def __init__(self, s_start, s_goal, heuristic_type):
self.s_start, self.s_goal = s_start, s_goal
self.heuristic_type = heuristic_type
self.Env = env.Env() # class Env
self.Plot = plotting.Plotting(s_start, s_goal)
self.u_set = self.Env.motions # feasible input set
self.obs = self.Env.obs # position of obstacles
self.x = self.Env.x_range
self.y = self.Env.y_range
self.g, self.rhs, self.U = {}, {}, {}
self.km = 0
for i in range(1, self.Env.x_range - 1):
for j in range(1, self.Env.y_range - 1):
self.rhs[(i, j)] = float("inf")
self.g[(i, j)] = float("inf")
self.rhs[self.s_goal] = 0.0
self.U[self.s_goal] = self.CalculateKey(self.s_goal)
self.visited = set()
self.count = 0
self.fig = plt.figure()
def __init__(self, s_start, s_goal, heuristic_type):
self.s_start, self.s_goal = s_start, s_goal
self.heuristic_type = heuristic_type
self.Env = env.Env()
self.Plot = plotting.Plotting(self.s_start, self.s_goal)
self.u_set = self.Env.motions
self.obs = self.Env.obs
self.x = self.Env.x_range
self.y = self.Env.y_range
self.g, self.rhs, self.U = {}, {}, {}
for i in range(self.Env.x_range):
for j in range(self.Env.y_range):
self.rhs[(i, j)] = float("inf")
self.g[(i, j)] = float("inf")
self.rhs[self.s_start] = 0
self.U[self.s_start] = self.CalculateKey(self.s_start)
self.visited = set()
self.count = 0
self.fig = plt.figure()
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 = deque() # OPEN set: visited nodes
self.PARENT = dict() # recorded parent
self.CLOSED = [] # CLOSED set / visited order
def __init__(self, s_start, s_goal, N, heuristic_type):
self.s_start, self.s_goal = s_start, s_goal
self.heuristic_type = heuristic_type
self.Env = env.Env()
self.u_set = self.Env.motions # feasible input set
self.obs = self.Env.obs # position of obstacles
self.N = N # number of expand nodes each iteration
self.visited = [] # order of visited nodes in planning
self.path = [] # path of each iteration
self.h_table = {} # h_value table
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 __init__(self, s_start, s_goal, heuristic_type):
self.s_start = s_start
self.s_goal = s_goal
self.heuristic_type = heuristic_type
self.Env = env.Env() # class Env
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 order
self.PARENT = dict() # recorded parent
self.g = dict() # cost to come
def __init__(self, s_start, s_goal, e, heuristic_type):
self.s_start, self.s_goal = s_start, s_goal
self.heuristic_type = heuristic_type
self.Env = env.Env() # class Env
self.u_set = self.Env.motions # feasible input set
self.obs = self.Env.obs # position of obstacles
self.e = e # weight
self.g = dict() # Cost to come
self.OPEN = dict() # priority queue / OPEN set
self.CLOSED = set() # CLOSED set
self.INCONS = {} # INCONSISTENT set
self.PARENT = dict() # relations
self.path = [] # planning path
self.visited = [] # order of visited nodes
def __init__(self, s_start, s_goal, heuristic_type):
self.s_start = s_start
self.s_goal = s_goal
self.heuristic_type = heuristic_type
self.Env = env.Env() # class Env
self.u_set = self.Env.motions # feasible input set
self.obs = self.Env.obs # position of obstacles
self.OPEN_fore = [] # OPEN set for forward searching
self.OPEN_back = [] # OPEN set for backward searching
self.CLOSED_fore = [] # CLOSED set for forward
self.CLOSED_back = [] # CLOSED set for backward
self.PARENT_fore = dict() # recorded parent for forward
self.PARENT_back = dict() # recorded parent for backward
self.g_fore = dict() # cost to come for forward
self.g_back = dict() # cost to come for backward