现在ptml可以解析string类型参数
This commit is contained in:
ChenXL97
parent
4fcb3c0bf6
commit
3aaab6c308
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@ -1 +0,0 @@
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{pre: 1, 2, 3}{action: moveTo(s)}{add: 4}{del: 2, 3}
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@ -6,3 +6,4 @@ gym==0.21.0
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grpcio==1.53.0
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requests
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urllib3
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tabulate
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from robowaiter.behavior_lib._base.Behavior import Bahavior
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class Act(Bahavior):
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def __init__(self,*args):
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super().__init__(*args)
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def get_conds(self):
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pre = set()
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add = set()
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de = set()
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return pre, add, de
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@ -0,0 +1,54 @@
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import py_trees as ptree
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from typing import Any
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import enum
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class Status(enum.Enum):
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"""An enumerator representing the status of a behavior."""
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SUCCESS = ptree.common.Status.SUCCESS
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"""Behaviour check has passed, or execution of its action has finished with a successful result."""
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FAILURE = ptree.common.Status.FAILURE
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"""Behaviour check has failed, or execution of its action finished with a failed result."""
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RUNNING = ptree.common.Status.RUNNING
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"""Behaviour is in the middle of executing some action, result still pending."""
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INVALID = ptree.common.Status.INVALID
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"""Behaviour is uninitialised and/or in an inactive state, i.e. not currently being ticked."""
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# _base Behavior
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class Bahavior(ptree.behaviour.Behaviour):
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num_params = 0
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valid_params='''
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None
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'''
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scene = None
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def __init__(self,*args):
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name = self.__class__.__name__
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if len(args)>0:
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name = f'{name}({",".join(list(args))})'
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self.name = name
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self.args = args
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super().__init__(self.name)
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def _update(self) -> ptree.common.Status:
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print("this is just a _base behavior node.")
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return Status.INVALID
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# let behavior node interact with the scene
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def set_scene(self, scene):
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self.scene = scene
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def setup(self, **kwargs: Any) -> None:
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return super().setup(**kwargs)
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def initialise(self) -> None:
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return super().initialise()
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def update(self) -> Status:
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re = self._update()
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print(f"{self.__class__.__name__}: {re.value}")
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return re
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def terminate(self, new_status: Status) -> None:
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return super().terminate(new_status)
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import py_trees as ptree
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from typing import Any
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from robowaiter.behavior_lib._base.Behavior import Bahavior, Status
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class Cond(Bahavior):
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def __init__(self):
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super().__init__()
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def _update(self) -> ptree.common.Status:
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# if self.scene.status?
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if self.scene.state['chat_list'] == []:
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return Status.FAILURE
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else:
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return Status.SUCCESS
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import py_trees as ptree
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from typing import Any
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from robowaiter.behavior_lib._base.Behavior import Bahavior
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from robowaiter.llm_client.ask_llm import ask_llm
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class DealChat(Bahavior):
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def __init__(self):
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super().__init__()
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def _update(self) -> ptree.common.Status:
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# if self.scene.status?
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chat = self.scene.state['chat_list'].pop()
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answer = ask_llm(chat)
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print(f"机器人回答：{answer}")
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self.scene.chat_bubble(f"机器人回答：{answer}")
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return ptree.common.Status.RUNNING
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import py_trees as ptree
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from typing import Any
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from robowaiter.behavior_lib._base.Act import Act
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class At(Act):
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num_params = 2
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valid_params = '''
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Coffee, Table
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'''
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def __init__(self,*args):
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super().__init__(*args)
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def _update(self) -> ptree.common.Status:
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# if self.scene.status?
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if self.scene.state['chat_list'] == []:
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return ptree.common.Status.FAILURE
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else:
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return ptree.common.Status.SUCCESS
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import py_trees as ptree
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from typing import Any
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from robowaiter.behavior_lib._base.Behavior import Bahavior
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class Chatting(Bahavior):
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def __init__(self):
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super().__init__()
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def _update(self) -> ptree.common.Status:
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# if self.scene.status?
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if self.scene.state['chat_list'] == []:
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return ptree.common.Status.FAILURE
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else:
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return ptree.common.Status.SUCCESS
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@ -0,0 +1,59 @@
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selector{
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cond At(Table,Coffee)
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selector{
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cond Holding(Coffee), At(Robot,Table)
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act PutDown(Table,Coffee)
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}
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selector{
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cond NotHolding, At(Robot,Coffee), At(Robot,Table)
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act PickUp(Coffee)
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}
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selector{
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cond Holding(Coffee), Available(Table)
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act MoveTo(Table)
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}
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selector{
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cond Holding(VacuumCup), At(Robot,Coffee), At(Robot,Table)
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act PutDown(Table,VacuumCup)
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}
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selector{
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cond NotHolding, At(Robot,CoffeeMachine), At(Robot,Table)
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act OpCoffeeMachine
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}
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selector{
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cond NotHolding, Available(Table), At(Robot,Coffee)
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act PickUp(Coffee)
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}
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selector{
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cond Holding(VacuumCup), At(Robot,Table), At(Robot,CoffeeMachine)
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act PutDown(Table,VacuumCup)
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}
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selector{
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cond NotHolding, Available(Coffee), Available(Table)
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act MoveTo(Coffee)
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}
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selector{
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cond NotHolding, Available(Table), At(Robot,CoffeeMachine)
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act OpCoffeeMachine
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}
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selector{
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cond Holding(VacuumCup), Available(Coffee), Available(Table), At(Robot,Table)
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act PutDown(Table,VacuumCup)
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}
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selector{
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cond Available(CoffeeMachine), NotHolding, Available(Table)
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act MoveTo(CoffeeMachine)
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}
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selector{
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cond Holding(VacuumCup), Available(Coffee), Available(Table)
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act MoveTo(Table)
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}
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selector{
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cond Available(CoffeeMachine), Holding(VacuumCup), Available(Table), At(Robot,Table)
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act PutDown(Table,VacuumCup)
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}
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selector{
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cond Available(CoffeeMachine), Holding(VacuumCup), Available(Table)
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act MoveTo(Table)
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}
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}
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Before Width: | Height: | Size: 54 KiB After Width: | Height: | Size: 54 KiB |
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@ -0,0 +1,3 @@
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from robowaiter.robot.robot import Robot
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from robowaiter.scene import task_map
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@ -1,5 +1,5 @@
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from opt_bt_expansion.OptimalBTExpansionAlgorithm import Action
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from zoo.opt_bt_expansion.OptimalBTExpansionAlgorithm import Action
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from robowaiter.behavior_tree.obtea.BehaviorTree import Leaf,ControlBT # 行为结点类：叶子结点和非叶子节点
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from zoo.opt_bt_expansion.OptimalBTExpansionAlgorithm import Action,OptBTExpAlgorithm,state_transition # 调用最优行为树扩展算法
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from robowaiter.behavior_tree.obtea.tools import print_action_data_table,BTTest
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from robowaiter.behavior_tree.obtea.examples import MoveBtoB_num,MoveBtoB,Cond2BelongsToCond3 # 导入三个例子
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from robowaiter.behavior_tree.obtea.examples import *
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# 封装好的主接口
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class BTOptExpInterface:
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def __init__(self, action_list):
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"""
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Initialize the BTOptExpansion with a list of actions.
