53 lines
1.9 KiB
Plaintext
53 lines
1.9 KiB
Plaintext
import numpy as np
|
||
|
||
def vec2attitude(a,b,c):
|
||
pi = np.arccos(-1.0) # pi 的值
|
||
|
||
# 输入a, b, c
|
||
# 定义矩阵
|
||
r1 = np.array([[1, 0, 0],
|
||
[0, np.cos(a * pi), np.sin(a * pi)],
|
||
[0, -np.sin(a * pi), np.cos(a * pi)]]) # r1 矩阵 3x3
|
||
|
||
r2 = np.array([[np.cos(b * pi), 0, -np.sin(b * pi)],
|
||
[0, 1, 0],
|
||
[np.sin(b * pi), 0, np.cos(b * pi)]]) # r2 矩阵 3x3
|
||
|
||
r3 = np.array([[np.cos(c * pi), np.sin(c * pi), 0],
|
||
[-np.sin(c * pi), np.cos(c * pi), 0],
|
||
[0, 0, 1]]) # r3 矩阵 3x3
|
||
|
||
vector1 = np.array([[1], [1], [1]]) # 初始向量 3x1
|
||
|
||
# 旋转矩阵相乘并应用于向量
|
||
matrix_result = np.dot(np.dot(np.dot(r1, r2), r3), vector1)
|
||
|
||
# 输出结果
|
||
rpy=[]
|
||
for m in range(matrix_result.shape[0]):
|
||
rpy.append(matrix_result[m][0])
|
||
print(f"{matrix_result[m][0]:<20}")
|
||
|
||
return rpy
|
||
|
||
#黄老师会给我传目标物的中心点坐标x,y,z和目标位姿的平面法向量a,b,c
|
||
def getPosition(x,y,z,a,b,c):
|
||
target = np.asarray([x, y, z])
|
||
camera2robot = np.loadtxt('D:\BaiduNetdiskDownload\机械臂\GRCNN\\real\cam_pose.txt', delimiter=' ')
|
||
position = np.dot(camera2robot[0:3, 0:3], target) + camera2robot[0:3, 3:]
|
||
target_position = position[0:3, 0]#转换后的位置信息
|
||
|
||
# vector = np.asarray([a, b, c])
|
||
# normal_vector = vector / np.linalg.norm(vector)#归一化
|
||
# normal_vector.shape = (3, 1)
|
||
# dot_angle = np.dot(camera2robot[0:3, 0:3], normal_vector)#转换后的法向量,方向依然是同一个方向，只是表示方法变了
|
||
|
||
# angle_tool = R.from_matrix(camera2robot[0:3, 0:3])
|
||
rpy = vec2attitude(a,b,c)
|
||
r,p,y=rpy[0],rpy[1],rpy[2]#r表示u,p表示v，y表示w
|
||
target_angle_raw = np.asarray([r,p,y])
|
||
target_angle = np.dot(camera2robot[0:3, 0:3],target_angle_raw)
|
||
print(target_position,target_angle)
|
||
|
||
return target_position, target_angle
|