def generate_NBA():
start = datetime.datetime.now()
task = Task()
buchi = Buchi(task)
buchi.construct_buchi_graph()
buchi.get_minimal_length()
buchi.get_feasible_accepting_state()
buchi_graph = buchi.buchi_graph
NBA_time = (datetime.datetime.now() - start).total_seconds()
print('Time for constructing the NBA: {0:.4f} s'.format(NBA_time))
return buchi, buchi_graph
save_covariances = True
drone_height = 16.0 # altitude of drones
waypoint_folder_location = "/home/samarth/catkin_ws/src/rotors_simulator/rotors_gazebo/resource"
launch_folder_location = "/home/samarth/catkin_ws/src/rotors_simulator/rotors_gazebo/launch"
time_array = [] #stores time for each trial run
cost_array = [] #stores cost of each trial run
for round_num in range(number_of_trials):
print('Trial {}'.format(round_num + 1))
start = datetime.datetime.now()
task = Task()
buchi = Buchi(task)
buchi.construct_buchi_graph()
buchi.get_minimal_length()
buchi.get_feasible_accepting_state()
buchi_graph = buchi.buchi_graph
NBA_time = (datetime.datetime.now() - start).total_seconds()
print('Time for constructing the NBA: {0:.4f} s'.format(NBA_time))
# workspace
workspace = Workspace()
geodesic = Geodesic(workspace, task.threshold)
# parameters
n_max = 100000
para = dict()
# lite version, excluding extending and rewiring
para['is_lite'] = True
# step_size used in function near
para['step_size'] = 0.25 * buchi.number_of_robots
# probability of choosing node q_p_closest