mirror of
https://github.com/zhm-real/PathPlanning.git
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zhm-real
99 lines
2.4 KiB
Python
99 lines
2.4 KiB
Python
"""
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BFS 2D (Breadth-first Searching)
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@author: huiming zhou
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"""
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import os
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import sys
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sys.path.append(os.path.dirname(os.path.abspath(__file__)) +
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"/../../Search-based Planning/")
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from Search_2D import queue
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from Search_2D import plotting
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from Search_2D import env
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class BFS:
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def __init__(self, s_start, s_goal):
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self.s_start, self.s_goal = s_start, s_goal
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self.Env = env.Env()
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self.plotting = plotting.Plotting(self.s_start, self.s_goal)
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self.u_set = self.Env.motions # feasible input set
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self.obs = self.Env.obs # position of obstacles
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self.OPEN = queue.QueueFIFO() # U set: visited nodes
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self.OPEN.put(self.s_start)
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self.CLOSED = [] # CLOSED set: explored nodes
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self.PARENT = {self.s_start: self.s_start}
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def searching(self):
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"""
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Breadth-first Searching.
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:return: path, visited order
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"""
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while self.OPEN:
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s = self.OPEN.get()
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if s == self.s_goal:
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break
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self.CLOSED.append(s)
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for s_n in self.get_neighbor(s):
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if s_n not in self.PARENT: # node not explored
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self.OPEN.put(s_n)
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self.PARENT[s_n] = s
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return self.extract_path(), self.CLOSED
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def get_neighbor(self, s):
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"""
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find neighbors of state s that not in obstacles.
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:param s: state
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:return: neighbors
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"""
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s_list = set()
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for u in self.u_set:
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s_next = tuple([s[i] + u[i] for i in range(2)])
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if s_next not in self.obs:
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s_list.add(s_next)
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return s_list
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def extract_path(self):
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"""
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Extract the path based on the PARENT set.
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:return: The planning path
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"""
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path = [self.s_goal]
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s = self.s_goal
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while True:
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s = self.PARENT[s]
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path.append(s)
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if s == self.s_start:
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break
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return list(path)
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def main():
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s_start = (5, 5)
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s_goal = (45, 25)
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bfs = BFS(s_start, s_goal)
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plot = plotting.Plotting(s_start, s_goal)
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path, visited = bfs.searching()
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plot.animation(path, visited, "Breadth-first Searching (BFS)")
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if __name__ == '__main__':
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main()
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