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Set the z-axis rotation to zero,

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Apply low-pass filter to screw quaternion
	modified:   src/maintain/scripts/test.py
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wxchen
2023-05-08 19:36:52 +08:00
parent ec7bca8c43
commit c2f252dce6
1 changed files with 97 additions and 16 deletions
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113
src/maintain/scripts/test.py
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@@ -5,8 +5,9 @@ import cv2 as cv
from matplotlib import pyplot as plt
import rospy
import tf2_ros
import tf
from sensor_msgs.msg import Image , CameraInfo
from geometry_msgs.msg import PoseStamped, TransformStamped
from geometry_msgs.msg import PoseStamped, TransformStamped, Quaternion
import message_filters
from cv_bridge import CvBridge, CvBridgeError
import rospkg
@@ -17,6 +18,73 @@ from rostopic import get_topic_type
from detection_msgs.msg import BoundingBox, BoundingBoxes
bridge = CvBridge()
annulus_width = 10
def calculate_image_edge_plane_normal(depth_roi):
# Get the shape of the depth_roi
height, width = depth_roi.shape
# Get the edges of the ROI
left_edge = [(0, y) for y in range(height)]
right_edge = [(width-1, y) for y in range(height)]
top_edge = [(x, 0) for x in range(width)]
bottom_edge = [(x, height-1) for x in range(width)]
edges = left_edge + right_edge + top_edge + bottom_edge
# Create a 2D grid of X and Y coordinates
X, Y = np.meshgrid(np.arange(width), np.arange(height))
# Reshape the X, Y, and depth_roi arrays into one-dimensional arrays
X = X.reshape(-1)
Y = Y.reshape(-1)
Z = depth_roi.reshape(-1)
# Stack the X, Y, and depth_roi arrays vertically to create a 3D array of points in the form of [X, Y, Z]
points = np.vstack([X, Y, Z]).T
# Compute the mean depth value of the edges
edge_depths = []
for edge_point in edges:
edge_depths.append(depth_roi[edge_point[1], edge_point[0]])
mean_depth = np.mean(edge_depths)
# Create a mask to extract the points on the edges
mask = np.zeros_like(depth_roi, dtype=np.uint8)
for edge_point in edges:
mask[edge_point[1], edge_point[0]] = 1
masked_depth_roi = depth_roi * mask
# Extract the 3D coordinates of the points on the edges
edge_points = []
for edge_point in edges:
edge_points.append([edge_point[0], edge_point[1], masked_depth_roi[edge_point[1], edge_point[0]]])
# Convert the list of edge points to a numpy array
edge_points = np.array(edge_points)
# Shift the edge points so that the mean depth value is at the origin
edge_points = edge_points - np.array([width/2, height/2, mean_depth])
# Compute the singular value decomposition (SVD) of the edge points
U, S, V = np.linalg.svd(edge_points)
# Extract the normal vector of the plane that best fits the edge points from the right-singular vector corresponding to the smallest singular value
normal = V[2]
return normal
def filter_quaternion(quat, quat_prev, alpha):
if quat_prev is None:
quat_prev = quat
# Apply low-pass filter to quaternion
quat_filtered = np.zeros(4)
for i in range(4):
quat_filtered[i] = alpha * quat[i] + (1-alpha) * quat_prev[i]
# Normalize the quaternion
quat_filtered = quat_filtered / np.linalg.norm(quat_filtered)
return quat_filtered
def box_callback(box, depth, color_info):
try:
color_intrinsics = color_info.K
@@ -33,18 +101,11 @@ def box_callback(box, depth, color_info):
z = np.mean(depth_roi) * 0.001
x = (screw_x - color_intrinsics[2]) * z / color_intrinsics[0]
y = (screw_y - color_intrinsics[5]) * z / color_intrinsics[4]
rospy.loginfo("screw pose: x: %f, y: %f, z: %f", x, y, z)
# rospy.loginfo("screw pose: x: %f, y: %f, z: %f", x, y, z)
# calculate normal direction of screw area
X,Y = np.meshgrid(np.arange(depth_roi.shape[1]), np.arange(depth_roi.shape[0]))
X = X.reshape(-1)
Y = Y.reshape(-1)
Z = depth_roi.reshape(-1)
points = np.vstack([X, Y, Z]).T
center = np.mean(points, axis=0)
points = points - center
U, S, V = np.linalg.svd(points)
normal = V[2]
annulus_roi = depth_array[boundingBox.ymin-annulus_width:boundingBox.ymax+annulus_width, boundingBox.xmin-annulus_width:boundingBox.xmax+annulus_width]
normal = calculate_image_edge_plane_normal(annulus_roi)
# print(normal)
# publish screw pose
@@ -61,6 +122,24 @@ def box_callback(box, depth, color_info):
# pose_pub.publish(screw_pose)
# normal vector to quaternion
screw_quat = tf.transformations.quaternion_from_euler(0, 0, 0)
screw_quat[0] = normal[0]
screw_quat[1] = normal[1]
screw_quat[2] = normal[2]
screw_quat[3] = 0
# quaternion to euler
screw_euler = tf.transformations.euler_from_quaternion(screw_quat)
screw_quat = tf.transformations.quaternion_from_euler(screw_euler[0], screw_euler[1], 0)
# Apply low-pass filter to screw quaternion
alpha = 0.4
global screw_quat_prev
screw_quat_filtered = filter_quaternion(screw_quat, screw_quat_prev, alpha)
screw_quat_prev = screw_quat_filtered
# publish screw tf
screw_tf = TransformStamped()
screw_tf.header.stamp = rospy.Time.now()
@@ -69,10 +148,10 @@ def box_callback(box, depth, color_info):
screw_tf.transform.translation.x = x
screw_tf.transform.translation.y = y
screw_tf.transform.translation.z = z
screw_tf.transform.rotation.x = normal[0]
screw_tf.transform.rotation.y = normal[1]
screw_tf.transform.rotation.z = normal[2]
screw_tf.transform.rotation.w = 0
screw_tf.transform.rotation.x = screw_quat_filtered[0]
screw_tf.transform.rotation.y = screw_quat_filtered[1]
screw_tf.transform.rotation.z = screw_quat_filtered[2]
screw_tf.transform.rotation.w = screw_quat_filtered[3]
tf_broadcaster.sendTransform(screw_tf)
@@ -84,6 +163,8 @@ def box_callback(box, depth, color_info):
if __name__ == "__main__":
global screw_quat_prev
screw_quat_prev = None
rospy.init_node("maintain")
rospy.loginfo("maintain task start ......")