • 通过使用压缩的2D地图来研究通信效率高的多机器人SLAM.
  • 引入一种架构,以减少带宽来实现全幅地图的传输.
  • 在协作SLAM中解决可扩展性和带宽限制.

主要方法:

  • 一个使用轻量级卷积神经网络 (CNN) 来从二维地图中提取特征的框架.
  • 一个将Huffman和Run-Length编码 (RLE) 结合在一起的编码器,用于地图数据压缩.
  • 一个轻量级的恢复 CNN 旨在恢复地图功能后传输.

主要成果:

  • 在一个两机器人SLAM系统上的实验验证表明,通讯开支降低了99%.
  • 提出的方法有效地保持了地图质量,尽管有很大的压缩.
  • 该框架成功地解决了多机器人SLAM中的带宽限制.

结论:

  • 开发的压缩通信策略为多机器人SLAM中的带宽限制提供了实际解决方案.
  • 这种方法提高了协作SLAM应用程序的可扩展性.
  • 在GNSS有限的环境中实现高效的勘探和导航.