ecki/Robotics-at-Home-with-Raspberry-Pi-Pico
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This rename makes the code easier to type and read.

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Danny Staple
2023-01-21 19:54:31 +00:00
parent 2d785f90ec
commit 2b720cedca
4 changed files with 15 additions and 15 deletions
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ch-13/3.4-movement-uncertainty/banana_shaped.py
+3 -3
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@@ -18,14 +18,14 @@ motion_line = np.array([[250, 300],
[motion_scale * np.cos(np.radians(motion_angle)), motion_scale * np.sin(np.radians(motion_angle))]])
def get_scaled_sample_around_mean(mean, scale):
def get_random_sample(mean, scale):
return mean + (random.uniform(-scale, scale) + random.uniform(-scale, scale)) / 2
rotation_scale = 0.05 * abs(motion_angle) + 0.01 * abs(motion_scale)
translation_scale = 0.05 * abs(motion_scale) + 0.01 * abs(motion_angle)
motion_rotation = np.array([get_scaled_sample_around_mean(motion_angle, rotation_scale) for _ in range(poses.shape[0])])
motion_translation = np.array([get_scaled_sample_around_mean(motion_scale, translation_scale) for _ in range(poses.shape[0])])
motion_rotation = np.array([get_random_sample(motion_angle, rotation_scale) for _ in range(poses.shape[0])])
motion_translation = np.array([get_random_sample(motion_scale, translation_scale) for _ in range(poses.shape[0])])
new_poses = np.zeros_like(poses)
new_poses[:, 0] = poses[:, 0] + motion_translation * np.cos(np.radians(motion_rotation))
ch-13/3.4-movement-uncertainty/robot/code.py
+4 -4
View File
@@ -41,7 +41,7 @@ class CollisionAvoid:
robot.set_left(self.speed)
await asyncio.sleep(0)
def get_scaled_sample_around_mean(mean, scale):
def get_random_sample(mean, scale):
return mean + (random.uniform(-scale, scale) + random.uniform(-scale, scale)) / 2
def send_json(data):
@@ -119,9 +119,9 @@ class Simulation:
rot1_scale = self.alpha_rot * abs(rot1) + self.alpha_rot_trans * abs(trans)
trans_scale = self.alpha_trans * abs(trans) + self.alpha_trans_rot * (abs(rot1) + abs(rot2))
rot2_scale = self.alpha_rot * abs(rot2) + self.alpha_rot_trans * abs(trans)
rot1_model = np.array([get_scaled_sample_around_mean(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
trans_model = np.array([get_scaled_sample_around_mean(trans, trans_scale) for _ in range(self.poses.shape[0])])
rot2_model = np.array([get_scaled_sample_around_mean(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
rot1_model = np.array([get_random_sample(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
trans_model = np.array([get_random_sample(trans, trans_scale) for _ in range(self.poses.shape[0])])
rot2_model = np.array([get_random_sample(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
return rot1_model, trans_model, rot2_model
def motion_model(self):
ch-13/4.1-generating-weights/robot/code.py
+4 -4
View File
@@ -41,7 +41,7 @@ class CollisionAvoid:
robot.set_left(self.speed)
await asyncio.sleep(0)
def get_scaled_sample_around_mean(mean, scale):
def get_random_sample(mean, scale):
return mean + (random.uniform(-scale, scale) + random.uniform(-scale, scale)) / 2
def send_json(data):
@@ -137,9 +137,9 @@ class Simulation:
rot1_scale = self.alpha_rot * abs(rot1) + self.alpha_rot_trans * abs(trans)
trans_scale = self.alpha_trans * abs(trans) + self.alpha_trans_rot * (abs(rot1) + abs(rot2))
rot2_scale = self.alpha_rot * abs(rot2) + self.alpha_rot_trans * abs(trans)
rot1_model = np.array([get_scaled_sample_around_mean(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
trans_model = np.array([get_scaled_sample_around_mean(trans, trans_scale) for _ in range(self.poses.shape[0])])
rot2_model = np.array([get_scaled_sample_around_mean(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
rot1_model = np.array([get_random_sample(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
trans_model = np.array([get_random_sample(trans, trans_scale) for _ in range(self.poses.shape[0])])
rot2_model = np.array([get_random_sample(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
return rot1_model, trans_model, rot2_model
def motion_model(self):
ch-13/4.3-monte-carlo/robot/code.py
+4 -4
View File
@@ -41,7 +41,7 @@ class CollisionAvoid:
robot.set_left(self.speed)
await asyncio.sleep(0)
def get_scaled_sample_around_mean(mean, scale):
def get_random_sample(mean, scale):
return mean + (random.uniform(-scale, scale) + random.uniform(-scale, scale)) / 2
def send_json(data):
@@ -137,9 +137,9 @@ class Simulation:
rot1_scale = self.alpha_rot * abs(rot1) + self.alpha_rot_trans * abs(trans)
trans_scale = self.alpha_trans * abs(trans) + self.alpha_trans_rot * (abs(rot1) + abs(rot2))
rot2_scale = self.alpha_rot * abs(rot2) + self.alpha_rot_trans * abs(trans)
rot1_model = np.array([get_scaled_sample_around_mean(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
trans_model = np.array([get_scaled_sample_around_mean(trans, trans_scale) for _ in range(self.poses.shape[0])])
rot2_model = np.array([get_scaled_sample_around_mean(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
rot1_model = np.array([get_random_sample(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
trans_model = np.array([get_random_sample(trans, trans_scale) for _ in range(self.poses.shape[0])])
rot2_model = np.array([get_random_sample(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
return rot1_model, trans_model, rot2_model
def motion_model(self):