*
* This example explains how to use the hand eye calibration for the case where
* the camera is attached to the robot tool and the calibration object
* is stationary with respect to the robot.
*这个示例展示了如何使用手眼标定,针对相机固定在机械手末端且标定板相对于机械手基础坐标系静止的情形。
* The robot positions the camera with respect to the calibration plate.
*机械手相对与相机姿态反映在标定板上。
* In this case, the goal of the hand eye calibration is to determine two unknown poses:
*在这种情况下,手眼标定的目标是得到两个未知的姿态。
* - the pose of the robot base in the coordinate system
* of the calibration object (CalObjInBasePose).
*标定板相对机械手基础坐标系的姿态
* - the pose of the camera in the coordinate system of the
* tool center point (ToolInCamPose).
*机器手末端工具坐标系相对于相机的姿态
* Theoretically, as input the method needs at least 3 poses of the
* calibration object in the camera coordinate system.
* However, it is recommended to use at least 10 Poses.
* The corresponding poses of the robot tool in the robot base coordinate system
* (ToolInBasePose) changes for each calibration image,
* because it describes the pose of the robot moving the camera.
* The poses of the calibration object are obtained from images of the
* calibration object recorded with the camera attached to the robot.
* To obtain good calibration results, it its essential to position
* the camera with respect to the calibration object so that the object appears
* tilted in the image.
* After the hand eye calibration, the computed transformations are
* extracted and used to compute the pose of the calibration object in the
* camera coordinate system.
dev_update_off ()
* Directories with calibration images and data files
ImageNameStart := '3d_machine_vision/handeye/movingcam_calib3cm_'
DataNameStart := 'handeye/movingcam_'
NumImages := 14
read_image (Image, ImageNameStart + '00')
dev_close_window ()
get_image_size (Image, Width, Height)
dev_open_window (0, 0, Width, Height, 'black', WindowHandle)
dev_set_line_width (2)
dev_set_draw ('margin')
dev_display (Image)
set_display_font (WindowHandle, 14, 'mono', 'true', 'false')
* Load the calibration plate description file.
*加载标定板描述文件
* Make sure that the file is in the current directory or
* in HALCONROOT/calib, or use an absolute path.
*确保文件在正确的路径或使用相对路径
CalTabFile := 'caltab_30mm.descr'
* Read the initial values for the internal camera parameters
*读取相机的内参
read_cam_par (DataNameStart + 'start_campar.dat', StartCamParam)
* Create the calibration model for the hand eye calibration
* where the calibration object is observed with a camera
*创建一个手眼标定模板,标定板在相机视野内
create_calib_data ('hand_eye_moving_cam', 1, 1, CalibDataID)
* Set the camera type used
*设置相机内参
set_calib_data_cam_param (CalibDataID, 0, 'area_scan_division', StartCamParam)
* Set the calibration object
*设置标定板参数
set_calib_data_calib_object (CalibDataID, 0, CalTabFile)
* Start the loop over the calibration images
* Set the opitmization method to be used
set_calib_data (CalibDataID, 'model', 'general', 'optimization_method', 'nonlinear')
disp_message (WindowHandle, 'The calibration data model was created', 'window', 12, 12, 'black', 'true')
disp_continue_message (WindowHandle, 'black', 'true')
stop ()
for I := 0 to NumImages - 1 by 1
read_image (Image, ImageNameStart + I$'02d')
* Search for the calibration plate, extract the marks and the
* pose of it, and store the results in the calibration data
* The poses are stored in the calibration data model for use by
* the hand eye calibration and do not have to be set explicitly
find_calib_object (Image, CalibDataID, 0, 0, I, [], [])
get_calib_data_observ_contours (Caltab, CalibDataID, 'caltab', 0, 0, I)
get_calib_data_observ_points (CalibDataID, 0, 0, I, RCoord, CCoord, Index, PoseForCalibrationPlate)
* Visualize the extracted calibration marks and the estimated pose (coordinate system)
dev_set_color ('green')
dev_display (Image)
dev_display (Caltab)
dev_set_color ('yellow')
disp_cross (WindowHandle, RCoord, CCoord, 6, 0)
dev_set_colored (3)
disp_3d_coord_system (WindowHandle, StartCamParam, PoseForCalibrationPlate, 0.01)
* Read pose of tool in robot base coordinates (ToolInBasePose)
*读机械手基础坐标系下的末端工具的姿态,每张图只要机械手末端相对标定板有XYZ方向的平移或旋转,此姿态就会不一样。
read_pose (DataNameStart + 'robot_pose_' + I$'02d' + '.dat', ToolInBasePose)
* Set the pose tool in robot base coordinates in the calibration data model