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:param action_list: A list of actions to be used in the behavior tree.
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"""
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# self.actions = []
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# for act in action_list:
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# a = Action(name=act.name)
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# a.pre=act['pre']
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# a.add=act['add']
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# a.del_set= act['del_set']
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# a.cost = 1
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# self.actions.append(a)
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self.actions = action_list
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self.has_processed = False
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def process(self, goal):
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"""
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Process the input sets and return a string result.
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:param input_set: The set of goal states and the set of initial states.
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:return: A PTML string representing the outcome of the behavior tree.
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"""
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self.goal = goal
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self.algo = OptBTExpAlgorithm(verbose=False)
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self.algo.clear()
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self.algo.run_algorithm(self.goal, self.actions) # 调用算法得到行为树保存至 algo.bt
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self.ptml_string = self.algo.get_ptml()
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self.has_processed = True
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# algo.print_solution() # print behavior tree
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return self.ptml_string
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# 方法一：查找所有初始状态是否包含当前状态
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def find_all_leaf_states_contain_start(self,start):
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if not self.has_processed:
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raise RuntimeError("The process method must be called before find_all_leaf_states_contain_start!")
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# 返回所有能到达目标状态的初始状态
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state_leafs = self.algo.get_all_state_leafs()
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for state in state_leafs:
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if start >= state:
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return True
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return False
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# 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
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def run_bt_from_start(self,goal,start):
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if not self.has_processed:
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raise RuntimeError("The process method must be called before run_bt_from_start!")
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# 检查是否能到达目标
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right_bt = True
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state = start
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steps = 0
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val, obj = self.algo.bt.tick(state)
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while val != 'success' and val != 'failure':
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state = state_transition(state, obj)
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val, obj = self.algo.bt.tick(state)
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if (val == 'failure'):
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# print("bt fails at step", steps)
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right_bt = False
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steps += 1
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if not goal <= state:
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# print("wrong solution", steps)
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right_bt = False
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else:
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pass
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# print("right solution", steps)
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return right_bt
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if __name__ == '__main__' :
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# todo: Example Cafe
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# todo: Define goal, start, actions
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actions=[
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Action(name='PutDown(Table,Coffee)', pre={'Holding(Coffee)','At(Robot,Table)'}, add={'At(Table,Coffee)','NotHolding'}, del_set={'Holding(Coffee)'}, cost=1),
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Action(name='PutDown(Table,VacuumCup)', pre={'Holding(VacuumCup)','At(Robot,Table)'}, add={'At(Table,VacuumCup)','NotHolding'}, del_set={'Holding(VacuumCup)'}, cost=1),
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Action(name='PickUp(Coffee)', pre={'NotHolding','At(Robot,Coffee)'}, add={'Holding(Coffee)'}, del_set={'NotHolding'}, cost=1),
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Action(name='MoveTo(Table)', pre={'Available(Table)'}, add={'At(Robot,Table)'}, del_set={'At(Robot,FrontDesk)','At(Robot,Coffee)','At(Robot,CoffeeMachine)'}, cost=1),
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Action(name='MoveTo(Coffee)', pre={'Available(Coffee)'}, add={'At(Robot,Coffee)'}, del_set={'At(Robot,FrontDesk)','At(Robot,Table)','At(Robot,CoffeeMachine)'}, cost=1),
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Action(name='MoveTo(CoffeeMachine)', pre={'Available(CoffeeMachine)'}, add={'At(Robot,CoffeeMachine)'}, del_set={'At(Robot,FrontDesk)','At(Robot,Coffee)','At(Robot,Table)'}, cost=1),
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Action(name='OpCoffeeMachine', pre={'At(Robot,CoffeeMachine)','NotHolding'}, add={'Available(Coffee)','At(Robot,Coffee)'}, del_set=set(), cost=1),
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]
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algo = BTOptExpInterface(actions)
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goal = {'At(Table,Coffee)'}
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ptml_string = algo.process(goal)
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print(ptml_string)
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file_name = "MakeCoffee"
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with open(f'./{file_name}.ptml', 'w') as file:
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file.write(ptml_string)
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# 判断初始状态能否到达目标状态
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start = {'At(Robot,Bar)', 'Holding(VacuumCup)', 'Available(Table)', 'Available(CoffeeMachine)','Available(FrontDesk)'}
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# 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
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right_bt = algo.find_all_leaf_states_contain_start(start)
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if not right_bt:
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print("ERROR1: The current state cannot reach the goal state!")
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else:
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print("Right1: The current state can reach the goal state!")
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# 方法二：预先跑一边行为树，看能否到达目标状态
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right_bt2 = algo.run_bt_from_start(goal,start)
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if not right_bt2:
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print("ERROR2: The current state cannot reach the goal state!")
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else:
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print("Right2: The current state can reach the goal state!")
