Halcon—Realsense相机标定+手眼标定[通俗易懂]

Halcon—Realsense相机标定+手眼标定[通俗易懂]使用软件:Halcon18.05(默认安装好任一版halcon)使用设备:IntelRealsense435+AUBO机械臂完成功能:相机标定、eye-in-hand手眼标定1.准备标定板如果没有标定板:1.窗口–打开算子窗口–gen_caltab设置XNum,YNum—圆点个数,X和Y方向圆点个数圆点直径=MarkDist×DiameterRatio间距为MarkDist…

大家好,又见面了,我是你们的朋友全栈君。

使用软件:Halcon18.05(默认安装好任一版halcon)
使用设备:Intel Realsense 435+AUBO机械臂
完成功能:相机标定、eye-in-hand手眼标定

1.准备标定板

1.1如果没有标定板:

1.1.1窗口–打开算子窗口–gen_caltab
设置XNum,YNum—圆点个数,X和Y方向圆点个数
圆点直径=MarkDist × DiameterRatio
间距为MarkDist(单位为米)
caltab.descr是标定板描述文件
caltab.ps为标定板生成文件,没有ps用Adobe PDF打开就能看到如下图1-2所示的标定板,可以直接打印。
如果买了标定板直接用标定板的数据就行,但还是需要用这个生成一个标定板的描述文件,也就是caltab.descr
图1
点filename.write可以看到保存路径
标定板图1-2

1.1.2.点插入,运行,在刚刚的保存路径下找到生成的caltab.descr

1.2有标定板

按照已有标定板尺寸生成caltab.descr——标定板描述文件,之后操作与1.1.2相同

2.相机标定

助手–打开新的Calibration
在描述文件地方插入刚刚生成的caltab.descr
在这里插入图片描述
点击标定,如下图所示,如果有图片直接在这里点击加载调用已拍摄完成的图片,移除掉识别错误的图片
没有图片就先连接相机,之后先点击图像采集助手,再采集图片,实时采集能看到识别出点的图片时再点采集按钮。
在这里插入图片描述
在结果中摄像机参数需要记录下来,之后会用到,摄像机位姿需要点击“保存”保存成 .dat 格式的文件
在这里插入图片描述

3.手眼标定

标定板不动,移动机械臂,拍摄15+张图片,覆盖多个位姿,并记录每张图片拍摄时机械臂的位姿(包括X,Y,Z,RX,RY,RZ六个)
生成机械臂位姿dat文件,打开默认路径下的movingcam_robot_pose_xx.dat,直接修改
我的路径:
C:\Users\Public\Documents\MVTec\HALCON-18.05-Progress\examples\solution_guide\3d_vision\hand_eye

在这里插入图片描述
movingcam_robot_pose_xx.dat内容如下:
对照自己记录的机械臂位姿进行修改,一定要一一对应


# Used representation type:
f 2

# Rotation angles [deg] or Rodriguez-vector:
r 180.0 0.0 75.0

# Translational vector (x y z [m]):
t 0.569269 -0.152535 -0.160

修改ImageNameStart(图片存储位置)和CalTabFile(标定板描述文件位置)的位置

ImageNameStart := '3d_machine_vision/923-0/0000'

改成自己的标定板描述文件位置

CalTabFile := 'C:/Users/alw/Desktop/caltab.descr'

