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rrt_reeds_shepp.py
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import copy
import math
import os
import random
import sys
import matplotlib.pyplot as plt
import numpy as np
from math import sin, cos, pi
try:
import reeds_shepp_planner
from rrt import RRT
except ImportError:
raise
class RRTReedsShepp(RRT):
class Node(RRT.Node):
def __init__(self, x, y, yaw):
super().__init__(x, y)
self.yaw = yaw
self.path_yaw = []
def __init__(self, start, goal, obstacle_list, rand_area,
max_iter):
self.start = self.Node(start[0], start[1], start[2])
self.end = self.Node(goal[0], goal[1], goal[2])
self.area = rand_area
self.min_x = rand_area[0]
self.max_x = rand_area[1]
self.min_y = rand_area[2]
self.max_y = rand_area[3]
self.max_iter = max_iter
self.obstacle_list = obstacle_list
self.node_failed_list = []
self.min_radius = 0.4
self.step_size = 0.02
self.goal_dist = 0.5
self.goal_sample_rate = 0.01
def planning(self):
self.node_list = [self.start]
for i in range(self.max_iter):
rnd = self.get_random_node()
nearest_ind = self.get_nearest_node_index(self.node_list, rnd)
new_node = self.steer(self.node_list[nearest_ind], rnd)
if self.check_collision(new_node, self.obstacle_list, self.area):
self.node_list.append(new_node)
else:
self.node_failed_list.append(new_node)
if i % 5 == 0:
self.plot_start_goal_arrow()
self.draw_graph(rnd)
if new_node and random.randint(0, 100) >= self.goal_sample_rate:
last_index = self.search_goal_node()
if last_index:
return self.generate_final_course(last_index)
print("Maximum Iteration reached")
last_index = self.search_goal_node()
if last_index:
return self.generate_final_course(last_index)
else:
print("Cannot find path")
return None
def try_goal_path(self, node):
goal = self.Node(self.end.x, self.end.y, self.end.yaw)
new_node = self.steer(node, goal)
if new_node is None:
return
if self.check_collision(new_node, self.obstacle_list, self.area):
self.node_list.append(new_node)
def steer(self, from_node, to_node):
px, py, pyaw, mode, clengths = reeds_shepp_planner.reeds_shepp_planner(
from_node.x, from_node.y, from_node.yaw,
to_node.x, to_node.y, to_node.yaw, self.min_radius, self.step_size)
if not px:
return None
for i in range(0, len(px)):
if px[i]<self.min_x or px[i]>self.max_x or py[i]<self.min_y or py[i]>self.max_y:
return None
new_node = copy.deepcopy(from_node)
new_node.x = px[-1]
new_node.y = py[-1]
new_node.yaw = pyaw[-1]
new_node.path_x = px
new_node.path_y = py
new_node.path_yaw = pyaw
new_node.parent = from_node
return new_node
def get_random_node(self):
rnd = self.Node(random.uniform(self.min_x, self.max_x),
random.uniform(self.min_y, self.max_y),
random.uniform(-math.pi, math.pi)
)
return rnd
def search_goal_node(self):
goal_indexes = []
for (i, node) in enumerate(self.node_list):
if self.calc_dist_to_goal(node.x, node.y) <= self.goal_dist:
goal_indexes.append(i)
if not goal_indexes:
return None
for i in goal_indexes:
nod = self.steer(self.node_list[i], self.end)
if self.check_collision(nod, self.obstacle_list, self.area):
return i
return None
def generate_final_course(self, goal_index):
path = [[self.end.x, self.end.y, self.end.yaw]]
node = self.node_list[goal_index]
while node.parent:
for (ix, iy, iyaw) in zip(reversed(node.path_x), reversed(node.path_y), reversed(node.path_yaw)):
path.append([ix, iy, iyaw])
node = node.parent
path.append([self.start.x, self.start.y, self.start.yaw])
return path
def draw_graph(self, rnd=None):
plt.clf()
plt.gcf().canvas.mpl_connect('key_release_event',
lambda event: [exit(0) if event.key == 'escape' else None])
if rnd is not None:
plt.plot(rnd.x, rnd.y, "^k")
for node in self.node_list:
reeds_shepp_planner.plot_arrow(
node.x, node.y, node.yaw, length=0.01, width=0.15, fc="g", ec="k")
if node.parent:
plt.plot(node.path_x, node.path_y, "r")
for node in self.node_failed_list:
if node:
reeds_shepp_planner.plot_arrow(
node.x, node.y, node.yaw, length=0.01, width=0.15, fc="k", ec="k")
for (x, y, r) in self.obstacle_list:
self.plot_circle(x, y, r)
plt.plot(self.start.x, self.start.y, "xr")
plt.plot(self.end.x, self.end.y, "xr")
plt.axis([-3.1, 3.1, -1.05, 1.05])
plt.grid(True)
self.plot_start_goal_arrow()
plt.pause(0.001)
def plot_start_goal_arrow(self):
reeds_shepp_planner.plot_arrow(
self.start.x, self.start.y, self.start.yaw, length=0.01, width=0.2, fc="r", ec="k")
reeds_shepp_planner.plot_arrow(
self.end.x, self.end.y, self.end.yaw, length=0.01, width=0.2, fc="b", ec="k")
def plot_circle(self, x, y, size, color="-k"):
deg = list(range(0, 360, 5))
deg.append(0)
xl = [x + size * math.cos(np.deg2rad(d)) for d in deg]
yl = [y + size * math.sin(np.deg2rad(d)) for d in deg]
plt.plot(xl, yl, color)
def main():
dt = 0.2
obstacleList = [
(0, 1, 1.0 - dt),
(0, -1, 1.0 - dt)
]
start = [-2.0, -0.5, 0.0]
goal = [2.0, -0.5, math.pi / 2]
rrt_reeds_shepp = RRTReedsShepp(start, goal, obstacleList, [-3, 3, -1, 1], 400)
path = rrt_reeds_shepp.planning()
if path:
rrt_reeds_shepp.draw_graph()
plt.plot([x for (x, y, yaw) in path], [y for (x, y, yaw) in path], '-b')
plt.grid(True)
plt.pause(0.0001)
plt.show()
if __name__ == '__main__':
main()