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from tabulate import tabulate
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import numpy as np
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import random
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from opt_bt_expansion.OptimalBTExpansionAlgorithm import Action,OptBTExpAlgorithm
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from zoo.opt_bt_expansion.OptimalBTExpansionAlgorithm import Action,OptBTExpAlgorithm
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import time
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cd ./robowaiter/behavior_tree/ptml
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antlr4 -Dlanguage=Python3 ptml.g4
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@ -4,13 +4,13 @@ root : tree+ EOF;
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tree : internal_node '{' (action_sign|tree)+ '}' ;
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internal_node : 'sequence' | 'selector' | 'parallel' Integer ;
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action_sign : ('task'|'cond') Names '(' action_parm? ')';
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action_parm : (Integer|Float|boolean) (',' (Integer|Float|boolean))* ;
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action_sign : ('act'|'cond') String '(' action_parm? ')';
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action_parm : (Integer|Float|boolean|String) (',' (Integer|Float|boolean|String))* ;
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// var_decls : var_type Names ;
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// var_type : 'int' | 'float' | 'bool' | 'string' ;
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boolean : 'True' | 'False' ;
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Names : [a-zA-Z_][a-zA-Z_0-9]* ;
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String : [a-zA-Z_][a-zA-Z_0-9]* ;
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Integer : '-'?[1-9][0-9]* | '0' ;
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Float : [0-9]+'.'[0-9]* | '.'[0-9]+ ;
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@ -5,7 +5,7 @@ null
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'sequence'
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'selector'
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'parallel'
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'task'
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'act'
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'cond'
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'('
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')'
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@ -32,7 +32,7 @@ null
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null
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null
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null
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Names
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String
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Integer
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Float
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LINE_COMMENT
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@ -48,4 +48,4 @@ boolean
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atn:
|
||||
