mirror of
https://github.com/zhm-real/PathPlanning.git
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zhm-real
105 lines
3.0 KiB
Python
105 lines
3.0 KiB
Python
"""
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Dijkstra 2D
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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 Dijkstra:
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def __init__(self, x_start, x_goal):
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self.xI, self.xG = x_start, x_goal
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self.Env = env.Env()
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self.plotting = plotting.Plotting(self.xI, self.xG)
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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.g = {self.xI: 0, self.xG: float("inf")} # cost to come
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self.OPEN = queue.QueuePrior() # priority queue / OPEN set
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self.OPEN.put(self.xI, 0)
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self.CLOSED = [] # closed set & visited
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self.PARENT = {self.xI: self.xI} # relations
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def searching(self):
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"""
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Searching using Dijkstra.
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:return: path, order of visited nodes in the planning
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"""
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while not self.OPEN.empty():
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s = self.OPEN.get()
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if s == self.xG: # stop condition
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break
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self.CLOSED.append(s)
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for u in self.u_set: # explore neighborhoods
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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: # node not visited and not in obstacles
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new_cost = self.g[s] + self.get_cost(s, u)
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if s_next not in self.g:
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self.g[s_next] = float("inf")
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if new_cost < self.g[s_next]:
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self.g[s_next] = new_cost
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self.OPEN.put(s_next, new_cost)
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self.PARENT[s_next] = s
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return self.extract_path(), self.CLOSED
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def extract_path(self):
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"""
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Extract the path based on the relationship of nodes.
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:return: The planning path
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"""
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path_back = [self.xG]
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x_current = self.xG
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while True:
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x_current = self.PARENT[x_current]
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path_back.append(x_current)
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if x_current == self.xI:
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break
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return list(path_back)
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@staticmethod
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def get_cost(x, u):
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"""
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Calculate cost for this motion
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:param x: current node
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:param u: input
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:return: cost for this motion
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:note: cost function could be more complicate!
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"""
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return 1
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def main():
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x_start = (5, 5)
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x_goal = (45, 25)
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dijkstra = Dijkstra(x_start, x_goal)
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plot = plotting.Plotting(x_start, x_goal) # class Plotting
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fig_name = "Dijkstra's"
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path, visited = dijkstra.searching()
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plot.animation(path, visited, fig_name) # animation generate
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if __name__ == '__main__':
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main()
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