def __init__(self, s_start, s_goal, eps, 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.OPEN = {}, {}, {} 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.eps = eps self.OPEN[self.s_goal] = self.Key(self.s_goal) self.CLOSED, self.INCONS = set(), dict() self.visited = set() self.count = 0 self.count_env_change = 0 self.obs_add = set() self.obs_remove = set() self.title = "Anytime D*: Small changes" # Significant changes self.fig = plt.figure()
def __init__(self, s_start, s_goal): self.s_start, self.s_goal = s_start, s_goal 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.fig = plt.figure() self.OPEN = set() self.t = {} self.PARENT = {} self.h = {} self.k = {} self.path = [] self.visited = set() self.count = 0 for i in range(self.Env.x_range): for j in range(self.Env.y_range): self.t[(i, j)] = 'NEW' self.k[(i, j)] = 0.0 self.h[(i, j)] = float("inf") self.PARENT[(i, j)] = None self.h[self.s_goal] = 0.0
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.u_set = self.Env.motions # feasible input set self.obs = self.Env.obs # position of obstacles self.g_fore = { self.s_start: 0, self.s_goal: float("inf") } # cost to come: from s_start self.g_back = { self.s_goal: 0, self.s_start: float("inf") } # cost to come: form s_goal self.OPEN_fore = queue.QueuePrior() # OPEN set for foreward searching self.OPEN_fore.put( self.s_start, self.g_fore[self.s_start] + self.h(self.s_start, self.s_goal)) self.OPEN_back = queue.QueuePrior() # OPEN set for backward searching self.OPEN_back.put( self.s_goal, self.g_back[self.s_goal] + self.h(self.s_goal, self.s_start)) self.CLOSED_fore = [] # CLOSED set for foreward self.CLOSED_back = [] # CLOSED set for backward self.PARENT_fore = {self.s_start: self.s_start} self.PARENT_back = {self.s_goal: self.s_goal}
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, 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.OPEN = {}, {}, {} self.parent = {} self.cknbr = {} self.ccknbr = {} self.bptr = {} self.init_table() 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.bptr[(i, j)] = (i, j) self.rhs[self.s_goal] = 0.0 self.OPEN[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): self.s_start, self.s_goal = s_start, 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 = queue.QueuePrior() # OPEN set self.OPEN.put(self.s_start, self.Heuristic(self.s_start)) self.CLOSED = [] # CLOSED set / visited order self.PARENT = {self.s_start: self.s_start}
def __init__(self, s_start, s_goal): self.s_start, self.s_goal = s_start, 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 = queue.QueueFIFO() # OPEN set: visited nodes self.OPEN.put(self.s_start) self.CLOSED = [] # CLOSED set: explored nodes self.PARENT = {self.s_start: self.s_start}
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, 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): self.s_start, self.s_goal = s_start, 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.g = {self.s_start: 0, self.s_goal: float("inf")} # cost to come self.OPEN = queue.QueuePrior() # priority queue / OPEN set self.OPEN.put(self.s_start, 0) self.CLOSED = [] # closed set & visited self.PARENT = {self.s_start: self.s_start}
def __init__(self, start, goal, heuristic_type): self.s_start, self.s_goal = start, 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.g = {self.s_start: 0, self.s_goal: float("inf")} # cost to come self.OPEN = queue.QueuePrior() # priority queue / OPEN set self.OPEN.put(self.s_start, self.fvalue(self.s_start)) self.CLOSED = [] # CLOSED set / VISITED order self.PARENT = {self.s_start: self.s_start}
def __init__(self, s_start, s_goal): self.s_start = s_start self.s_goal = s_goal self.kp = 5.0 self.eta = 400 self.r = 30.0 self.OL = 10 self.rr = 2 self.Env = env.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
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 # initial weight self.g = {self.s_start: 0, self.s_goal: float("inf")} # cost to come self.OPEN = {self.s_start: self.fvalue(self.s_start)} # priority queue / OPEN set self.CLOSED = set() # CLOSED set self.INCONS = {} # INCONS set self.PARENT = {self.s_start: self.s_start} # relations self.path = [] # planning path self.visited = [] # order of visited nodes
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
def __init__(self, s_start, s_goal): self.s_start, self.s_goal = s_start, s_goal 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.fig = plt.figure() self.OPEN = set() self.t = dict() self.PARENT = dict() self.h = dict() self.k = dict() self.path = [] self.visited = set() self.count = 0
def __init__(self, problemFile): self.env = env.Env(problemFile) self.xI = self.env.xI self.xG = self.env.xG self.obs = self.env.obs
def __init__(self, xI, xG): self.xI, self.xG = xI, xG self.env = env.Env() self.obs = self.env.obs_map()