[4, 1, 17, 62, 2, 0, 7, 0, 2, 1, 7, 1, 2, 2, 7, 2, 2, 3, 7, 3, 2, 4, 7, 4, 2, 5, 7, 5, 1, 0, 4, 0, 14, 8, 0, 11, 0, 12, 0, 15, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 24, 8, 1, 11, 1, 12, 1, 25, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 3, 2, 34, 8, 2, 1, 3, 1, 3, 1, 3, 1, 3, 3, 3, 40, 8, 3, 1, 3, 1, 3, 1, 4, 1, 4, 1, 4, 3, 4, 47, 8, 4, 1, 4, 1, 4, 1, 4, 1, 4, 3, 4, 53, 8, 4, 5, 4, 55, 8, 4, 10, 4, 12, 4, 58, 9, 4, 1, 5, 1, 5, 1, 5, 0, 0, 6, 0, 2, 4, 6, 8, 10, 0, 2, 1, 0, 6, 7, 1, 0, 11, 12, 66, 0, 13, 1, 0, 0, 0, 2, 19, 1, 0, 0, 0, 4, 33, 1, 0, 0, 0, 6, 35, 1, 0, 0, 0, 8, 46, 1, 0, 0, 0, 10, 59, 1, 0, 0, 0, 12, 14, 3, 2, 1, 0, 13, 12, 1, 0, 0, 0, 14, 15, 1, 0, 0, 0, 15, 13, 1, 0, 0, 0, 15, 16, 1, 0, 0, 0, 16, 17, 1, 0, 0, 0, 17, 18, 5, 0, 0, 1, 18, 1, 1, 0, 0, 0, 19, 20, 3, 4, 2, 0, 20, 23, 5, 1, 0, 0, 21, 24, 3, 6, 3, 0, 22, 24, 3, 2, 1, 0, 23, 21, 1, 0, 0, 0, 23, 22, 1, 0, 0, 0, 24, 25, 1, 0, 0, 0, 25, 23, 1, 0, 0, 0, 25, 26, 1, 0, 0, 0, 26, 27, 1, 0, 0, 0, 27, 28, 5, 2, 0, 0, 28, 3, 1, 0, 0, 0, 29, 34, 5, 3, 0, 0, 30, 34, 5, 4, 0, 0, 31, 32, 5, 5, 0, 0, 32, 34, 5, 14, 0, 0, 33, 29, 1, 0, 0, 0, 33, 30, 1, 0, 0, 0, 33, 31, 1, 0, 0, 0, 34, 5, 1, 0, 0, 0, 35, 36, 7, 0, 0, 0, 36, 37, 5, 13, 0, 0, 37, 39, 5, 8, 0, 0, 38, 40, 3, 8, 4, 0, 39, 38, 1, 0, 0, 0, 39, 40, 1, 0, 0, 0, 40, 41, 1, 0, 0, 0, 41, 42, 5, 9, 0, 0, 42, 7, 1, 0, 0, 0, 43, 47, 5, 14, 0, 0, 44, 47, 5, 15, 0, 0, 45, 47, 3, 10, 5, 0, 46, 43, 1, 0, 0, 0, 46, 44, 1, 0, 0, 0, 46, 45, 1, 0, 0, 0, 47, 56, 1, 0, 0, 0, 48, 52, 5, 10, 0, 0, 49, 53, 5, 14, 0, 0, 50, 53, 5, 15, 0, 0, 51, 53, 3, 10, 5, 0, 52, 49, 1, 0, 0, 0, 52, 50, 1, 0, 0, 0, 52, 51, 1, 0, 0, 0, 53, 55, 1, 0, 0, 0, 54, 48, 1, 0, 0, 0, 55, 58, 1, 0, 0, 0, 56, 54, 1, 0, 0, 0, 56, 57, 1, 0, 0, 0, 57, 9, 1, 0, 0, 0, 58, 56, 1, 0, 0, 0, 59, 60, 7, 1, 0, 0, 60, 11, 1, 0, 0, 0, 8, 15, 23, 25, 33, 39, 46, 52, 56]
|
||||
[4, 1, 17, 64, 2, 0, 7, 0, 2, 1, 7, 1, 2, 2, 7, 2, 2, 3, 7, 3, 2, 4, 7, 4, 2, 5, 7, 5, 1, 0, 4, 0, 14, 8, 0, 11, 0, 12, 0, 15, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 24, 8, 1, 11, 1, 12, 1, 25, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 3, 2, 34, 8, 2, 1, 3, 1, 3, 1, 3, 1, 3, 3, 3, 40, 8, 3, 1, 3, 1, 3, 1, 4, 1, 4, 1, 4, 1, 4, 3, 4, 48, 8, 4, 1, 4, 1, 4, 1, 4, 1, 4, 1, 4, 3, 4, 55, 8, 4, 5, 4, 57, 8, 4, 10, 4, 12, 4, 60, 9, 4, 1, 5, 1, 5, 1, 5, 0, 0, 6, 0, 2, 4, 6, 8, 10, 0, 2, 1, 0, 6, 7, 1, 0, 11, 12, 70, 0, 13, 1, 0, 0, 0, 2, 19, 1, 0, 0, 0, 4, 33, 1, 0, 0, 0, 6, 35, 1, 0, 0, 0, 8, 47, 1, 0, 0, 0, 10, 61, 1, 0, 0, 0, 12, 14, 3, 2, 1, 0, 13, 12, 1, 0, 0, 0, 14, 15, 1, 0, 0, 0, 15, 13, 1, 0, 0, 0, 15, 16, 1, 0, 0, 0, 16, 17, 1, 0, 0, 0, 17, 18, 5, 0, 0, 1, 18, 1, 1, 0, 0, 0, 19, 20, 3, 4, 2, 0, 20, 23, 5, 1, 0, 0, 21, 24, 3, 6, 3, 0, 22, 24, 3, 2, 1, 0, 23, 21, 1, 0, 0, 0, 23, 22, 1, 0, 0, 0, 24, 25, 1, 0, 0, 0, 25, 23, 1, 0, 0, 0, 25, 26, 1, 0, 0, 0, 26, 27, 1, 0, 0, 0, 27, 28, 5, 2, 0, 0, 28, 3, 1, 0, 0, 0, 29, 34, 5, 3, 0, 0, 30, 34, 5, 4, 0, 0, 31, 32, 5, 5, 0, 0, 32, 34, 5, 14, 0, 0, 33, 29, 1, 0, 0, 0, 33, 30, 1, 0, 0, 0, 33, 31, 1, 0, 0, 0, 34, 5, 1, 0, 0, 0, 35, 36, 7, 0, 0, 0, 36, 37, 5, 13, 0, 0, 37, 39, 5, 8, 0, 0, 38, 40, 3, 8, 4, 0, 39, 38, 1, 0, 0, 0, 39, 40, 1, 0, 0, 0, 40, 41, 1, 0, 0, 0, 41, 42, 5, 9, 0, 0, 42, 7, 1, 0, 0, 0, 43, 48, 5, 14, 0, 0, 44, 48, 5, 15, 0, 0, 45, 48, 3, 10, 5, 0, 46, 48, 5, 13, 0, 0, 47, 43, 1, 0, 0, 0, 47, 44, 1, 0, 0, 0, 47, 45, 1, 0, 0, 0, 47, 46, 1, 0, 0, 0, 48, 58, 1, 0, 0, 0, 49, 54, 5, 10, 0, 0, 50, 55, 5, 14, 0, 0, 51, 55, 5, 15, 0, 0, 52, 55, 3, 10, 5, 0, 53, 55, 5, 13, 0, 0, 54, 50, 1, 0, 0, 0, 54, 51, 1, 0, 0, 0, 54, 52, 1, 0, 0, 0, 54, 53, 1, 0, 0, 0, 55, 57, 1, 0, 0, 0, 56, 49, 1, 0, 0, 0, 57, 60, 1, 0, 0, 0, 58, 56, 1, 0, 0, 0, 58, 59, 1, 0, 0, 0, 59, 9, 1, 0, 0, 0, 60, 58, 1, 0, 0, 0, 61, 62, 7, 1, 0, 0, 62, 11, 1, 0, 0, 0, 8, 15, 23, 25, 33, 39, 47, 54, 58]
|
||||
|
|
@ -10,7 +10,7 @@ T__8=9
|
|||
T__9=10
|
||||
T__10=11
|
||||
T__11=12
|
||||
Names=13
|
||||
String=13
|
||||
Integer=14
|
||||
Float=15
|
||||
LINE_COMMENT=16
|
||||
|
|
@ -20,7 +20,7 @@ WS=17
|
|||
'sequence'=3
|
||||
'selector'=4
|
||||
'parallel'=5
|
||||
'task'=6
