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1 parent 3a67dac commit 8e741ef40bf88f07c12dff065f67c32ba02ce856 huanghuang committed Mar 25, 2012
Showing with 318 additions and 2 deletions.
  1. +161 −0 5-11.py
  2. +3 −2 5-5.py
  3. +154 −0 5-9.py
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@@ -0,0 +1,161 @@
+# -----------
+# User Instructions
+#
+# Implement a PD controller by running 100 iterations
+# of robot motion. The steering angle should be set
+# by the parameter tau so that:
+#
+# steering = -tau_p * CTE - tau_d * diff_CTE
+# where differential crosstrack error (diff_CTE)
+# is given by CTE(t) - CTE(t-1)
+#
+# Your code should print output that looks like
+# the output shown in the video.
+#
+# Only modify code at the bottom!
+# ------------
+
+from math import *
+import random
+
+
+# ------------------------------------------------
+#
+# this is the robot class
+#
+
+class robot:
+
+ # --------
+ # init:
+ # creates robot and initializes location/orientation to 0, 0, 0
+ #
+
+ def __init__(self, length = 20.0):
+ self.x = 0.0
+ self.y = 0.0
+ self.orientation = 0.0
+ self.length = length
+ self.steering_noise = 0.0
+ self.distance_noise = 0.0
+ self.steering_drift = 0.0
+
+ # --------
+ # set:
+ # sets a robot coordinate
+ #
+
+ def set(self, new_x, new_y, new_orientation):
+
+ self.x = float(new_x)
+ self.y = float(new_y)
+ self.orientation = float(new_orientation) % (2.0 * pi)
+
+
+ # --------
+ # set_noise:
+ # sets the noise parameters
+ #
+
+ def set_noise(self, new_s_noise, new_d_noise):
+ # makes it possible to change the noise parameters
+ # this is often useful in particle filters
+ self.steering_noise = float(new_s_noise)
+ self.distance_noise = float(new_d_noise)
+
+ # --------
+ # set_steering_drift:
+ # sets the systematical steering drift parameter
+ #
+
+ def set_steering_drift(self, drift):
+ self.steering_drift = drift
+
+ # --------
+ # move:
+ # steering = front wheel steering angle, limited by max_steering_angle
+ # distance = total distance driven, most be non-negative
+
+ def move(self, steering, distance,
+ tolerance = 0.001, max_steering_angle = pi / 4.0):
+
+ if steering > max_steering_angle:
+ steering = max_steering_angle
+ if steering < -max_steering_angle:
+ steering = -max_steering_angle
+ if distance < 0.0:
+ distance = 0.0
+
+
+ # make a new copy
+ res = robot()
+ res.length = self.length
+ res.steering_noise = self.steering_noise
+ res.distance_noise = self.distance_noise
+ res.steering_drift = self.steering_drift
+
+ # apply noise
+ steering2 = random.gauss(steering, self.steering_noise)
+ distance2 = random.gauss(distance, self.distance_noise)
+
+ # apply steering drift
+ steering2 += self.steering_drift
+
+ # Execute motion
+ turn = tan(steering2) * distance2 / res.length
+
+ if abs(turn) < tolerance:
+
+ # approximate by straight line motion
+
+ res.x = self.x + (distance2 * cos(self.orientation))
+ res.y = self.y + (distance2 * sin(self.orientation))
+ res.orientation = (self.orientation + turn) % (2.0 * pi)
+
+ else:
+
+ # approximate bicycle model for motion
+
+ radius = distance2 / turn
+ cx = self.x - (sin(self.orientation) * radius)
+ cy = self.y + (cos(self.orientation) * radius)
+ res.orientation = (self.orientation + turn) % (2.0 * pi)
+ res.x = cx + (sin(res.orientation) * radius)
+ res.y = cy - (cos(res.orientation) * radius)
+
+ return res
+
+ def __repr__(self):
+ return '[x=%.5f y=%.5f orient=%.5f]' % (self.x, self.y, self.orientation)
+
+############## ADD / MODIFY CODE BELOW ####################
+
+# ------------------------------------------------------------------------
+#
+# run - does a single control run.
