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mycobot_280/mycobot_280/camera_calibration/EyesInHand_matrix.json
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[[-0.996091560743614, 0.02359232376557422, -0.0851175943897141, -22.980358398950056], [-0.04045681823508953, -0.9785014715102557, 0.20223282649104501, -7.126480805661541], [-0.07851654904314409, 0.20488599881789024, 0.9756315283009006, 30.736245192702807], [0.0, 0.0, 0.0, 1.0]] |
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mycobot_280/mycobot_280/camera_calibration/camera_calibration.py
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import cv2 | ||
from uvc_camera import UVCCamera | ||
import stag | ||
import numpy as np | ||
import json | ||
import time | ||
from scipy.linalg import svd | ||
from pymycobot import * | ||
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mc = MyCobot("/dev/ttyUSB0") # 设置端口 | ||
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np.set_printoptions(suppress=True, formatter={'float_kind': '{:.2f}'.format}) | ||
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class camera_detect: | ||
#Camera parameter initialize | ||
def __init__(self, camera_id, marker_size, mtx, dist): | ||
self.camera_id = camera_id | ||
self.mtx = mtx | ||
self.dist = dist | ||
self.marker_size = marker_size | ||
self.camera = UVCCamera(self.camera_id, self.mtx, self.dist) | ||
self.camera_open() | ||
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self.origin_mycbot_horizontal = [0,60,-60,0,0,0] | ||
self.origin_mycbot_level = [0, 5, -104, 14, 0, 90] | ||
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# Initialize EyesInHand_matrix to None or load from a document if available | ||
self.EyesInHand_matrix = None | ||
self.load_matrix() | ||
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def save_matrix(self, filename="EyesInHand_matrix.json"): | ||
# Save the EyesInHand_matrix to a JSON file | ||
if self.EyesInHand_matrix is not None: | ||
with open(filename, 'w') as f: | ||
json.dump(self.EyesInHand_matrix.tolist(), f) | ||
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def load_matrix(self, filename="EyesInHand_matrix.json"): | ||
# Load the EyesInHand_matrix from a JSON file, if it exists | ||
try: | ||
with open(filename, 'r') as f: | ||
self.EyesInHand_matrix = np.array(json.load(f)) | ||
except FileNotFoundError: | ||
print("Matrix file not found. EyesInHand_matrix will be initialized later.") | ||
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def wait(self): | ||
time.sleep(0.5) | ||
while(mc.is_moving() == 1): | ||
time.sleep(0.2) | ||
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def camera_open(self): | ||
self.camera.capture() # 打开摄像头 | ||
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# 获取物体坐标(相机系) | ||
def calc_markers_base_position(self, corners, ids): | ||
if len(corners) == 0: | ||
return [] | ||
rvecs, tvecs = solve_marker_pnp(corners, self.marker_size, self.mtx, self.dist) # 通过二维码角点获取物体旋转向量和平移向量 | ||
for i, tvec, rvec in zip(ids, tvecs, rvecs): | ||
tvec = tvec.squeeze().tolist() | ||
rvec = rvec.squeeze().tolist() | ||
rotvector = np.array([[rvec[0], rvec[1], rvec[2]]]) | ||
Rotation = cv2.Rodrigues(rotvector)[0] # 将旋转向量转为旋转矩阵 | ||
Euler = self.CvtRotationMatrixToEulerAngle(Rotation) # 将旋转矩阵转为欧拉角 | ||
target_coords = np.array([tvec[0], tvec[1], tvec[2], Euler[0], Euler[1], Euler[2]]) # 物体坐标(相机系) | ||
return target_coords | ||
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def eyes_in_hand_calculate(self, pose, tbe1, Mc1, tbe2, Mc2, tbe3, Mc3, Mr): | ||
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tbe1, Mc1, tbe2, Mc2, tbe3, Mc3, Mr = map(np.array, [tbe1, Mc1, tbe2, Mc2, tbe3, Mc3, Mr]) | ||
# Convert pose from degrees to radians | ||
euler = np.array(pose) * np.pi / 180 | ||
Rbe = self.CvtEulerAngleToRotationMatrix(euler) | ||
print("Rbe", Rbe) | ||
Reb = Rbe.T | ||
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A = np.hstack([(Mc2 - Mc1).reshape(-1, 1), | ||
(Mc3 - Mc1).reshape(-1, 1), | ||
(Mc3 - Mc2).reshape(-1, 1)]) | ||
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b = Reb @ np.hstack([(tbe1 - tbe2).reshape(-1, 1), | ||
(tbe1 - tbe3).reshape(-1, 1), | ||
(tbe2 - tbe3).reshape(-1, 1)]) | ||
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print("A = ", A) | ||
print("B = ", b) | ||
U, S, Vt = svd(A @ b.T) | ||
Rce = Vt.T @ U.T | ||
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tce = Reb @ (Mr - (1/3)*(tbe1 + tbe2 + tbe3) - (1/3)*(Rbe @ Rce @ (Mc1 + Mc2 + Mc3))) | ||
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eyes_in_hand_matrix = np.vstack([np.hstack([Rce, tce.reshape(-1, 1)]), np.array([0, 0, 0, 1])]) | ||
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return eyes_in_hand_matrix | ||
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# 读取Camera坐标(单次) | ||
def stag_identify(self): | ||
self.camera.update_frame() # 刷新相机界面 | ||
frame = self.camera.color_frame() # 获取当前帧 | ||