|
||||
'act'=6
|
||||
'cond'=7
|
||||
'('=8
|
||||
')'=9
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
import os
|
||||
import sys
|
||||
from antlr4 import *
|
||||
|
||||
if "." in __name__:
|
||||
|
|
@ -40,6 +41,11 @@ def load(scene, ptml_path: str, behaviour_lib_path: str):
|
|||
tree = parser.root()
|
||||
|
||||
walker = ParseTreeWalker()
|
||||
|
||||
|
||||
sys.path.append(os.path.join(behaviour_lib_path,"cond"))
|
||||
sys.path.append(os.path.join(behaviour_lib_path,"act"))
|
||||
|
||||
ptml = ptmlTranslator(scene, behaviour_lib_path) # listener mode
|
||||
walker.walk(ptml, tree)
|
||||
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
|
|
@ -1,4 +1,4 @@
|
|||
# Generated from E:/Projects/UE5/HARIX_RDKSim/Plugins/HarixSim/Python/ptml/ptml.g4 by ANTLR 4.13.1
|
||||
# Generated from ptml.g4 by ANTLR 4.13.1
|
||||
from antlr4 import *
|
||||
from io import StringIO
|
||||
import sys
|
||||
|
|
@ -10,62 +10,61 @@ else:
|
|||
|
||||
def serializedATN():
|
||||
return [
|
||||
4,0,17,156,6,-1,2,0,7,0,2,1,7,1,2,2,7,2,2,3,7,3,2,4,7,4,2,5,7,5,
|
||||
4,0,17,155,6,-1,2,0,7,0,2,1,7,1,2,2,7,2,2,3,7,3,2,4,7,4,2,5,7,5,
|
||||
2,6,7,6,2,7,7,7,2,8,7,8,2,9,7,9,2,10,7,10,2,11,7,11,2,12,7,12,2,
|
||||
13,7,13,2,14,7,14,2,15,7,15,2,16,7,16,1,0,1,0,1,1,1,1,1,2,1,2,1,
|
||||
2,1,2,1,2,1,2,1,2,1,2,1,2,1,3,1,3,1,3,1,3,1,3,1,3,1,3,1,3,1,3,1,
|
||||
4,1,4,1,4,1,4,1,4,1,4,1,4,1,4,1,4,1,5,1,5,1,5,1,5,1,5,1,6,1,6,1,
|
||||
6,1,6,1,6,1,7,1,7,1,8,1,8,1,9,1,9,1,10,1,10,1,10,1,10,1,10,1,11,
|
||||
1,11,1,11,1,11,1,11,1,11,1,12,1,12,5,12,96,8,12,10,12,12,12,99,9,
|
||||
12,1,13,3,13,102,8,13,1,13,1,13,5,13,106,8,13,10,13,12,13,109,9,
|
||||
13,1,13,3,13,112,8,13,1,14,4,14,115,8,14,11,14,12,14,116,1,14,1,
|
||||
14,5,14,121,8,14,10,14,12,14,124,9,14,1,14,1,14,4,14,128,8,14,11,
|
||||
14,12,14,129,3,14,132,8,14,1,15,1,15,1,15,1,15,5,15,138,8,15,10,
|
||||
15,12,15,141,9,15,1,15,3,15,144,8,15,1,15,1,15,1,15,1,15,1,16,4,
|
||||
16,151,8,16,11,16,12,16,152,1,16,1,16,1,139,0,17,1,1,3,2,5,3,7,4,
|
||||
9,5,11,6,13,7,15,8,17,9,19,10,21,11,23,12,25,13,27,14,29,15,31,16,
|
||||
33,17,1,0,5,3,0,65,90,95,95,97,122,4,0,48,57,65,90,95,95,97,122,
|
||||
1,0,49,57,1,0,48,57,3,0,9,10,12,13,32,32,166,0,1,1,0,0,0,0,3,1,0,
|
||||
0,0,0,5,1,0,0,0,0,7,1,0,0,0,0,9,1,0,0,0,0,11,1,0,0,0,0,13,1,0,0,
|
||||
0,0,15,1,0,0,0,0,17,1,0,0,0,0,19,1,0,0,0,0,21,1,0,0,0,0,23,1,0,0,
|
||||
0,0,25,1,0,0,0,0,27,1,0,0,0,0,29,1,0,0,0,0,31,1,0,0,0,0,33,1,0,0,
|
||||
0,1,35,1,0,0,0,3,37,1,0,0,0,5,39,1,0,0,0,7,48,1,0,0,0,9,57,1,0,0,
|
||||
0,11,66,1,0,0,0,13,71,1,0,0,0,15,76,1,0,0,0,17,78,1,0,0,0,19,80,
|
||||
1,0,0,0,21,82,1,0,0,0,23,87,1,0,0,0,25,93,1,0,0,0,27,111,1,0,0,0,
|
||||
29,131,1,0,0,0,31,133,1,0,0,0,33,150,1,0,0,0,35,36,5,123,0,0,36,
|
||||
2,1,0,0,0,37,38,5,125,0,0,38,4,1,0,0,0,39,40,5,115,0,0,40,41,5,101,
|
||||
0,0,41,42,5,113,0,0,42,43,5,117,0,0,43,44,5,101,0,0,44,45,5,110,
|
||||
0,0,45,46,5,99,0,0,46,47,5,101,0,0,47,6,1,0,0,0,48,49,5,115,0,0,
|
||||
49,50,5,101,0,0,50,51,5,108,0,0,51,52,5,101,0,0,52,53,5,99,0,0,53,
|
||||
54,5,116,0,0,54,55,5,111,0,0,55,56,5,114,0,0,56,8,1,0,0,0,57,58,
|
||||
5,112,0,0,58,59,5,97,0,0,59,60,5,114,0,0,60,61,5,97,0,0,61,62,5,
|
||||
108,0,0,62,63,5,108,0,0,63,64,5,101,0,0,64,65,5,108,0,0,65,10,1,
|
||||
0,0,0,66,67,5,116,0,0,67,68,5,97,0,0,68,69,5,115,0,0,69,70,5,107,
|
||||
0,0,70,12,1,0,0,0,71,72,5,99,0,0,72,73,5,111,0,0,73,74,5,110,0,0,
|
||||
74,75,5,100,0,0,75,14,1,0,0,0,76,77,5,40,0,0,77,16,1,0,0,0,78,79,
|
||||
5,41,0,0,79,18,1,0,0,0,80,81,5,44,0,0,81,20,1,0,0,0,82,83,5,84,0,
|
||||
0,83,84,5,114,0,0,84,85,5,117,0,0,85,86,5,101,0,0,86,22,1,0,0,0,
|
||||
87,88,5,70,0,0,88,89,5,97,0,0,89,90,5,108,0,0,90,91,5,115,0,0,91,
|
||||
92,5,101,0,0,92,24,1,0,0,0,93,97,7,0,0,0,94,96,7,1,0,0,95,94,1,0,
|
||||