附上全部代码

* 
* 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. The robot positions the
* camera with respect to the calibration plate.
* In this case, the goal of the hand eye calibration is to determine two unknown poses:
* - the pose of the robot base in the coordinate system
*   of the calibration object (CalObjInBasePose).
* - the pose of the camera in the coordinate system of the
*   tool center point (ToolInCamPose).
* 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/923-0/0000'
DataNameStart := 'hand_eye/movingcam_'
NumImages := 14
read_image (Image, ImageNameStart + '01')
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')
ParamName := ['color_0','color_1','color_2','color_3','color_4','color_5','color_6','alpha_6']
ParamValue := ['red','green','blue','red','green','blue','white',0.7]
* Labels for the visualized 3D object models.
tuple_gen_const (7, '', Labels)
Labels[0] := 'Robot\'s Tool'
Labels[3] := 'Robot\'s Base'
Instructions[0] := 'Rotate: Left button'
Instructions[1] := 'Zoom:   Shift + left button'
Instructions[2] := 'Move:   Ctrl  + left button'
* Set size for 3D visualization in [m]
ArrowThickness := 0.005
ArrowLength := 0.05
gen_robot_tool_and_base_object_model_3d (ArrowThickness, ArrowLength, OM3DToolOrigin, OM3DBase)
* Load the calibration plate description file.
* Make sure that the file is in the current directory or
* in HALCONROOT/calib, or use an absolute path.
CalTabFile := 'C:/Users/alw/Desktop/caltab.descr'
* Read the initial values for the internal camera parameters
* 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
* Calibration 02: Code generated by Calibration 02

StartCamParam := ['area_scan_division',0.008,0,8.3e-006,8.3e-006,640,480,1280,960]

create_calib_data ('hand_eye_moving_cam', 1, 1, CalibDataID)
* Set the camera type used
set_calib_data_cam_param (CalibDataID, 0, [], StartCamParam)
* Set the calibration object
set_calib_data_calib_object (CalibDataID, 0, CalTabFile)
* Start the loop over the calibration images
* Set the optimization 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 ()

