first commit

Trace/vec_change.py

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+import numpy as np
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+def plot_coordinate_system(ax, T, name, color, labels):
+    """绘制坐标系"""
+    origin = T[:3, 3]
+    x_axis = origin + T[:3, 0] * 300  # X 轴
+    y_axis = origin + T[:3, 1] * 300  # Y 轴
+    z_axis = origin + T[:3, 2] * 300  # Z 轴
+
+    # 绘制原点
+    ax.scatter(*origin, color=color, s=100)
+
+    # 绘制轴线
+    ax.quiver(*origin, *(x_axis - origin), color='r', length=1, arrow_length_ratio=0.2, linewidth=2)
+    ax.quiver(*origin, *(y_axis - origin), color='g', length=1, arrow_length_ratio=0.2, linewidth=2)
+    ax.quiver(*origin, *(z_axis - origin), color='b', length=1, arrow_length_ratio=0.2, linewidth=2)
+
+    # 标注坐标系名称
+    ax.text(*x_axis, f'{labels[0]}', color='r', fontsize=12)
+    ax.text(*y_axis, f'{labels[1]}', color='g', fontsize=12)
+    ax.text(*z_axis, f'{labels[2]}', color='b', fontsize=12)
+
+# A 到 B 的齐次转换矩阵 (工具到基坐标系)
+T_AB = np.array([[-9.36910568e-01,-4.37100341e-03, 3.49541818e-01, 5.04226000e+02],
+ [-5.82144893e-03, 9.99978253e-01, -3.09911034e-03, 2.62300000e+00],
+ [-3.49520671e-01, -4.93842907e-03, -9.36915638e-01, 5.23709000e+02],
+ [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.00000000e+00]])
+
+# B 到 C 的齐次转换矩阵 (相机到工具)
+T_BC = np.loadtxt('./com_pose.txt', delimiter=' ')
+
+# 计算 A 到 C 的齐次转换矩阵
+# T_AC = T_AB @ T_BC
+
+# 输入四个角点的空间坐标 (相机坐标系下)
+# corner_points_camera = np.array([
+# [-605.3829, 288.2771, 1710.0],
+# [-364.94568, 300.40274, 1634.0],
+# [-301.4996, -253.04178, 1645.0],
+# [-548.8065, -297.23093, 1748.0]
+# ])
+#
+# # 将角点从相机坐标系转换到基坐标系
+#
+# corner_points_base = np.dot(T_BC[:3, :3], corner_points_camera.T).T + T_BC[:3, 3]
+# edges = np.array([corner_points_base[1] - corner_points_base[0]])# for i in range(len(corner_points_base))])
+# edge_lengths = np.linalg.norm(edges, axis=1)
+# min_edge_idx = np.argmin(edge_lengths)
+# short_edge_direction = edges[min_edge_idx] / edge_lengths[min_edge_idx]  # 单位化方向向量
+
+
+corner_points_camera = np.array([
+[-548.8065, -297.23093, 1748.0],
+[-301.4996, -253.04178, 1645.0],
+[-364.94568, 300.40274, 1634.0],
+[-605.3829, 288.2771, 1710.0]
+])
+
+# 将角点从相机坐标系转换到基坐标系
+corner_points_base = np.dot(T_BC[:3, :3], corner_points_camera.T).T + T_BC[:3, 3]
+
+# 按照 x 轴排序
+sorted_points = corner_points_base[np.argsort(corner_points_base[:, 0])]
+
+# 选出x轴较大的两个点
+point_1 = sorted_points[-1]  # x值较大的点
+point_2 = sorted_points[-2]  # x值较小的点
+
+# 根据 y 值选择差值方向，y值较大的点减去 y 值较小的点
+if point_1[1] > point_2[1]:
+    edge_vector = point_1 - point_2
+else:
+    edge_vector = point_2 - point_1
+
+# 单位化方向向量
+short_edge_direction = edge_vector / np.linalg.norm(edge_vector)
+
+print("方向向量（单位化）：", short_edge_direction)
+
+
+# 假设法向量 (a, b, c) 在相机坐标系下
+normal_vector_camera = np.array([0.2694268969253701, 0.033645691818738714, 0.9624329143556991, 0])  # 最后一个元素为0，因为它是方向矢量
+
+# 将法向量从相机坐标系转换到法兰坐标系
+normal_vector_flange = T_BC @ normal_vector_camera
+
+# 将法向量从法兰坐标系转换到基坐标系
+# normal_vector_base = T_AB @ normal_vector_flange
+
+# 创建 3D 图形对象
+fig = plt.figure()
+ax = fig.add_subplot(111, projection='3d')
+
+# 设置绘图区域的范围
+ax.set_xlim([-1000, 1000])
+ax.set_ylim([-1000, 1000])
+ax.set_zlim([-1000, 1000])
+
+# 绘制基坐标系 O
+plot_coordinate_system(ax, np.eye(4), 'O', 'k', ['x', 'y', 'z'])
+
+# 绘制法兰坐标系 B
+# plot_coordinate_system(ax, T_AB, 'B', 'm', ["x'", "y'", "z'"])
+
+# 绘制相机坐标系 C
+plot_coordinate_system(ax, T_BC, 'C', 'b', ["x''", "y''", "z''"])
+
+# 绘制长边方向向量 (基坐标系下)
+origin = np.zeros(3)  # 基坐标系的原点
+short_edge_endpoint = short_edge_direction * 300
+ax.quiver(*origin, *(short_edge_endpoint), color='orange', length=1, arrow_length_ratio=0.2, linewidth=2)
+ax.text(*short_edge_endpoint, 'Short Edge', color='orange', fontsize=12)
+
+# 绘制法向量 (基坐标系下)
+normal_vector_endpoint = normal_vector_flange[:3] * 300
+ax.quiver(*origin, *(normal_vector_endpoint), color='purple', length=1, arrow_length_ratio=0.2, linewidth=2)
+ax.text(*normal_vector_endpoint, 'Normal Vector', color='purple', fontsize=12)
+
+# 在基坐标系下绘制四个角点和边
+ax.scatter(corner_points_base[:, 0], corner_points_base[:, 1], corner_points_base[:, 2], color='b', s=50, label='Corners')
+for i in range(len(corner_points_base)):
+    ax.plot([corner_points_base[i - 1, 0], corner_points_base[i, 0]],
+            [corner_points_base[i - 1, 1], corner_points_base[i, 1]],
+            [corner_points_base[i - 1, 2], corner_points_base[i, 2]], 'k--')
+
+# 设置标签
+ax.set_xlabel('X')
+ax.set_ylabel('Y')
+ax.set_zlabel('Z')
+
+# 显示图形
+plt.show()