0,0,96,99,1,0,0,0,97,95,1,0,0,0,97,98,1,0,0,0,98,26,1,0,0,0,99,97,
|
||||
1,0,0,0,100,102,5,45,0,0,101,100,1,0,0,0,101,102,1,0,0,0,102,103,
|
||||
1,0,0,0,103,107,7,2,0,0,104,106,7,3,0,0,105,104,1,0,0,0,106,109,
|
||||
1,0,0,0,107,105,1,0,0,0,107,108,1,0,0,0,108,112,1,0,0,0,109,107,
|
||||
1,0,0,0,110,112,5,48,0,0,111,101,1,0,0,0,111,110,1,0,0,0,112,28,
|
||||
1,0,0,0,113,115,7,3,0,0,114,113,1,0,0,0,115,116,1,0,0,0,116,114,
|
||||
1,0,0,0,116,117,1,0,0,0,117,118,1,0,0,0,118,122,5,46,0,0,119,121,
|
||||
7,3,0,0,120,119,1,0,0,0,121,124,1,0,0,0,122,120,1,0,0,0,122,123,
|
||||
1,0,0,0,123,132,1,0,0,0,124,122,1,0,0,0,125,127,5,46,0,0,126,128,
|
||||
7,3,0,0,127,126,1,0,0,0,128,129,1,0,0,0,129,127,1,0,0,0,129,130,
|
||||
1,0,0,0,130,132,1,0,0,0,131,114,1,0,0,0,131,125,1,0,0,0,132,30,1,
|
||||
0,0,0,133,134,5,47,0,0,134,135,5,47,0,0,135,139,1,0,0,0,136,138,
|
||||
9,0,0,0,137,136,1,0,0,0,138,141,1,0,0,0,139,140,1,0,0,0,139,137,
|
||||
1,0,0,0,140,143,1,0,0,0,141,139,1,0,0,0,142,144,5,13,0,0,143,142,
|
||||
1,0,0,0,143,144,1,0,0,0,144,145,1,0,0,0,145,146,5,10,0,0,146,147,
|
||||
1,0,0,0,147,148,6,15,0,0,148,32,1,0,0,0,149,151,7,4,0,0,150,149,
|
||||
1,0,0,0,151,152,1,0,0,0,152,150,1,0,0,0,152,153,1,0,0,0,153,154,
|
||||
1,0,0,0,154,155,6,16,0,0,155,34,1,0,0,0,12,0,97,101,107,111,116,
|
||||
122,129,131,139,143,152,1,6,0,0
|
||||
4,1,4,1,4,1,4,1,4,1,4,1,4,1,4,1,4,1,5,1,5,1,5,1,5,1,6,1,6,1,6,1,
|
||||
6,1,6,1,7,1,7,1,8,1,8,1,9,1,9,1,10,1,10,1,10,1,10,1,10,1,11,1,11,
|
||||
1,11,1,11,1,11,1,11,1,12,1,12,5,12,95,8,12,10,12,12,12,98,9,12,1,
|
||||
13,3,13,101,8,13,1,13,1,13,5,13,105,8,13,10,13,12,13,108,9,13,1,
|
||||
13,3,13,111,8,13,1,14,4,14,114,8,14,11,14,12,14,115,1,14,1,14,5,
|
||||
14,120,8,14,10,14,12,14,123,9,14,1,14,1,14,4,14,127,8,14,11,14,12,
|
||||
14,128,3,14,131,8,14,1,15,1,15,1,15,1,15,5,15,137,8,15,10,15,12,
|
||||
15,140,9,15,1,15,3,15,143,8,15,1,15,1,15,1,15,1,15,1,16,4,16,150,
|
||||
8,16,11,16,12,16,151,1,16,1,16,1,138,0,17,1,1,3,2,5,3,7,4,9,5,11,
|
||||
6,13,7,15,8,17,9,19,10,21,11,23,12,25,13,27,14,29,15,31,16,33,17,
|
||||
1,0,5,3,0,65,90,95,95,97,122,4,0,48,57,65,90,95,95,97,122,1,0,49,
|
||||
57,1,0,48,57,3,0,9,10,12,13,32,32,165,0,1,1,0,0,0,0,3,1,0,0,0,0,
|
||||
5,1,0,0,0,0,7,1,0,0,0,0,9,1,0,0,0,0,11,1,0,0,0,0,13,1,0,0,0,0,15,
|
||||
1,0,0,0,0,17,1,0,0,0,0,19,1,0,0,0,0,21,1,0,0,0,0,23,1,0,0,0,0,25,
|
||||
1,0,0,0,0,27,1,0,0,0,0,29,1,0,0,0,0,31,1,0,0,0,0,33,1,0,0,0,1,35,
|
||||
1,0,0,0,3,37,1,0,0,0,5,39,1,0,0,0,7,48,1,0,0,0,9,57,1,0,0,0,11,66,
|
||||
1,0,0,0,13,70,1,0,0,0,15,75,1,0,0,0,17,77,1,0,0,0,19,79,1,0,0,0,
|
||||
21,81,1,0,0,0,23,86,1,0,0,0,25,92,1,0,0,0,27,110,1,0,0,0,29,130,
|
||||
1,0,0,0,31,132,1,0,0,0,33,149,1,0,0,0,35,36,5,123,0,0,36,2,1,0,0,
|
||||
0,37,38,5,125,0,0,38,4,1,0,0,0,39,40,5,115,0,0,40,41,5,101,0,0,41,
|
||||
42,5,113,0,0,42,43,5,117,0,0,43,44,5,101,0,0,44,45,5,110,0,0,45,
|
||||
46,5,99,0,0,46,47,5,101,0,0,47,6,1,0,0,0,48,49,5,115,0,0,49,50,5,
|
||||
101,0,0,50,51,5,108,0,0,51,52,5,101,0,0,52,53,5,99,0,0,53,54,5,116,
|
||||
0,0,54,55,5,111,0,0,55,56,5,114,0,0,56,8,1,0,0,0,57,58,5,112,0,0,
|
||||
58,59,5,97,0,0,59,60,5,114,0,0,60,61,5,97,0,0,61,62,5,108,0,0,62,
|
||||
63,5,108,0,0,63,64,5,101,0,0,64,65,5,108,0,0,65,10,1,0,0,0,66,67,
|
||||
5,97,0,0,67,68,5,99,0,0,68,69,5,116,0,0,69,12,1,0,0,0,70,71,5,99,
|
||||
0,0,71,72,5,111,0,0,72,73,5,110,0,0,73,74,5,100,0,0,74,14,1,0,0,
|
||||
0,75,76,5,40,0,0,76,16,1,0,0,0,77,78,5,41,0,0,78,18,1,0,0,0,79,80,
|
||||
5,44,0,0,80,20,1,0,0,0,81,82,5,84,0,0,82,83,5,114,0,0,83,84,5,117,
|
||||
0,0,84,85,5,101,0,0,85,22,1,0,0,0,86,87,5,70,0,0,87,88,5,97,0,0,
|
||||
88,89,5,108,0,0,89,90,5,115,0,0,90,91,5,101,0,0,91,24,1,0,0,0,92,
|
||||
96,7,0,0,0,93,95,7,1,0,0,94,93,1,0,0,0,95,98,1,0,0,0,96,94,1,0,0,
|
||||
