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replace math.radians to np.deg2rad

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Atsushi Sakai
2018-10-23 21:49:08 +09:00
parent 15e044d015
commit a164faa7f2
30 changed files with 107 additions and 106 deletions
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8
SLAM/EKFSLAM/ekf_slam.py
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@@ -12,11 +12,11 @@ import matplotlib.pyplot as plt
# EKF state covariance
Cx = np.diag([0.5, 0.5, math.radians(30.0)])**2
Cx = np.diag([0.5, 0.5, np.deg2rad(30.0)])**2
# Simulation parameter
Qsim = np.diag([0.2, math.radians(1.0)])**2
Rsim = np.diag([1.0, math.radians(10.0)])**2
Qsim = np.diag([0.2, np.deg2rad(1.0)])**2
Rsim = np.diag([1.0, np.deg2rad(10.0)])**2
DT = 0.1 # time tick [s]
SIM_TIME = 50.0 # simulation time [s]
@@ -203,7 +203,7 @@ def jacobH(q, delta, x, i):
def pi_2_pi(angle):
return (angle + math.pi) % (2*math.pi) - math.pi
return (angle + math.pi) % (2 * math.pi) - math.pi
def main():

10
SLAM/FastSLAM1/fast_slam1.py
View File

@@ -12,12 +12,12 @@ import matplotlib.pyplot as plt
# Fast SLAM covariance
Q = np.diag([3.0, math.radians(10.0)])**2
R = np.diag([1.0, math.radians(20.0)])**2
Q = np.diag([3.0, np.deg2rad(10.0)])**2
R = np.diag([1.0, np.deg2rad(20.0)])**2
# Simulation parameter
Qsim = np.diag([0.3, math.radians(2.0)])**2
Rsim = np.diag([0.5, math.radians(10.0)])**2
Qsim = np.diag([0.3, np.deg2rad(2.0)])**2
Rsim = np.diag([0.5, np.deg2rad(10.0)])**2
OFFSET_YAWRATE_NOISE = 0.01
DT = 0.1 # time tick [s]
@@ -325,7 +325,7 @@ def motion_model(x, u):
def pi_2_pi(angle):
return (angle + math.pi) % (2*math.pi) - math.pi
return (angle + math.pi) % (2 * math.pi) - math.pi
def main():

10
SLAM/FastSLAM2/fast_slam2.py
View File

@@ -12,12 +12,12 @@ import matplotlib.pyplot as plt
# Fast SLAM covariance
Q = np.diag([3.0, math.radians(10.0)])**2
R = np.diag([1.0, math.radians(20.0)])**2
Q = np.diag([3.0, np.deg2rad(10.0)])**2
R = np.diag([1.0, np.deg2rad(20.0)])**2
# Simulation parameter
Qsim = np.diag([0.3, math.radians(2.0)])**2
Rsim = np.diag([0.5, math.radians(10.0)])**2
Qsim = np.diag([0.3, np.deg2rad(2.0)])**2
Rsim = np.diag([0.5, np.deg2rad(10.0)])**2
OFFSET_YAWRATE_NOISE = 0.01
DT = 0.1 # time tick [s]
@@ -354,7 +354,7 @@ def motion_model(x, u):
def pi_2_pi(angle):
return (angle + math.pi) % (2*math.pi) - math.pi
return (angle + math.pi) % (2 * math.pi) - math.pi
def main():

8
SLAM/GraphBasedSLAM/graph_based_slam.py
View File

@@ -18,8 +18,8 @@ import matplotlib.pyplot as plt
# Simulation parameter
Qsim = np.diag([0.2, math.radians(1.0)])**2
Rsim = np.diag([0.1, math.radians(10.0)])**2
Qsim = np.diag([0.2, np.deg2rad(1.0)])**2
Rsim = np.diag([0.1, np.deg2rad(10.0)])**2
DT = 2.0 # time tick [s]
SIM_TIME = 100.0 # simulation time [s]
@@ -29,7 +29,7 @@ STATE_SIZE = 3 # State size [x,y,yaw]
# Covariance parameter of Graph Based SLAM
C_SIGMA1 = 0.1
C_SIGMA2 = 0.1
C_SIGMA3 = math.radians(1.0)
C_SIGMA3 = np.deg2rad(1.0)
MAX_ITR = 20 # Maximum iteration
@@ -253,7 +253,7 @@ def motion_model(x, u):
def pi_2_pi(angle):
return (angle + math.pi) % (2*math.pi) - math.pi
return (angle + math.pi) % (2 * math.pi) - math.pi
def main():

2
SLAM/iterative_closest_point/iterative_closest_point.py
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@@ -138,7 +138,7 @@ def main():
# simulation parameters
nPoint = 10
fieldLength = 50.0
motion = [0.5, 2.0, math.radians(-10.0)] # movement [x[m],y[m],yaw[deg]]
motion = [0.5, 2.0, np.deg2rad(-10.0)] # movement [x[m],y[m],yaw[deg]]
nsim = 3 # number of simulation