*
* This example explains how to use the hand eye calibration for the case where
* the camera is stationary with respect to the robot and the calibration
* object is attached to the robot arm.
*這個示例展示了如何使用手眼標定，這種情形用于相機與機械手基礎坐標系位置固定且標定板固定在相機的末端軸上。
* In this case, the goal of the hand eye calibration
* is to determine two unknown poses:
*在這種情況下，手眼標定目標是確定一下兩個位置姿態。
* - the pose of the robot base in the coordinate system
* of the camera (BaseInCamPose).
*基于相機坐標系的機械手基礎坐標系姿態
* - the pose of the calibration object in the coordinate system of the
* tool (CalObjInToolPose)
*基于相機末端（工具）坐標系的標定板姿態
* Theoretically, as input the method needs at least 3 poses of the
* calibration object in the camera coordinate system and the corresponding
* poses of the robot tool in the coordinate system of the
* robot base. However it is recommended to use at least 10 Poses.
*理論上至少需要三個基于相機坐標系系統下標定物的姿態和基于機器人坐標系機器人末端工作坐標系的姿態。
*但建議至少使用10個姿態。
* The poses of the calibration object are obtained from images of the
* calibration object recorded with the stationary camera.
*標定板的姿態是從靜止相機拍攝的標定板圖像內獲得的。
* The calibration object is moved by the robot with respect to the camera.
*標定板相對于相機由機器人移動。
* To obtain good calibration results, it its essential to position
* the calibration object with respect to the camera so that the object appears
* tilted in the image.
*為了獲得良好的標定效果，標定物相對于相機其圖像要傾斜（旋轉）一些。
* 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.
*在手眼標定后，提取計算出的變換矩陣用于計算在相機坐標系系統中計算標定對象的姿態。
dev_update_off ()
* Directories with calibration images and data files
*以下是圖像和數據文件
ImageNameStart := '3d_machine_vision/handeye/stationarycam_calib3cm_'
DataNameStart := 'handeye/stationarycam_'
NumImages := 17
* Read image
read_image (Image, ImageNameStart + '00')
get_image_size (Image, Width, Height)
* Open window 打開窗口
dev_close_window ()
dev_open_window (0, 0, Width, Height, 'black', WindowHandle)
dev_set_line_width (2)
dev_set_draw ('margin')
dev_display (Image)
* Set font 設置字體
set_display_font (WindowHandle, 14, 'mono', 'true', 'false')
* Load the calibration plate description file.
* Make sure that the file is in the current directory,
* the HALCONROOT/calib directory, or use an absolut path
*加載標定板說明文件，確保文件在正確的目錄內或使用絕對路徑
CalTabFile := 'caltab_30mm.descr'
* Read the initial values for the internal camera parameters
*讀取相機的內參
read_cam_par (DataNameStart + 'start_campar.dat', StartCamParam)
* Create the calibration model for the hand eye calibration
*創建一個標定模型用于手眼標定
create_calib_data ('hand_eye_stationary_cam', 1, 1, CalibDataID)
*給標定模板設置相機參數 面陣相機
set_calib_data_cam_param (CalibDataID, 0, 'area_scan_division', StartCamParam)
*給標定模板設置標定板文數據
set_calib_data_calib_object (CalibDataID, 0, CalTabFile)
*設置標定數據
*設置手眼校準過程中使用的優化方法。如果設置了dataValue='linear'，則使用線性方法進行手眼校準。
*如果設置了dataValue='非線性'，則將使用非線性方法進行手眼校準（有關詳細信息，請參見校準手眼）。
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 ()
* Start the loop over the calibration images 開始循環標定圖像
for I := 0 to NumImages - 1 by 1
read_image (Image, ImageNameStart + I$'02d')
* Search for the calibration plate, extract the marks and the
* pose of it, and store the results in the calibration data model of the
* hand-eye calibration
*搜索標定板，提取標記和位置，并將結果存儲在手眼標定的數據模板中
find_calib_object (Image, CalibDataID, 0, 0, I, [], [])
get_calib_data_observ_contours (Caltab, CalibDataID, 'caltab', 0, 0, I)
* get_calib_data_observ_contours (Caltab, CalibDataID, 'marks', 0, 0, I)
get_calib_data_observ_points (CalibDataID, 0, 0, I, RCoord, CCoord, Index, CalObjInCamPose)
* Visualize the extracted calibration marks and the estimated pose (coordinate system)
*顯示提取到的標定mark點和估算姿態
dev_set_color ('green')
dev_display (Image)
dev_display (Caltab)
dev_set_color ('yellow')
disp_cross (WindowHandle, RCoord, CCoord, 6, 0)
dev_set_colored (3)
disp_3d_coord_system (WindowHandle, StartCamParam, CalObjInCamPose, 0.01)
* Read pose of tool in robot base coordinates (ToolInBasePose)
*在機械手基礎坐標系中讀取末端工具坐標系的姿態
read_pose (DataNameStart + 'robot_pose_' + I$'02d' + '.dat', ToolInBasePose)
* Set the pose tool in robot base coordinates in the calibration data model
*給標定數據模板設置基于機械手基礎坐標系下的工具姿態
set_calib_data (CalibDataID, 'tool', I, 'tool_in_base_pose', ToolInBasePose)
* Uncomment to inspect visualization
* disp_message (WindowHandle, 'Extracting data from calibration image ' + (I + 1) + ' of ' + NumImages, 'window', -1, -1, '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 hand-eye calibration 進行手眼標定
* Internally before performing the hand-eye calibration the cameras are calibrated
* and the calibrated poses of the calibration object in the camera are used.
