Skip to content

Instantly share code, notes, and snippets.

@serser
Created December 14, 2017 08:16
Show Gist options
  • Save serser/e5e202395cc2d9daff3fa6e21d63da5b to your computer and use it in GitHub Desktop.
Save serser/e5e202395cc2d9daff3fa6e21d63da5b to your computer and use it in GitHub Desktop.
# https://classroom.udacity.com/courses/cs373/lessons/48743150/concepts/487372200923
# -----------
# User Instructions
#
# Implement a P controller by running 100 iterations
# of robot motion. The desired trajectory for the
# robot is the x-axis. 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
# 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!
# ------------
import random
import numpy as np
import matplotlib.pyplot as plt
# import proportional
# ------------------------------------------------
#
# this is the Robot class
#
class robot(object):
def __init__(self, length=20.0):
"""
Creates robot and initializes location/orientation to 0, 0, 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
def set(self, x, y, orientation):
"""
Sets a robot coordinate.
"""
self.x = x
self.y = y
self.orientation = orientation % (2.0 * np.pi)
def set_noise(self, steering_noise, distance_noise):
"""
Sets the noise parameters.
"""
# makes it possible to change the noise parameters
# this is often useful in particle filters
self.steering_noise = steering_noise
self.distance_noise = distance_noise
def set_steering_drift(self, drift):
"""
Sets the systematical steering drift parameter
"""
self.steering_drift = drift
def move(self, steering, distance, tolerance=0.001, max_steering_angle=np.pi / 4.0):
"""
steering = front wheel steering angle, limited by max_steering_angle
distance = total distance driven, must be non-negative
"""
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 = np.tan(steering2) * distance2 / self.length
if abs(turn) < tolerance:
# approximate by straight line motion
res.x = self.x + distance2 * np.cos(self.orientation)
res.y = self.y + distance2 * np.sin(self.orientation)
res.orientation = (self.orientation + turn) % (2.0 * np.pi)
else:
# approximate bicycle model for motion
radius = distance2 / turn
cx = self.x - (np.sin(self.orientation) * radius)
cy = self.y + (np.cos(self.orientation) * radius)
res.orientation = (self.orientation + turn) % (2.0 * np.pi)
res.x = cx + (np.sin(res.orientation) * radius)
res.y = cy - (np.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
for i in range(N):
#
# Enter code here
# proportional to cross track error
steer = param*(-myrobot.y)
myrobot = myrobot.move(steer,speed)
print( myrobot, steer )
run(0.1)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment