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()