*在進行手眼校準之前，對相機進行內部校準，并使用相機中校準對象的校準姿態。
dev_display (Image)
disp_message (WindowHandle, 'Performing the hand-eye calibration', 'window', 12, 12, 'black', 'true')
*進行手眼校準之前，得到優化的平均殘差
calibrate_hand_eye (CalibDataID, Errors)
* Query the camera parameters and the poses 查詢相機參數和姿勢
get_calib_data (CalibDataID, 'camera', 0, 'params', CamParam)
* Get poses computed by the hand eye calibration 通過手眼標定計算出姿勢
get_calib_data (CalibDataID, 'camera', 0, 'base_in_cam_pose', BaseInCamPose)
get_calib_data (CalibDataID, 'calib_obj', 0, 'obj_in_tool_pose', ObjInToolPose)
dev_get_preferences ('suppress_handled_exceptions_dlg', PreferenceValue)
dev_set_preferences ('suppress_handled_exceptions_dlg', 'true')
try
* Store the camera parameters to file 將相機參數存儲到文件
write_cam_par (CamParam, DataNameStart + 'final_campar.dat')
* Save the hand eye calibration results to file 將手眼標定結果保存到文件
write_pose (BaseInCamPose, DataNameStart + 'final_pose_cam_base.dat')
write_pose (ObjInToolPose, DataNameStart + 'final_pose_tool_calplate.dat')
catch (Exception)
* Do nothing
endtry
dev_set_preferences ('suppress_handled_exceptions_dlg', PreferenceValue)
* Display calibration errors of the hand-eye calibration
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
*對于給定的相機，獲取相應的姿態指數和標定對象指數。
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.
*通過標定姿態和工具基本姿態計算相機坐標系中校準對象的姿態，并將其可視化。
for I := 0 to NumImages - 1 by 1
read_image (Image, ImageNameStart + I$'02d')
* 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.
*在校準中使用的機器人基礎坐標中獲取工具的姿態。
*該索引對應于觀測對象姿態的索引。
get_calib_data (CalibDataID, 'tool', PoseIds[I], 'tool_in_base_pose', ToolInBasePose)
dev_display (Image)
* Compute the pose of the calibration plate with respect to the camera and visualize it
* 計算校準板相對于攝像機的姿態并將其可視化
calc_calplate_pose_stationarycam (ObjInToolPose, BaseInCamPose, ToolInBasePose, CalObjInCamPose)
dev_set_colored (3)
disp_3d_coord_system (WindowHandle, CamParam, CalObjInCamPose, 0.01)
Message := 'Using the calibration results to display the'
Message[1] := '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
* BaseInCamPose can be used in robotic grasping applications.
* If the tool coordinate system is placed at the gripper
* and a object detected at ObjInCamPose shall be grasped,
* the pose of the detected object relative
* to the robot base coordinate system has to be computed.
pose_invert (BaseInCamPose, CamInBasePose)
pose_compose (CamInBasePose, CalObjInCamPose, ObjInBasePose)

轉載于:https://www.cnblogs.com/yangmengke2018/p/9743334.html

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