+
+
+def run(param1, param2):
+ myrobot = robot()
+ myrobot.set(0.0, 1.0, 0.0)
+ #myrobot.set_steering_drift(10.0 / 180.8 * pi)
+ speed = 1.0 # motion distance is equal to speed (we assume time = 1)
+ N = 100
+ cte = myrobot.y
+ for i in range(N):
+ cte_now = myrobot.y
+ steer = -param1 * cte_now - param2 * (cte_now - cte)
+ myrobot = myrobot.move(steer, speed)
+ cte = cte_now
+ print myrobot, steer
+
+ #
+ # Enter code here
+ #
+
+# Call your function with parameters of 0.2 and 3.0 and print results
+run(0.2, 3.0)
+
+
+
+
View
@@ -17,8 +17,9 @@
#(Xi-Yi)**2 --> min
#(Yi-Yi+1)**2 --> min
#
-# Xi means the element in old path
-# Yi means the element in new path
+# Xi means the element in old path path[i][j]
+# Yi means the element in new path newpath[i][j] Yi-1 Yi+1 means newpath[i-1][j]
+# newpath[i+1][j]
# j means for x cordinate and y cordiante we use the same method
# tolerance means until the change would not make a difference big than that
View
@@ -0,0 +1,154 @@
+# -----------
+# User Instructions
+#
+# Implement a P controller by running 100 iterations
+# of robot motion. The steering angle should be set
+# by the parameter tau so that:
+#
+# steering = -tau * crosstrack_error
+#
+# Note that tau is called "param" in the function
+# run to be completed below.
+#
+# Your code should print output that looks like
+# the output shown in the video. That is, at each step:
+# print myrobot, steering
+#
+# Only modify code at the bottom!
+# ------------
+
+from math import *
+import random
+
+
+# ------------------------------------------------
+#
+# this is the robot class
+#
+
+class robot:
+
+ # --------
+ # init:
+ # creates robot and initializes location/orientation to 0, 0, 0
+ #
+
+ def __init__(self, length = 20.0):
+ self.x = 0.0
+ self.y = 0.0
+ self.orientation = 0.0
+ self.length = length
+ self.steering_noise = 0.0
+ self.distance_noise = 0.0
+ self.steering_drift = 0.0
+
+ # --------
+ # set:
+ # sets a robot coordinate
+ #
+
+ def set(self, new_x, new_y, new_orientation):
+
+ self.x = float(new_x)
+ self.y = float(new_y)
+ self.orientation = float(new_orientation) % (2.0 * pi)
+
+
+ # --------
+ # set_noise:
+ # sets the noise parameters
+ #
+
+ def set_noise(self, new_s_noise, new_d_noise):
+ # makes it possible to change the noise parameters
+ # this is often useful in particle filters
+ self.steering_noise = float(new_s_noise)
+ self.distance_noise = float(new_d_noise)
+
+ # --------
+ # set_steering_drift:
+ # sets the systematical steering drift parameter
+ #
+
+ def set_steering_drift(self, drift):
+ self.steering_drift = drift
+
+ # --------
+ # move:
+ # steering = front wheel steering angle, limited by max_steering_angle
+ # distance = total distance driven, most be non-negative
+
+ def move(self, steering, distance,
+ tolerance = 0.001, max_steering_angle = pi / 4.0):
+
+ if steering > max_steering_angle:
+ steering = max_steering_angle
+ if steering < -max_steering_angle:
+ steering = -max_steering_angle
+ if distance < 0.0:
+ distance = 0.0
+
+
+ # make a new copy
+ res = robot()
+ res.length = self.length
+ res.steering_noise = self.steering_noise
+ res.distance_noise = self.distance_noise
+ res.steering_drift = self.steering_drift
+
+ # apply noise
+ steering2 = random.gauss(steering, self.steering_noise)
+ distance2 = random.gauss(distance, self.distance_noise)
+
+ # apply steering drift
+ steering2 += self.steering_drift
+
+ # Execute motion
+ turn = tan(steering2) * distance2 / res.length
+
+ if abs(turn) < tolerance:
+
+ # approximate by straight line motion
+
+ res.x = self.x + (distance2 * cos(self.orientation))
+ res.y = self.y + (distance2 * sin(self.orientation))
+ res.orientation = (self.orientation + turn) % (2.0 * pi)
+
+ else:
+
+ # approximate bicycle model for motion
+
+ radius = distance2 / turn
+ cx = self.x - (sin(self.orientation) * radius)
+ cy = self.y + (cos(self.orientation) * radius)
+ res.orientation = (self.orientation + turn) % (2.0 * pi)
+ res.x = cx + (sin(res.orientation) * radius)
+ res.y = cy - (cos(res.orientation) * radius)
+
+ return res
+
+ def __repr__(self):
+ return '[x=%.5f y=%.5f orient=%.5f]' % (self.x, self.y, self.orientation)
+
+############## ADD / MODIFY CODE BELOW ####################
+
+# ------------------------------------------------------------------------
+#
+# run - does a single control run
+
+
+def run(param):
+ myrobot = robot()
+ myrobot.set(0.0, 1.0, 0.0)
+ speed = 1.0 # motion distance is equal to speed (we assume time = 1)
+ N = 100
+ #
+ # Add Code Here
+ #
+ for i in range(N):
+ steering = -param * myrobot.y
+ myrobot = myrobot.move(steering, speed)
+ print myrobot, steering
+
+run(0.1) # call function with parameter tau of 0.1 and print results
+

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