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Copy pathcontroller2d.py
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219 lines (186 loc) · 8.59 KB
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#!/usr/bin/env python3
import cutils
import numpy as np
class Controller2D(object):
def __init__(self, waypoints):
self.vars = cutils.CUtils()
self._current_x = 0
self._current_y = 0
self._current_yaw = 0
self._current_speed = 0
self._desired_speed = 0
self._current_frame = 0
self._current_timestamp = 0
self._start_control_loop = False
self._set_throttle = 0
self._set_brake = 0
self._set_steer = 0
self._waypoints = waypoints
self._conv_rad_to_steer = 180.0 / 70.0 / np.pi
self._pi = np.pi
self._2pi = 2.0 * np.pi
def update_values(self, x, y, yaw, speed, timestamp, frame):
self._current_x = x
self._current_y = y
self._current_yaw = yaw
self._current_speed = speed
self._current_timestamp = timestamp
self._current_frame = frame
if self._current_frame:
self._start_control_loop = True
def update_desired_speed(self):
min_idx = 0
min_dist = float("inf")
desired_speed = 0
for i in range(len(self._waypoints)):
dist = np.linalg.norm(np.array([
self._waypoints[i][0] - self._current_x,
self._waypoints[i][1] - self._current_y]))
if dist < min_dist:
min_dist = dist
min_idx = i
if min_idx < len(self._waypoints)-1:
desired_speed = self._waypoints[min_idx][2]
else:
desired_speed = self._waypoints[-1][2]
self._desired_speed = desired_speed
def update_waypoints(self, new_waypoints):
self._waypoints = new_waypoints
def get_commands(self):
return self._set_throttle, self._set_steer, self._set_brake
def set_throttle(self, input_throttle):
# Clamp the throttle command to valid bounds
throttle = np.fmax(np.fmin(input_throttle, 1.0), 0.0)
self._set_throttle = throttle
def set_steer(self, input_steer_in_rad):
# Covnert radians to [-1, 1]
input_steer = self._conv_rad_to_steer * input_steer_in_rad
# Clamp the steering command to valid bounds
steer = np.fmax(np.fmin(input_steer, 1.0), -1.0)
self._set_steer = steer
def set_brake(self, input_brake):
# Clamp the steering command to valid bounds
brake = np.fmax(np.fmin(input_brake, 1.0), 0.0)
self._set_brake = brake
def update_controls(self):
######################################################
# RETRIEVE SIMULATOR FEEDBACK
######################################################
x = self._current_x
y = self._current_y
yaw = self._current_yaw
v = self._current_speed
self.update_desired_speed()
v_desired = self._desired_speed
t = self._current_timestamp
waypoints = self._waypoints
throttle_output = 0
steer_output = 0
brake_output = 0
######################################################
######################################################
# MODULE 7: DECLARE USAGE VARIABLES HERE
######################################################
######################################################
"""
Use 'self.vars.create_var(<variable name>, <default value>)'
to create a persistent variable (not destroyed at each iteration).
This means that the value can be stored for use in the next
iteration of the control loop.
Example: Creation of 'v_previous', default value to be 0
self.vars.create_var('v_previous', 0.0)
Example: Setting 'v_previous' to be 1.0
self.vars.v_previous = 1.0
Example: Accessing the value from 'v_previous' to be used
throttle_output = 0.5 * self.vars.v_previous
"""
self.vars.create_var('v_previous', 0.0)
self.vars.create_var('t_previous', 0.0)
self.vars.create_var('throttle_previous', 0.0)
self.vars.create_var('int_val', 0.0)
self.vars.create_var('last_error', 0.0)
kp = 1
ki = 0.9
kd = 0.01
# Skip the first frame to store previous values properly
if self._start_control_loop:
# Change these outputs with the longitudinal controller. Note that
# brake_output is optional and is not required to pass the
# assignment, as the car will naturally slow down over time.
throttle_output = 0
brake_output = 0
# pid control
st = t - self.vars.t_previous
# error term
delta_v = v_desired - v
# I
integral = self.vars.int_val + delta_v * st
# D
derivate = (delta_v - self.vars.last_error) / st
rst = kp * delta_v + ki * integral + kd * derivate
if rst > 0:
throttle_output = np.tanh(rst)
throttle_output = max(0.0, min(1.0, throttle_output))
if throttle_output - self.vars.throttle_previous > 0.1:
throttle_output = self.vars.throttle_previous + 0.1
else:
throttle_output = 0
# Change the steer output with the lateral controller.
steer_output = 0
# Use stanley controller for lateral control
# 0. spectify stanley params
k_e = 0.3
k_v = 10
# 1. calculate heading error
yaw_path = np.arctan2(waypoints[-1][1]-waypoints[0][1], waypoints[-1][0]-waypoints[0][0])
yaw_diff = yaw_path - yaw
if yaw_diff > np.pi:
yaw_diff -= 2 * np.pi
if yaw_diff < - np.pi:
yaw_diff += 2 * np.pi
# 2. calculate crosstrack error
current_xy = np.array([x, y])
crosstrack_error = np.min(np.sum((current_xy - np.array(waypoints)[:, :2])**2, axis=1))
yaw_cross_track = np.arctan2(y-waypoints[0][1], x-waypoints[0][0])
yaw_path2ct = yaw_path - yaw_cross_track
if yaw_path2ct > np.pi:
yaw_path2ct -= 2 * np.pi
if yaw_path2ct < - np.pi:
yaw_path2ct += 2 * np.pi
if yaw_path2ct > 0:
crosstrack_error = abs(crosstrack_error)
else:
crosstrack_error = - abs(crosstrack_error)
yaw_diff_crosstrack = np.arctan(k_e * crosstrack_error / (k_v + v))
print(crosstrack_error, yaw_diff, yaw_diff_crosstrack)
# 3. control low
steer_expect = yaw_diff + yaw_diff_crosstrack
if steer_expect > np.pi:
steer_expect -= 2 * np.pi
if steer_expect < - np.pi:
steer_expect += 2 * np.pi
steer_expect = min(1.22, steer_expect)
steer_expect = max(-1.22, steer_expect)
# 4. update
steer_output = steer_expect
#steer_output = 0.05
######################################################
# SET CONTROLS OUTPUT
######################################################
self.set_throttle(throttle_output) # in percent (0 to 1)
self.set_steer(steer_output) # in rad (-1.22 to 1.22)
self.set_brake(brake_output) # in percent (0 to 1)
######################################################
######################################################
# MODULE 7: STORE OLD VALUES HERE (ADD MORE IF NECESSARY)
######################################################
######################################################
"""
Use this block to store old values (for example, we can store the
current x, y, and yaw values here using persistent variables for use
in the next iteration)
"""
self.vars.v_previous = v # Store forward speed to be used in next step
self.vars.t_previous = t
self.vars.int_val = integral
self.vars.throttle_previous = throttle_output