def conflict_detection(owner, intruders):
conflict_UAV = []
antecedent = [None] * 3
for i in intruders:
temp_conflict = []
d = get_distance([owner[0], owner[1]], [i[0], i[1]])
if d < 24:
Relative_location = Get_Relative_Location([owner[0], owner[1]],
[i[0], i[1]], owner[3])
# print(Relative_location)
if Relative_location:
temp_conflict.append(Relative_location)
if temp_conflict:
conflict_UAV.append(temp_conflict)
if temp_conflict[0] == 'F':
if d < 6:
antecedent[1] = 'N'
elif d > 16:
antecedent[1] = 'F'
else:
antecedent[1] = 'M'
if temp_conflict[0] == 'R':
if d < 10:
antecedent[2] = 'N'
else:
antecedent[2] = 'M'
if temp_conflict[0] == 'L':
if d < 10:
antecedent[0] = 'N'
else:
antecedent[0] = 'M'
if conflict_UAV:
# print(conflict_UAV)
if antecedent[0] == None:
antecedent[0] = 'M'
if antecedent[1] == None:
antecedent[1] = 'F'
if antecedent[2] == None:
antecedent[2] = 'M'
# print(antecedent)
consequence = fuzzy_control(antecedent)
# print(consequence)
# print(defuzzificztion(consequence))
return defuzzificztion(consequence)[0], defuzzificztion(consequence)[1]
def main(P1, P2, P3, P4):
start = time.time()
used_time = 0
turtle.setup(700, 700, 600, 10)
# turtle.clear()
r1 = Robot(P1[0], P1[1], 'red')
r2 = Robot(P2[0], P2[1], 'blue')
r3 = Robot(P3[0], P3[1], 'green')
r4 = Robot(P4[0], P4[1], 'black')
robot_list = [r1, r2, r3, r4]
Tr = [[[] for i in range(2)] for j in range(len(robot_list))]
while True:
# calculate the detection params
detection_params = [[] for i in range(len(robot_list))]
for r in robot_list:
detection_params[robot_list.index(r)].append(
[r.location_x, r.location_y, r.velocity, r.heading])
temp = copy.copy(robot_list)
index = temp.index(r)
del temp[index]
intruders_temp = []
for j in temp:
intruders_temp.append(
[j.location_x, j.location_y, j.velocity, j.heading])
detection_params[robot_list.index(r)].append(intruders_temp)
target = 0
# target used to check if reach target position
for r in robot_list:
if get_distance([r.location_x, r.location_y],
[r.target_x, r.target_y]) < 20:
target = target + 1
else:
order = conflict_detection(
detection_params[robot_list.index(r)][0],
detection_params[robot_list.index(r)][1])
if order:
r.move_heading_velocity(order[0], order[1])
Tr[robot_list.index(r)][0].append(r.location_x)
Tr[robot_list.index(r)][1].append(r.location_y)
else:
r.move()
Tr[robot_list.index(r)][0].append(r.location_x)
Tr[robot_list.index(r)][1].append(r.location_y)
target = target + 0
if target == len(robot_list):
end = time.time()
time.sleep(5)
turtle.clearscreen()
excepted_legth = 0
real_legth = 0
for i in Tr:
temp = get_distance([i[0][0], i[1][0]], [i[0][-1], i[1][-1]])
excepted_legth = excepted_legth + temp
# print("期望距离：",excepted_legth)
for j in Tr:
for k in range(len(j[0]) - 1):
real_legth = real_legth + get_distance(
[j[0][k], j[1][k]], [j[0][k + 1], j[1][k + 1]])
# print("实际距离：",real_legth)
# print("路径度量",real_legth/excepted_legth)
Tra_metric = real_legth / excepted_legth
used_time = end - start
episode = []
for i in Tr:
episode.append(len(i[0]))
# print(episode)
# print("到达目标所需步骤：", episode)
# print("总共花费实际时间：", used_time)
# print("时间度量：", (used_time/max(episode))/4)
Time_metric = (used_time / max(episode)) / 4
mean_min_separation = []
for j in range(len(episode)):
for k in range(len(Tr)):
for m in range(k + 1, len(Tr)):
mean_min_separation.append(
get_distance([Tr[k][0][j], Tr[k][0][j]],
[Tr[m][0][j], Tr[m][1][j]]))
# print("最小间隔：", min(mean_min_separation)/2)
Sep_metric = min(mean_min_separation)
print("本次度量：", Sep_metric, Tra_metric, Time_metric, '\n')
return Sep_metric, Tra_metric, Time_metric