ROS_Kinetic_14 ROS工具roswtf的基本使用方法等

本文介绍ROS工具roswtf的基本使用方法,包括安装、检查及错误报告等内容,并提供了进一步学习ROS及其相关组件如rviz、tf和urdf等资源链接。

ROS_Kinetic_14 ROS工具roswtf的基本使用方法

官网教程:http://wiki.ros.org/cn/ROS/Tutorials/Getting%20started%20with%20roswtf

安装检查

~$ roscore

~$ roswtf

这时,会有警告。

WARNING The following node subscriptions are unconnected:
 * /rosout:
   * /rosout

运行时检查

在终端启动一个node,成功运行后,就没有警告等了。

~$ roswtf
Loaded plugin tf.tfwtf
No package or stack in context
================================================================================
Static checks summary:

No errors or warnings
================================================================================
Beginning tests of your ROS graph. These may take awhile...
analyzing graph...
... done analyzing graph
running graph rules...
... done running graph rules

Online checks summary:

No errors or warnings


还有错误报告等。

探索ROS维基

非常重要,介绍了ROS维基(wiki.ros.org)的组织结构以及使用方法。同时讲解了如何才能从ROS维基中找到你需要的信息。

http://wiki.ros.org/cn/ROS/Tutorials/NavigatingTheWiki

接下来做什么

这里将讨论获取更多知识的途径,以帮助你更好地使用ROS搭建真实或虚拟机器人。

http://wiki.ros.org/cn/ROS/Tutorials/WhereNext

rviz

http://wiki.ros.org/rviz

http://wiki.ros.org/rviz/UserGuide

tf

http://wiki.ros.org/tf

urdf

http://wiki.ros.org/urdf/Tutorials

http://wiki.ros.org/urdf

actionlib

http://wiki.ros.org/actionlib

navigation

http://wiki.ros.org/navigation

moveit!

http://moveit.ros.org/


-End-

### ROS Kinetic Calibration Tutorial and Resources For users interested in calibrating sensors or other components within the ROS Kinetic environment, several tutorials and resources are available. The `pluginlib` package provides an abstract framework for creating and using plugins which might be useful when developing custom calibration nodes[^1]. However, specific to calibration tasks, one of the most comprehensive guides comes from the official ROS wiki documentation. The Camera Calibration tool is part of the image_pipeline suite and allows performing camera intrinsic parameter estimation through a graphical user interface. This process involves capturing images containing a known pattern such as a chessboard grid placed at different orientations relative to the camera lens. After collecting enough samples, running the calibration node will compute focal length, principal point position, distortion coefficients among others parameters necessary for undistorting captured frames during operation. Another important aspect covered by these materials includes extrinsic parameters determination between multiple cameras mounted on robots like TurtleBot where accurate alignment ensures better performance especially while navigating environments based upon visual SLAM algorithms. Instructions provided explain not only theoretical concepts behind each step involved but also practical considerations regarding setup preparation before starting actual measurements. Moreover, integrating self-created maps alongside simulation platforms enhances testing capabilities without requiring physical hardware availability all times thus facilitating development cycles significantly according to explanations found elsewhere concerning Stage integration techniques specifically tailored towards mobile bases equipped with laser scanners capable of generating occupancy grids used later inside Gazebo worlds after proper adjustments made via configuration files following guidelines outlined thereupon too[^3]. Lastly, expanding workspaces beyond base installations enables incorporating specialized libraries supporting advanced functionalities required throughout various stages ranging from data acquisition up until post-processing analysis phases thanks largely due contributions coming directly out-of-the-box once extra dependencies get added properly following instructions laid down hereunder about managing releases efficiently so projects benefit fully from community efforts put forth collectively over time ensuring compatibility across diverse setups encountered regularly nowadays within research labs around globe alike[^5]. ```bash roslaunch camera_calibration cameracalibrator.launch \ image:=<your_image_topic> \ camera_name:=<your_camera_name> \ calib_url:=<path_to_your_calib_file> ```
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