def __init__(self):
rospy.init_node('robot', anonymous=True)
self.astarPublisher = rospy.Publisher("/results/path_list",
AStarPath,
queue_size=15)
self.simComplete = rospy.Publisher("/map_node/sim_complete",
Bool,
queue_size=15)
self.mdpPublisher = rospy.Publisher("/results/policy_list",
PolicyList,
queue_size=15)
rospy.sleep(0.1)
#self.config = read_config()
self.move_list = astar.run_astar()
for elem in self.move_list:
#print AStarPath(elem).data
rospy.sleep(0.1)
self.astarPublisher.publish(AStarPath(elem).data)
rospy.sleep(0.1)
self.map_list = mdp.run_mdp()
rospy.sleep(0.1)
self.mdpPublisher.publish(self.map_list)
rospy.sleep(0.1)
self.simComplete.publish(True)
rospy.sleep(0.1)
rospy.signal_shutdown(0)
def __init__ (self):
rospy.init_node('robot', anonymous = True)
self.astarPublisher = rospy.Publisher("/results/path_list", AStarPath, queue_size = 15)
self.simComplete = rospy.Publisher("/map_node/sim_complete", Bool, queue_size = 15)
self.mdpPublisher = rospy.Publisher("/results/policy_list", PolicyList, queue_size= 15)
rospy.sleep(0.1)
#self.config = read_config()
self.move_list = astar.run_astar()
for elem in self.move_list:
#print AStarPath(elem).data
rospy.sleep(0.1)
self.astarPublisher.publish(AStarPath(elem).data)
rospy.sleep(0.1)
self.map_list= mdp.run_mdp()
rospy.sleep(0.1)
self.mdpPublisher.publish(self.map_list)
rospy.sleep(0.1)
self.simComplete.publish(True)
rospy.sleep(0.1)
rospy.signal_shutdown(0)
board_names = ["level 1"] + ["level " + str(i) for i in range(15,41)]
boards = [level_1, level_15, level_16, level_17, level_18, level_19, level_20,
level_21, level_22, level_23, level_24, level_25, level_26,
level_27, level_28, level_29, level_30, level_31, level_32,
level_33, level_34, level_35, level_36, level_37, level_38,
level_39, level_40]
bfs_pops = 0
manhattan_distance_pops = 0
free_moves_to_center_pops = 0
free_moves2_pops = 0
free_moves3_pops = 0
for i in xrange(len(boards)):
board = boards[i]
name = board_names[i]
print("solving board " + name)
bfs_pops += run_bfs(board, name)
manhattan_distance_pops += run_astar(board, heuristics.manhattan_distance, name)
free_moves_to_center_pops += run_astar(board, heuristics.free_moves_to_center, name)
free_moves2_pops += run_astar(board, heuristics.free_moves2, name)
free_moves3_pops += run_astar(board, heuristics.free_moves3, name)
n = len(board_names)
print("bfs average: " + str(bfs_pops / n))
print("manhattan average: " + str(manhattan_distance_pops / n))
print("free moves to center average: " + str(free_moves_to_center_pops / n))
print("free moves 2 average: " + str(free_moves2_pops / n))
print("free moves 3 average: " + str(free_moves3_pops / n))
def find_astar_route(source, target, roads):
return run_astar(source, target, roads)
def simple(source, target, start_time):
'call function to find path, and return list of indices'
return run_astar(source, target, start_time)
