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
# plot_workspace(workspace)
# plt.show()
with open('data/workspace', 'wb') as filehandle:
pickle.dump(workspace, filehandle)
# with open('data/workspace', 'rb') as filehandle:
# workspace.p2p = pickle.load(filehandle)
# workspace.plot_workspace()
# plt.show()
start = datetime.now()
task = Task()
buchi = Buchi(task, workspace)
buchi.construct_buchi_graph()
print((datetime.now()-start).total_seconds())
# print('partial time: {0}'.format((datetime.now() - start).total_seconds()))
print(buchi.buchi_graph.number_of_nodes(), buchi.buchi_graph.number_of_edges())
init_state, accept_state, is_nonempty_self_loop = buchi.get_init_accept()
# is_nonempty_self_loop = False
pruned_subgraph, paths = buchi.get_subgraph(init_state, accept_state, is_nonempty_self_loop)
print(pruned_subgraph.number_of_nodes(), pruned_subgraph.number_of_edges())
identity = 'run1'
number_of_trials = 1
save_waypoints = True
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
# -*- coding: utf-8 -*-
import numpy as np
import math
from shapely.geometry import Point, LineString, shape
from shapely.ops import nearest_points
from buchi_parse import Buchi
from workspace import Workspace
from task import Task
workspace = Workspace()
task = Task()
buchi = Buchi(task)
obstacles = workspace.obs
def calculate_STL_cost(new_state, neighbor_state):
(minVal, mobs, maxVal,
Mobs) = max_min_distances_to_obs(new_state, neighbor_state)
# min distance
if mobs == 'o1':
qsi_min = minVal - 0.1 # robot has to be at least 0.3m away from obstacles
elif mobs == 'o2':
qsi_min = minVal - 0.1
""" # max distance
if Mobs=='o1':
qsi_max=0.5-maxVal # robot has to be less than 0.5m away from obstacles
elif Mobs=='o2':