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)