set_calib_data (CalibDataID, 'tool', I, 'tool_in_base_pose', ToolInBasePose)
* Uncomment for inspection of visualization
* disp_message (WindowHandle, 'Extracting data from calibration image ' + (I + 1) + ' of ' + NumImages, 'window', 12, 12, 'black', 'true')
* disp_continue_message (WindowHandle, 'black', 'true')
* stop ()
endfor
disp_message (WindowHandle, 'All relevant data has been set in the calibration data model', 'window', 12, 12, 'black', 'true')
disp_continue_message (WindowHandle, 'black', 'true')
stop ()
* Perform the hand eye calibration and store the results to file
* The calibration of the cameras is done internally prior
* to the hand eye calibration
dev_display (Image)
disp_message (WindowHandle, 'Performing the hand-eye calibration', 'window', 12, 12, 'black', 'true')
calibrate_hand_eye (CalibDataID, Errors)
* Query the camera parameters and the poses
get_calib_data (CalibDataID, 'camera', 0, 'params', CamParam)
* Get poses computed by the hand eye calibration
*tool_in_cam_pose:在相机坐标系下工具坐标系的关系
get_calib_data (CalibDataID, 'camera', 0, 'tool_in_cam_pose', ToolInCamPose)
*obj_in_base_pose:在机械手基础坐标系下标定板的姿态
get_calib_data (CalibDataID, 'calib_obj', 0, 'obj_in_base_pose', CalObjInBasePose)
dev_get_preferences ('suppress_handled_exceptions_dlg', PreferenceValue)
dev_set_preferences ('suppress_handled_exceptions_dlg', 'true')
try
* Handle situation where user does not have the permission
* to write in the current directory.
*
* Store the camera parameters to file
*保存一个相机的内参
write_cam_par (CamParam, DataNameStart + 'final_campar.dat')
* Save the hand eye calibration results to file
*保存工具坐标系(机械手末端)相对于相机的姿态参数
write_pose (ToolInCamPose, DataNameStart + 'final_pose_cam_tool.dat')
*保存标定板相对于机械手基础坐标系的姿态参数
write_pose (CalObjInBasePose, DataNameStart + 'final_pose_base_calplate.dat')
catch (Exception)
* do nothing
endtry
dev_set_preferences ('suppress_handled_exceptions_dlg', PreferenceValue)
dev_display (Image)
* Display calibration errors
Message := 'Quality of the results: root mean square maximum'
Message[1] := 'Translation part in meter: ' + Errors[0]$'6.4f' + ' ' + Errors[2]$'6.4f'
Message[2] := 'Rotation part in degree: ' + Errors[1]$'6.4f' + ' ' + Errors[3]$'6.4f'
disp_message (WindowHandle, Message, 'window', 12, 12, 'black', 'true')
disp_continue_message (WindowHandle, 'black', 'true')
stop ()
* For the given camera, get the corresponding pose indices and calibration object indices
query_calib_data_observ_indices (CalibDataID, 'camera', 0, CalibObjIdx, PoseIds)
* Compute the pose of the calibration object in the camera coordinate
* system via calibrated poses and the ToolInBasePose and visualize it.
for I := 0 to NumImages - 1 by 1
read_image (Image, ImageNameStart + I$'02d')
dev_display (Image)
* Obtain the pose of the tool in robot base coordinates used in the calibration.
* The index corresponds to the index of the pose of the observation object.
get_calib_data (CalibDataID, 'tool', PoseIds[I], 'tool_in_base_pose', ToolInBasePose)
* Compute the pose of the calibration object relative to the camera
calc_calplate_pose_movingcam (CalObjInBasePose, ToolInCamPose, ToolInBasePose, CalObjInCamPose)
* Display the coordinate system
dev_set_colored (3)
disp_3d_coord_system (WindowHandle, CamParam, CalObjInCamPose, 0.01)
Message := 'Using the calibration results to display '
Message[1] := 'the coordinate system in image ' + (I + 1) + ' of ' + NumImages
disp_message (WindowHandle, Message, 'window', 12, 12, 'black', 'true')
if (I < NumImages - 1)
disp_continue_message (WindowHandle, 'black', 'true')
stop ()
endif
endfor
* Clear the data model
clear_calib_data (CalibDataID)
*
* After the hand-eye calibration the computed pose
* ToolInCamPose can be used in robotic grasping applications.
* If the tool coordinate system is placed at the gripper
* and a detected object ObjInCamPose shall be grasped
* (here the calibration object),
* the pose of the detected object relative
* to the robot base coordinate system has to be computed.
*姿态反转
pose_invert (ToolInCamPose, CamInToolPose)
*由两个已知姿态得到第三个姿态,相当于两个分数乘法,其中一个分子与另一个分母相等,相约的情况
pose_compose (ToolInBasePose, CamInToolPose, CamInBasePose)
pose_compose (CamInBasePose, CalObjInCamPose, ObjInBasePose)

