课程资源下载汇总（三维点云处理、多传感器融合、机器人学状态估计）

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已于 2024-05-06 17:57:51 修改

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分类专栏：ＳＬＡＭ入门学习文章标签： ubuntu bug python

于 2021-11-17 21:08:20 首次发布

本文链接：https://blog.youkuaiyun.com/wtlll/article/details/121387393

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这是一份包含3D点云处理、多传感器融合、机器人学状态估计等课程资源的下载汇总。课程涵盖了激光SLAM、多传感器融合技术、状态估计理论等，适合机器人和自动驾驶领域的学习者。讲师包括曾树杰、任乾等，通过学习，可以帮助读者掌握相关领域的关键技术和理论。

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@[TOC](Course resource download summary (3D point cloud processing, multi-sensor fusion, robotics state estimation)）)

1 Introduction

It is convenient for everyone to find information, and in order to avoid frequent harmonization of videos in other places, so I chose to write a collection here, and everyone can save it after seeing it. . .。。。

2. Course content

2.1 `激光SLAM的发展和应用`

Download address：传送门
Course introduction:：

SLAM(Synchronous positioning and map construction) refers to the process in which a moving object calculates its own position while building an environmental map based on the information of the sensor, and solves the problem of positioning and map construction when the robot moves in an unknown environment. At present, SLAM is mainly used in the fields of robots, drones, unmanned driving, and AR. According to the sensor, SLAM is mainly divided into two categories: laser SLAM and visual SLAM (VSLAM). Among them, laser SLAM started earlier than VSLAM, and is relatively mature in theory, technology and product implementation.。

This open class mainly introduces the overall framework of laser SLAM, the development and application of two-dimensional laser SLAM and three-dimensional laser SLAM, the future development trend of laser SLAM and the problems to be solved.
Lecturer: Zeng Shuge