122 lines
5.3 KiB
Python
122 lines
5.3 KiB
Python
from opt_bt_expansion.BehaviorTree import Leaf,ControlBT # 行为结点类：叶子结点和非叶子节点
|
|
from opt_bt_expansion.OptimalBTExpansionAlgorithm import Action,OptBTExpAlgorithm,state_transition # 调用最优行为树扩展算法
|
|
from opt_bt_expansion.tools import print_action_data_table,BTTest
|
|
from opt_bt_expansion.examples import MoveBtoB_num,MoveBtoB,Cond2BelongsToCond3 # 导入三个例子
|
|
from opt_bt_expansion.examples import *
|
|
|
|
|
|
# 封装好的主接口
|
|
class BTOptExpInterface:
|
|
def __init__(self, action_list):
|
|
"""
|
|
Initialize the BTOptExpansion with a list of actions.
|
|
:param action_list: A list of actions to be used in the behavior tree.
|
|
"""
|
|
# self.actions = []
|
|
# for act in action_list:
|
|
# a = Action(name=act.name)
|
|
# a.pre=act['pre']
|
|
# a.add=act['add']
|
|
# a.del_set= act['del_set']
|
|
# a.cost = 1
|
|
# self.actions.append(a)
|
|
self.actions = action_list
|
|
self.has_processed = False
|
|
|
|
def process(self, goal):
|
|
"""
|
|
Process the input sets and return a string result.
|
|
:param input_set: The set of goal states and the set of initial states.
|
|
:return: A PTML string representing the outcome of the behavior tree.
|
|
"""
|
|
self.goal = goal
|
|
self.algo = OptBTExpAlgorithm(verbose=False)
|
|
self.algo.clear()
|
|
self.algo.run_algorithm(self.goal, self.actions) # 调用算法得到行为树保存至 algo.bt
|
|
self.ptml_string = self.algo.get_ptml()
|
|
self.has_processed = True
|
|
# algo.print_solution() # print behavior tree
|
|
|
|
return self.ptml_string
|
|
|
|
# 方法一：查找所有初始状态是否包含当前状态
|
|
def find_all_leaf_states_contain_start(self,start):
|
|
if not self.has_processed:
|
|
raise RuntimeError("The process method must be called before find_all_leaf_states_contain_start!")
|
|
# 返回所有能到达目标状态的初始状态
|
|
state_leafs = self.algo.get_all_state_leafs()
|
|
for state in state_leafs:
|
|
if start >= state:
|
|
return True
|
|
return False
|
|
|
|
# 方法二：模拟跑一遍行为树，看 start 能够通过执行一系列动作到达 goal
|
|
def run_bt_from_start(self,goal,start):
|
|
if not self.has_processed:
|
|
raise RuntimeError("The process method must be called before run_bt_from_start!")
|
|
# 检查是否能到达目标
|
|
right_bt = True
|
|
state = start
|
|
steps = 0
|
|
val, obj = self.algo.bt.tick(state)
|
|
while val != 'success' and val != 'failure':
|
|
state = state_transition(state, obj)
|
|
val, obj = self.algo.bt.tick(state)
|
|
if (val == 'failure'):
|
|
# print("bt fails at step", steps)
|
|
right_bt = False
|
|
steps += 1
|
|
if not goal <= state:
|
|
# print("wrong solution", steps)
|
|
right_bt = False
|
|
else:
|
|
pass
|
|
# print("right solution", steps)
|
|
return right_bt
|
|
|
|
|
|
|
|
|
|
if __name__ == '__main__' :
|
|
|
|
# todo: Example Cafe
|
|
# todo: Define goal, start, actions
|
|
actions=[
|
|
Action(name='PutDown(Table,Coffee)', pre={'Holding(Coffee)','At(Robot,Table)'}, add={'At(Table,Coffee)','NotHolding'}, del_set={'Holding(Coffee)'}, cost=1),
|
|
Action(name='PutDown(Table,VacuumCup)', pre={'Holding(VacuumCup)','At(Robot,Table)'}, add={'At(Table,VacuumCup)','NotHolding'}, del_set={'Holding(VacuumCup)'}, cost=1),
|
|
|
|
Action(name='PickUp(Coffee)', pre={'NotHolding','At(Robot,Coffee)'}, add={'Holding(Coffee)'}, del_set={'NotHolding'}, cost=1),
|
|
|
|
Action(name='MoveTo(Table)', pre={'Available(Table)'}, add={'At(Robot,Table)'}, del_set={'At(Robot,FrontDesk)','At(Robot,Coffee)','At(Robot,CoffeeMachine)'}, cost=1),
|
|
Action(name='MoveTo(Coffee)', pre={'Available(Coffee)'}, add={'At(Robot,Coffee)'}, del_set={'At(Robot,FrontDesk)','At(Robot,Table)','At(Robot,CoffeeMachine)'}, cost=1),
|
|
Action(name='MoveTo(CoffeeMachine)', pre={'Available(CoffeeMachine)'}, add={'At(Robot,CoffeeMachine)'}, del_set={'At(Robot,FrontDesk)','At(Robot,Coffee)','At(Robot,Table)'}, cost=1),
|
|
|
|
Action(name='OpCoffeeMachine', pre={'At(Robot,CoffeeMachine)','NotHolding'}, add={'Available(Coffee)','At(Robot,Coffee)'}, del_set=set(), cost=1),
|
|
]
|
|
algo = BTOptExpInterface(actions)
|
|
|
|
|
|
goal = {'At(Table,Coffee)'}
|
|
ptml_string = algo.process(goal)
|
|
print(ptml_string)
|
|
|
|
file_name = "MakeCoffee"
|
|
with open(f'./{file_name}.ptml', 'w') as file:
|
|
file.write(ptml_string)
|
|
|
|
|
|
# 判断初始状态能否到达目标状态
|
|
start = {'At(Robot,Bar)', 'Holding(VacuumCup)', 'Available(Table)', 'Available(CoffeeMachine)','Available(FrontDesk)'}
|
|
# 方法一：算法返回所有可能的初始状态，在里面看看有没有对应的初始状态
|
|
right_bt = algo.find_all_leaf_states_contain_start(start)
|
|
if not right_bt:
|
|
print("ERROR1: The current state cannot reach the goal state!")
|
|
else:
|
|
print("Right1: The current state can reach the goal state!")
|
|
# 方法二：预先跑一边行为树，看能否到达目标状态
|
|
right_bt2 = algo.run_bt_from_start(goal,start)
|
|
if not right_bt2:
|
|
print("ERROR2: The current state cannot reach the goal state!")
|
|
else:
|
|
print("Right2: The current state can reach the goal state!")
|