手眼标定之相机随动eye-in-hand 示例:handeye_movingcam_calibration的更多相关文章

  1. 手眼标定eye-to-hand 示例:handeye_stationarycam_calibration

    * * This example explains how to use the hand eye calibration for the case where* the camera is stat ...

  2. halcon 手眼标定的坐标转换原理讲解

    原文链接:https://blog.csdn.net/opencv_learner/article/details/82113323 一直以来,对于手眼标定所涉及到的坐标系及坐标系之间的转换关系都没能 ...

  3. ROS标定IDS相机

    参考 ROS 相机标定http://blog.csdn.net/ArtistA/article/details/51125560 ROS里的标定程序只要使用了OPNCV的标定程序: opencv 相机 ...

  4. 相机标定:PNP基于单应面解决多点透视问题

              利用二维视野内的图像,求出三维图像在场景中的位姿,这是一个三维透视投影的反向求解问题.常用方法是PNP方法,需要已知三维点集的原始模型. 本文做了大量修改,如有不适,请移步原文:  ...

  5. 相机标定简介与MatLab相机标定工具箱的使用(未涉及原理公式推导)

    相机标定 一.相机标定的目的 确定空间物体表面某点的三维几何位置与其在图像中对应点之间的相互关系,建立摄像机成像的几何模型,这些几何模型参数就是摄像机参数. 二.通用摄像机模型 世界坐标系.摄像机坐标 ...

  6. 相机标定:kalibr标定工具箱使用总结

    1 多相机标定 1.1采集图像和IMU 1.2制作Bag包 1)组织文件结构 ~/kalibr_workspace/test/stereo_calib bagsrc cam0 (1+time(0))* ...

  7. MATLAB二维相机标定的解决方案 calibration

    第一步,在命令行下面输入cameraCalibrator,启动MATLAB相机标定.相机矫正界面 cameraCalibrator 第二步:拍照.如果你是做相机标定,你应该知道,你需要一些calibr ...

  8. 直接线性变换解法(DLT)用于标定相机

    直接线性变换法是建立像点坐标和相应物点物方空间坐标之间直接的线性关系的算法.特点:不需要内外方位元素:适合于非量测相机:满足中.低精度的测量任务:可以标定单个相机. 1 各坐标系之间的关系推导直接线性 ...

  9. 相机标定过程(opencv) + matlab参数导入opencv + matlab标定和矫正

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 辛苦原创所得,转载请注明出处 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ...

随机推荐

  1. Hadoop 2.x 版本的单机模式安装

    Hadoop 2.x 版本比起之前的版本在Hadoop和MapReduce上做了许多变化,主要的变化之一,是JobTracker被ResourceManager和ApplicationManager所 ...

  2. Django的安装和启动以及第一个工程的建立

    ---恢复内容开始--- 前提:已经安装了python和Anaconda (windows系统) 在Anaconda安装好之后,其文件夹下有一个叫做Anaconda Prompt的工具,类似windo ...

  3. 新安装mysql,如何提升mysql安全性

    1.修改mysql默认端口,将3306修改为其他端口. 2.设定足够复杂的密码策略并指定访问IP(在user表中可以指定用户可访问的访问IP地址). 3.设定IP访问白名单. 4.设定root用户只能 ...

  4. soapui的简单使用

    工具下载地址:https://www.soapui.org/downloads/soapui.html 名词解释 https://www.cnblogs.com/fcfblog/p/5830205.h ...

  5. 计算机网络学习-20180901-TCP/IP协议的五大分层

    摘要:TCP/IP协议的五大分层:应用层.传输层.网络层.数据链路层.物理层(附带一个第0层物理媒介):互联网的核心,即为ip协议. TCP/IP协议的五大分层 5-应用层:获取主机中进程所产生的数据 ...

  6. JavaScript最后的课程笔记

    一.快捷位置和尺寸 DOM已经提供给我们计算后的样式,但是还觉得不方便,所以DOM又提供给我们一些API: ele.offsetLeft ele.offsetTop ele.offsetWidth e ...

  7. SpringCloud注解和配置以及pom依赖说明

    在本文中说明了pom依赖可以支持什么功能,以及支持什么注解,引入该依赖可以在application.properties中添加什么配置. 1.SpringCloud 的pom依赖 序号 pom依赖 说 ...

  8. # 20175311 2018-2019-2 《Java程序设计》第2周学习总结

    ## 教材学习内容总结 第二周我对如何运行java程序已经比较熟悉了,第二周更多的是注重程序内部的原理了. ## 教材学习中的问题和解决过程 - 问题1:看书时看到的一个例子,不是很懂它是怎么得出结果 ...

  9. xamarin android 开发

    开始环境vs2017 直接创建android 项目,左边是android studio 的项目目录  右边是vs创建的android 项目目录 结构基本相同,有res对应的Resources文件 加载 ...

  10. spring boot profiles 实现多环境下配置切换 docker版

    1,前言 开发环境总需要调试,docker直接部署不需要调试,环境配置不一样,这里的目的只是,在docker文件环境与开发环境使用不同的配置文件,项目结构如下 2,设置项目配置文件 默认配置文件 ap ...