dev_open_window (0, Width + 10, Width, Height, 'black', WindowHandleR)
set_display_font (WindowHandleR, 14, 'mono', 'true', 'false')
for I := 1 to NumImages - 1 by 1
    dev_set_window (WindowHandle)
    dev_clear_window ()
    read_image (Image, ImageNameStart + I$'02d')
    dev_display (Image)
    * Search for the calibration plate, extract the marks and the
    * pose of it, and store the results in the calibration data
    * The poses are stored in the calibration data model for use by
    * the hand eye calibration and do not have to be set explicitly
    find_calib_object (Image, CalibDataID, 0, 0, I, [], [])
    get_calib_data_observ_contours (Caltab, CalibDataID, 'caltab', 0, 0, I)
    get_calib_data_observ_points (CalibDataID, 0, 0, I, RCoord, CCoord, Index, PoseForCalibrationPlate)
    * Visualize the extracted calibration marks and the estimated pose (coordinate system)
    dev_set_color ('green')
    dev_display (Image)
    dev_display (Caltab)
    dev_set_color ('yellow')
    disp_cross (WindowHandle, RCoord, CCoord, 6, 0)
    dev_set_colored (3)
    disp_3d_coord_system (WindowHandle, StartCamParam, PoseForCalibrationPlate, 0.01)
    disp_message (WindowHandle, 'Extracting data from calibration image ' + (I + 1) + ' of ' + NumImages, 'window', 12, 12, 'black', 'true')
    * Read pose of tool in robot base coordinates (ToolInBasePose)
    read_pose (DataNameStart + 'robot_pose_' + I$'02d' + '.dat', ToolInBasePose)
    if (I == 1)
        PoseIn := [-0.006,-0.296,12,178,2,270,0]
    else
        PoseIn := PoseOut
    endif
    rigid_trans_object_model_3d (OM3DToolOrigin, ToolInBasePose, OM3DTool)
    visualize_object_model_3d (WindowHandleR, [OM3DTool,OM3DBase], [], PoseIn, ParamName, ParamValue, 'Position of robot tool coordinate system in robot base coordinate system', Labels, Instructions, PoseOut)
    * Set the pose tool in robot base coordinates in the calibration data model
    set_calib_data (CalibDataID, 'tool', I, 'tool_in_base_pose', ToolInBasePose)
endfor
dev_set_window (WindowHandleR)
dev_close_window ()
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 ()
* Check the input poses for consistency
check_hand_eye_calibration_input_poses (CalibDataID, 0.05, 0.005, Warnings)
if (|Warnings| != 0)
    * There were problem detected in the input poses. Inspect Warnings and
    * remove erroneous poses with remove_calib_data and remove_calib_data_observ.
    dev_inspect_ctrl (Warnings)
    stop ()
endif
* 
* 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 error of the camera calibration
get_calib_data (CalibDataID, 'model', 'general', 'camera_calib_error', CamCalibError)
* Query the camera parameters and the poses
get_calib_data (CalibDataID, 'camera', 0, 'params', CamParam)
* Get poses computed by the hand eye calibration
get_calib_data (CalibDataID, 'camera', 0, 'tool_in_cam_pose', ToolInCamPose)
get_calib_data (CalibDataID, 'calib_obj', 0, 'obj_in_base_pose', CalObjInBasePose)
* Get the plane in base coordinate system pose by translating the
* CalObjInBasePose by the calibration object's thickness in the
* z-direction.
set_origin_pose (CalObjInBasePose, 0, 0, 0.005, PlaneInBasePose)
try
    * Handle situation where user does not have the permission
    * to write in the current directory.
    * 
    * Store the camera parameters to file
    write_cam_par (CamParam, DataNameStart + 'final_campar.dat')
    * Save the hand eye calibration results to file
    write_pose (ToolInCamPose, DataNameStart + 'final_pose_cam_tool.dat')
    write_pose (CalObjInBasePose, DataNameStart + 'final_pose_base_calplate.dat')
    write_pose (PlaneInBasePose, DataNameStart + 'final_pose_base_plane.dat')
catch (Exception)
    * do nothing
endtry
dev_display (Image)
* Display calibration errors
disp_results (WindowHandle, CamCalibError, Errors)
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.
* Set sizes for 3D visualization in [m]
CameraSize := 0.05
CameraConeLength := 0.3
get_calib_data (CalibDataID, 'calib_obj', 0, 'x', PX)
get_calib_data (CalibDataID, 'calib_obj', 0, 'y', PY)
get_calib_data (CalibDataID, 'calib_obj', 0, 'z', PZ)
gen_object_model_3d_from_points (PX, PY, PZ, OM3DObjectOrig)
rigid_trans_object_model_3d (OM3DObjectOrig, CalObjInBasePose, OM3DObject)
dev_open_window (0, Width + 10, Width, Height, 'black', WindowHandleR)
set_display_font (WindowHandleR, 14, 'mono', 'true', 'false')
ParamName := ['color_0','color_1','color_2','color_3','color_4','color_5','color_6','color_7','alpha_7','color_8','color_9','color_10','alpha_8','alpha_9','alpha_10','point_size']
ParamValue := ['red','red','green','blue','red','green','blue','white',0.7,'magenta','yellow','white',0.5,0.5,0.5,5]
* Labels for the visualized 3D object models.
tuple_gen_const (11, '', Labels)
Labels[0] := 'Calibration Object'
Labels[1] := 'Robot\'s Tool'
Labels[4] := 'Robot\'s Base'
Labels[8] := 'Camera'
for I := 1 to NumImages - 1 by 1
    dev_set_window (WindowHandle)
    dev_clear_window ()
    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.
    * set_calib_data (CalibDataID, 'tool', I, 'tool_in_base_pose', ToolInBasePose)
    get_calib_data (CalibDataID, 'tool', I, 'tool_in_base_pose', ToolInBasePose)    
*       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')
    gen_camera_and_tool_moving_cam_object_model_3d (ToolInCamPose, ToolInBasePose, CameraSize, CameraConeLength, OM3DToolOrigin, CamParam, OM3DCamera, OM3DTool)
    if (I == 1)
        PoseIn := [-0.006,-0.296,12,178,2,270,0]
    else
        PoseIn := PoseOut
    endif
    visualize_object_model_3d (WindowHandleR, [OM3DObject,OM3DTool,OM3DBase,OM3DCamera], [], PoseIn, ParamName, ParamValue, [], Labels, Instructions, PoseOut)
endfor
* Clear the data model
clear_calib_data (CalibDataID)
dev_set_window (WindowHandleR)
dev_close_window ()
* 
* After the hand-eye calibration the computed pose
* ToolInCamPose can be used in robotic grasping applications.
* To grasp an object with the robot, typically, its pose
* with respect to the camera is determined (which
* is simulated here by setting the object's pose to the
* pose of the calibration object)
ObjInCamPose := CalObjInCamPose
* 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.
pose_invert (ToolInCamPose, CamInToolPose)
pose_compose (ToolInBasePose, CamInToolPose, CamInBasePose)
pose_compose (CamInBasePose, ObjInCamPose, ObjInBasePose)