0,96,97,1,0,0,0,97,26,1,0,0,0,98,96,1,0,0,0,99,101,5,45,0,0,100,
|
||||
99,1,0,0,0,100,101,1,0,0,0,101,102,1,0,0,0,102,106,7,2,0,0,103,105,
|
||||
7,3,0,0,104,103,1,0,0,0,105,108,1,0,0,0,106,104,1,0,0,0,106,107,
|
||||
1,0,0,0,107,111,1,0,0,0,108,106,1,0,0,0,109,111,5,48,0,0,110,100,
|
||||
1,0,0,0,110,109,1,0,0,0,111,28,1,0,0,0,112,114,7,3,0,0,113,112,1,
|
||||
0,0,0,114,115,1,0,0,0,115,113,1,0,0,0,115,116,1,0,0,0,116,117,1,
|
||||
0,0,0,117,121,5,46,0,0,118,120,7,3,0,0,119,118,1,0,0,0,120,123,1,
|
||||
0,0,0,121,119,1,0,0,0,121,122,1,0,0,0,122,131,1,0,0,0,123,121,1,
|
||||
0,0,0,124,126,5,46,0,0,125,127,7,3,0,0,126,125,1,0,0,0,127,128,1,
|
||||
0,0,0,128,126,1,0,0,0,128,129,1,0,0,0,129,131,1,0,0,0,130,113,1,
|
||||
0,0,0,130,124,1,0,0,0,131,30,1,0,0,0,132,133,5,47,0,0,133,134,5,
|
||||
47,0,0,134,138,1,0,0,0,135,137,9,0,0,0,136,135,1,0,0,0,137,140,1,
|
||||
0,0,0,138,139,1,0,0,0,138,136,1,0,0,0,139,142,1,0,0,0,140,138,1,
|
||||
0,0,0,141,143,5,13,0,0,142,141,1,0,0,0,142,143,1,0,0,0,143,144,1,
|
||||
0,0,0,144,145,5,10,0,0,145,146,1,0,0,0,146,147,6,15,0,0,147,32,1,
|
||||
0,0,0,148,150,7,4,0,0,149,148,1,0,0,0,150,151,1,0,0,0,151,149,1,
|
||||
0,0,0,151,152,1,0,0,0,152,153,1,0,0,0,153,154,6,16,0,0,154,34,1,
|
||||
0,0,0,12,0,96,100,106,110,115,121,128,130,138,142,151,1,6,0,0
|
||||
]
|
||||
|
||||
class ptmlLexer(Lexer):
|
||||
|
|
@ -86,7 +85,7 @@ class ptmlLexer(Lexer):
|
|||
T__9 = 10
|
||||
T__10 = 11
|
||||
T__11 = 12
|
||||
Names = 13
|
||||
String = 13
|
||||
Integer = 14
|
||||
Float = 15
|
||||
LINE_COMMENT = 16
|
||||
|
|
@ -97,14 +96,14 @@ class ptmlLexer(Lexer):
|
|||
modeNames = [ "DEFAULT_MODE" ]
|
||||
|
||||
literalNames = [ "<INVALID>",
|
||||
"'{'", "'}'", "'sequence'", "'selector'", "'parallel'", "'task'",
|
||||
"'{'", "'}'", "'sequence'", "'selector'", "'parallel'", "'act'",
|
||||
"'cond'", "'('", "')'", "','", "'True'", "'False'" ]
|
||||
|
||||
symbolicNames = [ "<INVALID>",
|
||||
"Names", "Integer", "Float", "LINE_COMMENT", "WS" ]
|
||||
"String", "Integer", "Float", "LINE_COMMENT", "WS" ]
|
||||
|
||||
ruleNames = [ "T__0", "T__1", "T__2", "T__3", "T__4", "T__5", "T__6",
|
||||
"T__7", "T__8", "T__9", "T__10", "T__11", "Names", "Integer",
|
||||
"T__7", "T__8", "T__9", "T__10", "T__11", "String", "Integer",
|
||||
"Float", "LINE_COMMENT", "WS" ]
|
||||
|
||||
grammarFileName = "ptml.g4"
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ T__8=9
|
|||
T__9=10
|
||||
T__10=11
|
||||
T__11=12
|
||||
Names=13
|
||||
String=13
|
||||
Integer=14
|
||||
Float=15
|
||||
LINE_COMMENT=16
|
||||
|
|
@ -20,7 +20,7 @@ WS=17
|
|||
'sequence'=3
|
||||
'selector'=4
|
||||
'parallel'=5
|
||||
'task'=6
|
||||
'act'=6
|
||||
'cond'=7
|
||||
'('=8
|
||||
')'=9
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
# Generated from E:/Projects/UE5/HARIX_RDKSim/Plugins/HarixSim/Python/ptml/ptml.g4 by ANTLR 4.13.1
|
||||
# Generated from ptml.g4 by ANTLR 4.13.1
|
||||
from antlr4 import *
|
||||
if "." in __name__:
|
||||
from .ptmlParser import ptmlParser
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
# Generated from E:/Projects/UE5/HARIX_RDKSim/Plugins/HarixSim/Python/ptml/ptml.g4 by ANTLR 4.13.1
|
||||
# Generated from ptml.g4 by ANTLR 4.13.1
|
||||
# encoding: utf-8
|
||||
from antlr4 import *
|
||||
from io import StringIO
|
||||
|
|
@ -10,26 +10,27 @@ else:
|
|||
|
||||
def serializedATN():
|
||||
return [
|
||||
4,1,17,62,2,0,7,0,2,1,7,1,2,2,7,2,2,3,7,3,2,4,7,4,2,5,7,5,1,0,4,
|
||||
4,1,17,64,2,0,7,0,2,1,7,1,2,2,7,2,2,3,7,3,2,4,7,4,2,5,7,5,1,0,4,
|
||||
0,14,8,0,11,0,12,0,15,1,0,1,0,1,1,1,1,1,1,1,1,4,1,24,8,1,11,1,12,
|
||||
1,25,1,1,1,1,1,2,1,2,1,2,1,2,3,2,34,8,2,1,3,1,3,1,3,1,3,3,3,40,8,
|
||||
3,1,3,1,3,1,4,1,4,1,4,3,4,47,8,4,1,4,1,4,1,4,1,4,3,4,53,8,4,5,4,
|
||||
55,8,4,10,4,12,4,58,9,4,1,5,1,5,1,5,0,0,6,0,2,4,6,8,10,0,2,1,0,6,
