1.验证自己的bag cartographer ROS提供了一个工具cartographer_rosbag_validate来自动分析包中的数据.在尝试调试cartographer之前运行这个工具. 操作方式: cartographer_rosbag_validate -bag_filename your_bag.bag 2.创建一个.lua配置文件 cartographer非常灵活且可以配置用于任何机器人上.机器人配置读取来自于一个options的数据结构,该数据结构必须定义在一个Lua脚本里

注意在运行bag包,之前需要去执行source install_isolated/setup.bash 1.Deutsches Museum 下载并启动2D的backpack demo: wget -P ~/Downloads https://storage.googleapis.com/cartographer-public-data/bags/backpack_2d/cartographer_paper_deutsches_museum.bag roslaunch cartographer_

谷歌自己提供了安装方法,但是安装比较繁琐,我做了一定的修改,代码放到个人github上,https://github.com/hitcm/. ros下面的安装非常快捷,只需要catkin_make即可. 更多细节,可以看看知乎的问题https://www.zhihu.com/question/51348391/answer/125560951?from=profile_answer_card 个人理解错误的地方还请不吝赐教,转载请标明出处,内容如有改动更新,请看原博:http://www.cnb

github source: https://github.com/googlecartographer/cartographer_turtlebot 1. Building & Installation Installation has been tested on Ubuntu 14.04 (Trusty) with ROS Indigo, but may also work on Ubuntu 16.04 (Xenial) with ROS Kinetic. We recommend us

Cartographer is a backpack equipped with Simultaneous Localization and Mapping (SLAM) technology. 1. Platform Dell PC installed Ubuntu 14.4 and ROS Indigo. 2. Building & Installation We recommend using wstool and rosdep. For faster builds, we also re

转载自谷歌Cartographer学习(1)-快速安装测试 代码放到个人github上,https://github.com/hitcm/ 如下,需要安装3个软件包,ceres solver.cartographer和cartographer_ros 1.首先安装ceres solver,选择的版本是1.11,路径随意. git clone https://github.com/hitcm/ceres-solver-1.11.0.git mkdir build cd ceres-solver-1

ROS_Kinetic_27 在ROS中使用Cartographer进行SLAM Cartographer是谷歌新開源的通用的2D和3D定位與構圖同步的SLAM工具,並提供ROS接口. 论文Real-Time Loop Closure in 2D LIDAR SLAM下载地址: http://download.csdn.net/detail/zhangrelay/9648192 资料汇总请参考:http://blog.csdn.net/zhangrelay/article/details/527

中文资料稍后补充 Introducing Cartographer By Tully Foote on October 5, 2016 10:11 AM From Damon Kohler, Wolfgang Hess, and Holger Rapp, Google Engineering We are happy to announce the open source release of Cartographer, a real-time SLAM library in 2D and 3D

安装过程: 官方安装教程: https://google-cartographer-ros.readthedocs.io/en/latest/index.html # Install wstool and rosdep. sudo apt-get update sudo apt-get install -y python-wstool python-rosdep ninja-build # Create a new workspace in 'catkin_ws'. mkdir catkin_w

在官网的基础上稍加修改,但保证代码都是最新的 我的系统配置: Debian9 strech,  ROS lunar 该方法对 ubuntu 系列操作系统以及其他ROS版本同样适用. 1.  安装依赖库 sudo apt-get install -y \ g++ \ git \ google-mock \ libboost-all-dev \ libcairo2-dev \ libeigen3-dev \ libgflags-dev \ libgoogle-glog-dev \ liblua5.2

原文链接:http://blog.csdn.net/zyh821351004/article/details/52421005 cartographer与karto的比较 1. 两者采取的都是图优化框架.  采取的优化库不一致, karto采取的是spa(karto_slam)或g2o(nav2d), cartographer采取的是google的ceres构建problem优化. karto的前端与后端采取的是单线程进行,cartographer按paper说明,采取的是4线程后端优化,还在进

一.Cartographer编译 cartographer依赖的大型第三方库很少,编译时基本没有依赖项问题,基本按照官方文档的步骤来,略作修改.使用的环境是Ubuntu16.04+ROS Kinetic 1.先装好wstool.rosdep.ninja sudo apt-get install -y python-wstool python-rosdep ninja-build 2.建工作空间 mkdir catkin_ws cd catkin_ws 用wstool初始化一下 wstool in

0.安装所有依赖项 sudo apt-get install -y google-mock libboost-all-dev  libeigen3-dev libgflags-dev libgoogle-glog-dev liblua5.2-dev libprotobuf-dev  libsuitesparse-dev libwebp-dev ninja-build protobuf-compiler python-sphinx  ros-indigo-tf2-eigen libatlas-ba

首先要正确安装 ROS ,然后第12步应注意,proto的版本是个关键容易出错.   1.添加ROS源http:/packages.ros.org/ros/ubuntu xenial main   (自己搜一下怎么添加)sudo apt-get update     更新源.2.Setup your sources.listsudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main"

目录: 1.运行多线激光雷达: 2.运行IMU: 3.录制rosbag包: 4.配置cartographer: 5.查看地图: 1.运行多线激光雷达: 主要是测试雷达是否正在运行,确认雷达点云topic类型是否一致,确认雷达frame id(可统一修改为laser_link). 2.运行IMU: 主要时测试IMU是否正常运行,可以通过rostopic list.rostopic info /imu.rosmsg info /sensor_msgs/Imu进行确认,同时确认IMU的frame id

在Google开源SLAM软件cartographer中,相对<SLAM for dummies>使用了更为复杂.性能更好的Scan匹配与UKF算法,这里简单介绍下cartographer中使用的UKF算法. (一)滤波器参数设定 constexpr static FloatType kAlpha = 1e-3; constexpr static FloatType kKappa = 0.; constexpr static FloatType kBeta = 2.; constexpr st

Bags are typically created by a tool like rosbag They store the serialized message data in a file as it is received http://pr.willowgarage.com/ 这里可以下载bag 使用bag文件作为静态输入的时候,要考虑bag和当前电脑的时间不一致的问题 参考了这篇博客关于时间问题的设置 http://blog.csdn.net/akunainiannian/artic

使用MATLAB实现图像的识别,这是MATLAB官网上面的例子,学习一下. http://cn.mathworks.com/help/vision/examples/image-category-classification-using-bag-of-features.html 这个算法叫做a bag of features approach for image category classification,用于识别小图片里面的是小狗.小猫.还是火车.船等. 首先要下载原材料,用于训练 % L

例1: 分词(返回以逗号隔开每一个词带上引號的词组.gap=",",quotes="'"或quotes='"') 单引號 <bag id=pPage act=2words name=words gap="," quotes="'">我喜欢黄色高领T恤衫</bag> 输出分词结果 <p><b>结果词组: </b>@{pPage:words}</p>