4.查看结果

最后,在窗口–打开变量控制窗口,查看最后的标定结果
在这里插入图片描述

版权声明:本文内容由互联网用户自发贡献,该文观点仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请联系我们举报,一经查实,本站将立刻删除。

发布者:全栈程序员-站长,转载请注明出处:https://javaforall.net/134205.html原文链接:https://javaforall.net

(1)
全栈程序员-站长的头像全栈程序员-站长


相关推荐

  • Hook技术【移动端&&PC端详解】「建议收藏」

    Hook技术【移动端&&PC端详解】「建议收藏」最近面试说到了这个hook技术,其实就是钩子函数,但是具体如何应用需要一探究竟,私下总结一下。文章目录移动端的hook技术应用1.whatisHook技术(移动端)2.Hook技术实现的步骤3.在移动开发中的应用:3.1使用hook技术实现免注册式跳转Windows端应用1.whatishook(钩子)2.Hook分类3.Hook工作原理Hook简介微软的MSDN中,…

    2022年5月26日
    53
  • opencv3编程入门_java基础与入门教程

    opencv3编程入门_java基础与入门教程——韦访 201810111、概述想学习图像处理,不管是机器学习也好,深度学习也好,不会点OpenCV好像有点说不过去吧?所以,现在开始OpenCV的学习。2、读写图片先从图片的读写开始,opencv读取图片的函数是imread,默认情况下,imread函数返回BGR格式的图像,可以用imwrite函数将数据写到本地。下面的代码会将JPG图片转成PNG。import…

    2022年10月3日
    2
  • mysql全文索引使用

    mysql全文索引使用一、前言      在以前的博客中小编介绍过mysql的执行流程,索引优化等。正好前一段时间项目有一个新的需求,就重新调研了一下mysql的全文索引,并对mysql的全文索引进行了压测,看看性能怎么样。以判断是否使用。——可想而知,性能不是很好。下面小编就向大家再说说mysql的全文检索。   &nbs…

    2022年6月21日
    29
  • strcmp函数的使用_用c语言实现strcmp

    strcmp函数的使用_用c语言实现strcmpAction(){/**********************************Author:旺仔*object:strcmp*date:2015-12-09*fuc:我输

    2022年8月3日
    4
  • mysql如何批量添加数据_mysql如何批量insert数据

    mysql如何批量添加数据_mysql如何批量insert数据mysql批量insert数据的方法:1、循环插入;2、减少连接资源,拼接一条sql;3、使用存储过程;4、使用【MYSQLLOCAL_INFILE】。本教程操作环境:windows7系统、mysql8.0.22版,该方法适用于所有品牌电脑。mysql批量insert数据的方法:方法一:循环插入这个也是最普通的方式,如果数据量不是很大,可以使用,但是每次都要消耗连接数据库的资源。大致思维如下(我…

    2025年8月12日
    2
  • SQL语句查询语句完整语法

    SQL语句查询语句完整语法数据库是 mysql 使用的数据库表名称是 my student 表的完整数据信息是 完整语法是 Select select 选项 字段列表 字段别名 from 数据源 where 字句 groupby 子句 having 子句 orderby 子句 limit 子句 select 选项 Select 选项包含 ALL 所有 默认 dis

    2025年10月6日
    3

发表回复

您的邮箱地址不会被公开。 必填项已用 * 标注

关注全栈程序员社区公众号