(corners, ids, rejected_corners) = stag.detectMarkers(frame, 11) # 获取画面中二维码的角度和id | ||
# 绘制检测到的标记及其ID | ||
stag.drawDetectedMarkers(frame, corners, ids) | ||
# 绘制被拒绝的候选区域,颜色设为红色 | ||
stag.drawDetectedMarkers(frame, rejected_corners, border_color=(255, 0, 0)) | ||
marker_pos_pack = self.calc_markers_base_position(corners, ids) # 获取物的坐标(相机系) | ||
if(len(marker_pos_pack) == 0): | ||
marker_pos_pack = self.stag_identify() | ||
# print("Camera coords = ", marker_pos_pack) | ||
# cv2.imshow("rrrr", frame) | ||
# cv2.waitKey(1) | ||
return marker_pos_pack | ||
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def Eyes_in_hand_calibration(self, ml): | ||
ml.send_angles(self.origin_mycbot_level, 50) # 移动到观测点 | ||
self.wait() | ||
input("make sure camera can observe the stag, enter any key quit") | ||
coords = ml.get_coords() | ||
pose = coords[3:6] | ||
print(pose) | ||
# self.camera_open_loop() | ||
Mc1,tbe1 = self.reg_get(ml) | ||
ml.send_coord(1, coords[0] + 30, 30) | ||
self.wait() | ||
Mc2,tbe2 = self.reg_get(ml) | ||
ml.send_coord(1, coords[0] - 10, 30) | ||
self.wait() | ||
ml.send_coord(3, coords[2] + 20, 30) | ||
self.wait() | ||
Mc3,tbe3 = self.reg_get(ml) | ||
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input("Move the end of the robot arm to the calibration point, press any key to release servo") | ||
ml.release_all_servos() | ||
input("focus servo and get current coords") | ||
ml.power_on() | ||
time.sleep(1) | ||
coords = ml.get_coords() | ||
while len(coords) == 0: | ||
coords = ml.get_coords() | ||
Mr = coords[0:3] | ||
print(Mr) | ||
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self.EyesInHand_matrix = self.eyes_in_hand_calculate(pose, tbe1, Mc1, tbe2, Mc2, tbe3, Mc3, Mr) | ||
print("EyesInHand_matrix = ", self.EyesInHand_matrix) | ||
self.save_matrix() # Save the matrix to a file after calculating it | ||
print("save successe") | ||
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def reg_get(self, ml): | ||
for i in range(50): | ||
Mc_all = self.stag_identify() | ||
tbe_all = ml.get_coords() # 获取机械臂当前坐标 | ||
while (tbe_all is None): | ||
tbe_all = ml.get_coords() | ||
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tbe = tbe_all[0:3] | ||
Mc = Mc_all[0:3] | ||
print("tbe = ", tbe) | ||
print("Mc = ", Mc) | ||
return Mc,tbe | ||
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if __name__ == "__main__": | ||
if mc.is_power_on()==0: | ||
mc.power_on() | ||
camera_params = np.load("camera_params.npz") # 相机配置文件 | ||
mtx, dist = camera_params["mtx"], camera_params["dist"] | ||
m = camera_detect(0, 32, mtx, dist) | ||
tool_len = 20 | ||
mc.set_tool_reference([0, 0, tool_len, 0, 0, 0]) | ||
mc.set_end_type(1) | ||
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m.Eyes_in_hand_calibration(mc) #手眼标定 | ||
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import cv2 | ||
import numpy as np | ||
import time | ||
import typing | ||
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class UVCCamera: | ||
def __init__( | ||
self, | ||
cam_index=0, | ||
mtx=None, | ||
dist=None, | ||
capture_size: typing.Tuple[int, int] = (640, 480), | ||
): | ||
super().__init__() | ||
self.cam_index = cam_index | ||
self.mtx = mtx | ||
self.dist = dist | ||
self.curr_color_frame: typing.Union[np.ndarray, None] = None | ||
self.capture_size = capture_size | ||
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def capture(self): | ||
self.cap = cv2.VideoCapture(self.cam_index) #windows | ||
width, height = self.capture_size | ||
self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, width) | ||
self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height) | ||
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def update_frame(self) -> bool: | ||
ret, self.curr_color_frame = self.cap.read() | ||
return ret | ||
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def color_frame(self) -> typing.Union[np.ndarray, None]: | ||
return self.curr_color_frame | ||
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def release(self): | ||
self.cap.release() | ||
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if __name__ == "__main__": | ||
cam = UVCCamera(2) | ||
cam.capture() | ||
while True: | ||
if not cam.update_frame(): | ||
continue | ||
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frame = cam.color_frame() | ||
if frame is None: | ||
time.sleep(0.01) | ||
continue | ||
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print(frame.shape) | ||
window_name = "preview" | ||
cv2.imshow(window_name, frame) | ||
if cv2.waitKey(1) == ord("q"): | ||
break |
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1 @@ | ||
[[-0.996091560743614, 0.02359232376557422, -0.0851175943897141, -22.980358398950056], [-0.04045681823508953, -0.9785014715102557, 0.20223282649104501, -7.126480805661541], [-0.07851654904314409, 0.20488599881789024, 0.9756315283009006, 30.736245192702807], [0.0, 0.0, 0.0, 1.0]] |
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