""" DFS 2D @author: huiming zhou """ import os import sys sys.path.append(os.path.dirname(os.path.abspath(__file__)) + "/../../Search-based Planning/") from Search_2D import queue from Search_2D import plotting from Search_2D import env class DFS: def __init__(self, x_start, x_goal): self.xI, self.xG = x_start, x_goal self.Env = env.Env() self.plotting = plotting.Plotting(self.xI, self.xG) self.u_set = self.Env.motions # feasible input set self.obs = self.Env.obs # position of obstacles self.OPEN = queue.QueueLIFO() # OPEN set: visited nodes self.OPEN.put(self.xI) self.CLOSED = [] # CLOSED set: explored nodes self.PARENT = {self.xI: self.xI} # relations def searching(self): """ Searching using DFS. :return: planning path, action in each node, visited nodes in the planning process """ while not self.OPEN.empty(): s = self.OPEN.get() if s == self.xG: break self.CLOSED.append(s) for u in self.u_set: # explore neighborhoods s_next = tuple([s[i] + u[i] for i in range(2)]) if s_next not in self.PARENT and s_next not in self.obs: # node not visited and not in obstacles self.OPEN.put(s_next) self.PARENT[s_next] = s return self.extract_path(), self.CLOSED def extract_path(self): """ Extract the path based on the relationship of nodes. :return: The planning path """ path = [self.xG] s = self.xG while True: s = self.PARENT[s] path.append(s) if s == self.xI: break return list(path) def main(): x_start = (5, 5) x_goal = (45, 25) dfs = DFS(x_start, x_goal) plot = plotting.Plotting(x_start, x_goal) fig_name = "Depth-first Searching (DFS)" path, visited = dfs.searching() plot.animation(path, visited, fig_name) # animation if __name__ == '__main__': main()