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PathPlanning/Search_based_Planning/Search_2D/Dijkstra.py
T
zhm-real 7bcd3f24a6 update
2020-08-10 12:22:06 -07:00

140 lines
3.7 KiB
Python

"""
Dijkstra 2D
@author: huiming zhou
"""
import os
import sys
import math
import heapq
sys.path.append(os.path.dirname(os.path.abspath(__file__)) +
"/../../Search_based_Planning/")
from Search_based_Planning.Search_2D import plotting, env
class Dijkstra:
def __init__(self, s_start, s_goal):
self.s_start = s_start
self.s_goal = s_goal
self.Env = env.Env()
self.plotting = plotting.Plotting(self.s_start, self.s_goal)
self.u_set = self.Env.motions # feasible input set
self.obs = self.Env.obs # position of obstacles
self.OPEN = [] # priority queue / OPEN set
self.CLOSED = [] # closed set & visited
self.PARENT = dict() # record parent
self.g = dict() # Cost to come
def searching(self):
"""
Dijkstra Searching.
:return: path, visited order
"""
self.PARENT[self.s_start] = self.s_start
self.g[self.s_start] = 0
self.g[self.s_goal] = math.inf
heapq.heappush(self.OPEN, (0, self.s_start))
while self.OPEN:
_, s = heapq.heappop(self.OPEN)
self.CLOSED.append(s)
if s == self.s_goal:
break
for s_n in self.get_neighbor(s):
new_cost = self.g[s] + self.cost(s, s_n)
if s_n not in self.g:
self.g[s_n] = math.inf
if new_cost < self.g[s_n]:
self.g[s_n] = new_cost
heapq.heappush(self.OPEN, (new_cost, s_n))
self.PARENT[s_n] = s
return self.extract_path(), self.CLOSED
def get_neighbor(self, s):
"""
find neighbors of state s that not in obstacles.
:param s: state
:return: neighbors
"""
return [(s[0] + u[0], s[1] + u[1]) for u in self.u_set]
def extract_path(self):
"""
Extract the path based on PARENT set.
:return: The planning path
"""
path = [self.s_goal]
s = self.s_goal
while True:
s = self.PARENT[s]
path.append(s)
if s == self.s_start:
break
return list(path)
def cost(self, s_start, s_goal):
"""
Calculate Cost for this motion
:param s_start: starting node
:param s_goal: end node
:return: Cost for this motion
"""
if self.is_collision(s_start, s_goal):
return math.inf
return math.hypot(s_goal[0] - s_start[0], s_goal[1] - s_start[1])
def is_collision(self, s_start, s_end):
"""
check if the line segment (s_start, s_end) is collision.
:param s_start: start node
:param s_end: end node
:return: True: is collision / False: not collision
"""
if s_start in self.obs or s_end in self.obs:
return True
if s_start[0] != s_end[0] and s_start[1] != s_end[1]:
if s_end[0] - s_start[0] == s_start[1] - s_end[1]:
s1 = (min(s_start[0], s_end[0]), min(s_start[1], s_end[1]))
s2 = (max(s_start[0], s_end[0]), max(s_start[1], s_end[1]))
else:
s1 = (min(s_start[0], s_end[0]), max(s_start[1], s_end[1]))
s2 = (max(s_start[0], s_end[0]), min(s_start[1], s_end[1]))
if s1 in self.obs or s2 in self.obs:
return True
return False
def main():
s_start = (5, 5)
s_goal = (45, 25)
dijkstra = Dijkstra(s_start, s_goal)
plot = plotting.Plotting(s_start, s_goal)
path, visited = dijkstra.searching()
plot.animation(path, visited, "Dijkstra's") # animation generate
if __name__ == '__main__':
main()