def find_best_vehicle_linetask(line_tasks):
# While there are free vehicles and undistributed tasks
v_best = None #vehicle
l_best = None #line
d_best = None
swap = None
# Find the shortes distance between a free vehicle and an undistributed task
for vehicle in free_vehicles:
for line in line_task:
d_s = Drone_Services.distance(vehicle.location.global_frame,
line[0])
d_e = Drone_Services.distance(vehicle.location.global_frame,
line[1])
d = min(d_e, d_s)
if (d_best == None) or (d < d_best):
d_best = d
v_best = vehicle
l_best = line
swap = (d_e < d_s)
if d_best == None:
raise RuntimeError(
"Unexpected Error in distribute tasks: if there are tasks then there should be an optimal one"
)
return ["line", v_best, l_best, d_best, swap]
def main():
Drone_Services.initialize(vehicles, UAV_BASE_PORT, server)
server.set_fn_message_received(message_received)
# Start web interface
with server:
while True:
free_vehicles.clear()
# For each vehicle
for vehicle in vehicles:
# If the vehicle does not have a next task, add it to free vehicles
if not vehicle.nextlocations:
free_vehicles.append(vehicle)
# Else if next task is reached remove it from the vehicles's task lis
elif Drone_Services.distance(
vehicle.nextlocations[0],
vehicle.location.global_frame) < 0.001:
vehicle.nextlocations.pop(0)
# If the vehicle has more tasks, start the next
if vehicle.nextlocations:
vehicle.simple_goto(vehicle.nextlocations[0])
# Else add it to free vehicles
else:
free_vehicles.append(vehicle)
# Distribute new tasks
distribute_tasks(free_vehicles)
time.sleep(1)
def distribute_taskssss(free_vehicles, line_task):
# While there are free vehicles and undistributed tasks
while free_vehicles and line_task:
v_best = None #vehicle
l_best = None #line
d_best = None
swap = None
# Find the shortes distance between a free vehicle and an undistributed task
for vehicle in free_vehicles:
for line in line_task:
d_s = Drone_Services.distance(vehicle.location.global_frame,
line[0])
d_e = Drone_Services.distance(vehicle.location.global_frame,
line[1])
d = min(d_e, d_s)
if (d_best == None) or (d < d_best):
d_best = d
v_best = vehicle
l_best = line
swap = (d_e < d_s)
if d_best == None:
raise RuntimeError(
"Unexpected Error in distribute tasks: if there are tasks then there should be an optimal one"
)
# Remove the vehicle from free vehicles and remove the task from undistributed tasks
free_vehicles.remove(v_best)
line_task.remove(l_best)
# Swap the line start and end position if the end position is closest
if swap:
l_best = reversed(l_best)
# Add task to the vehicle's task list and start the task
v_best.nextlocations.extend(l_best)
v_best.simple_goto(v_best.nextlocations[0])
def find_best_vehicle_polytask(poly_tasks):
v_best = None #vehicle
l_best = None #line
p_best = None #polygon
d_best = None
swap = None
for vehicle in free_vehicles:
for polygon in poly_tasks:
for line in polygon:
d_s = Drone_Services.distance(vehicle.location.global_frame,
line[0])
d_e = Drone_Services.distance(vehicle.location.global_frame,
line[1])
d = min(d_e, d_s)
if (d_best == None) or (d < d_best):
d_best = d
v_best = vehicle
p_best = polygon
l_best = line
swap = (d_e < d_s)
if swap:
l_best = reversed(l_best)
return ["poly", v_best, l_best, d_best, swap]