|
||||
7,1,0,11,12,66,0,13,1,0,0,0,2,19,1,0,0,0,4,33,1,0,0,0,6,35,1,0,0,
|
||||
0,8,46,1,0,0,0,10,59,1,0,0,0,12,14,3,2,1,0,13,12,1,0,0,0,14,15,1,
|
||||
0,0,0,15,13,1,0,0,0,15,16,1,0,0,0,16,17,1,0,0,0,17,18,5,0,0,1,18,
|
||||
1,1,0,0,0,19,20,3,4,2,0,20,23,5,1,0,0,21,24,3,6,3,0,22,24,3,2,1,
|
||||
0,23,21,1,0,0,0,23,22,1,0,0,0,24,25,1,0,0,0,25,23,1,0,0,0,25,26,
|
||||
1,0,0,0,26,27,1,0,0,0,27,28,5,2,0,0,28,3,1,0,0,0,29,34,5,3,0,0,30,
|
||||
34,5,4,0,0,31,32,5,5,0,0,32,34,5,14,0,0,33,29,1,0,0,0,33,30,1,0,
|
||||
0,0,33,31,1,0,0,0,34,5,1,0,0,0,35,36,7,0,0,0,36,37,5,13,0,0,37,39,
|
||||
5,8,0,0,38,40,3,8,4,0,39,38,1,0,0,0,39,40,1,0,0,0,40,41,1,0,0,0,
|
||||
41,42,5,9,0,0,42,7,1,0,0,0,43,47,5,14,0,0,44,47,5,15,0,0,45,47,3,
|
||||
10,5,0,46,43,1,0,0,0,46,44,1,0,0,0,46,45,1,0,0,0,47,56,1,0,0,0,48,
|
||||
52,5,10,0,0,49,53,5,14,0,0,50,53,5,15,0,0,51,53,3,10,5,0,52,49,1,
|
||||
0,0,0,52,50,1,0,0,0,52,51,1,0,0,0,53,55,1,0,0,0,54,48,1,0,0,0,55,
|
||||
58,1,0,0,0,56,54,1,0,0,0,56,57,1,0,0,0,57,9,1,0,0,0,58,56,1,0,0,
|
||||
0,59,60,7,1,0,0,60,11,1,0,0,0,8,15,23,25,33,39,46,52,56
|
||||
3,1,3,1,3,1,4,1,4,1,4,1,4,3,4,48,8,4,1,4,1,4,1,4,1,4,1,4,3,4,55,
|
||||
8,4,5,4,57,8,4,10,4,12,4,60,9,4,1,5,1,5,1,5,0,0,6,0,2,4,6,8,10,0,
|
||||
2,1,0,6,7,1,0,11,12,70,0,13,1,0,0,0,2,19,1,0,0,0,4,33,1,0,0,0,6,
|
||||
35,1,0,0,0,8,47,1,0,0,0,10,61,1,0,0,0,12,14,3,2,1,0,13,12,1,0,0,
|
||||
0,14,15,1,0,0,0,15,13,1,0,0,0,15,16,1,0,0,0,16,17,1,0,0,0,17,18,
|
||||
5,0,0,1,18,1,1,0,0,0,19,20,3,4,2,0,20,23,5,1,0,0,21,24,3,6,3,0,22,
|
||||
24,3,2,1,0,23,21,1,0,0,0,23,22,1,0,0,0,24,25,1,0,0,0,25,23,1,0,0,
|
||||
0,25,26,1,0,0,0,26,27,1,0,0,0,27,28,5,2,0,0,28,3,1,0,0,0,29,34,5,
|
||||
3,0,0,30,34,5,4,0,0,31,32,5,5,0,0,32,34,5,14,0,0,33,29,1,0,0,0,33,
|
||||
30,1,0,0,0,33,31,1,0,0,0,34,5,1,0,0,0,35,36,7,0,0,0,36,37,5,13,0,
|
||||
0,37,39,5,8,0,0,38,40,3,8,4,0,39,38,1,0,0,0,39,40,1,0,0,0,40,41,
|
||||
1,0,0,0,41,42,5,9,0,0,42,7,1,0,0,0,43,48,5,14,0,0,44,48,5,15,0,0,
|
||||
45,48,3,10,5,0,46,48,5,13,0,0,47,43,1,0,0,0,47,44,1,0,0,0,47,45,
|
||||
1,0,0,0,47,46,1,0,0,0,48,58,1,0,0,0,49,54,5,10,0,0,50,55,5,14,0,
|
||||
0,51,55,5,15,0,0,52,55,3,10,5,0,53,55,5,13,0,0,54,50,1,0,0,0,54,
|
||||
51,1,0,0,0,54,52,1,0,0,0,54,53,1,0,0,0,55,57,1,0,0,0,56,49,1,0,0,
|
||||
0,57,60,1,0,0,0,58,56,1,0,0,0,58,59,1,0,0,0,59,9,1,0,0,0,60,58,1,
|
||||
0,0,0,61,62,7,1,0,0,62,11,1,0,0,0,8,15,23,25,33,39,47,54,58
|
||||
]
|
||||
|
||||
class ptmlParser ( Parser ):
|
||||
|
|
@ -43,13 +44,13 @@ class ptmlParser ( Parser ):
|
|||
sharedContextCache = PredictionContextCache()
|
||||
|
||||
literalNames = [ "<INVALID>", "'{'", "'}'", "'sequence'", "'selector'",
|
||||
"'parallel'", "'task'", "'cond'", "'('", "')'", "','",
|
||||
"'parallel'", "'act'", "'cond'", "'('", "')'", "','",
|
||||
"'True'", "'False'" ]
|
||||
|
||||
symbolicNames = [ "<INVALID>", "<INVALID>", "<INVALID>", "<INVALID>",
|
||||
"<INVALID>", "<INVALID>", "<INVALID>", "<INVALID>",
|
||||
"<INVALID>", "<INVALID>", "<INVALID>", "<INVALID>",
|
||||
"<INVALID>", "Names", "Integer", "Float", "LINE_COMMENT",
|
||||
"<INVALID>", "String", "Integer", "Float", "LINE_COMMENT",
|
||||
"WS" ]
|
||||
|
||||
RULE_root = 0
|
||||
|
|
@ -75,7 +76,7 @@ class ptmlParser ( Parser ):
|
|||
T__9=10
|
||||
T__10=11
|
||||
T__11=12
|
||||
Names=13
|
||||
String=13
|
||||
Integer=14
|
||||
Float=15
|
||||
LINE_COMMENT=16
|
||||
|
|
@ -304,8 +305,8 @@ class ptmlParser ( Parser ):
|
|||
super().__init__(parent, invokingState)
|
||||
self.parser = parser
|
||||
|
||||
def Names(self):
|
||||
return self.getToken(ptmlParser.Names, 0)
|
||||
def String(self):
|
||||
return self.getToken(ptmlParser.String, 0)
|
||||
|
||||
def action_parm(self):
|
||||
return self.getTypedRuleContext(ptmlParser.Action_parmContext,0)
|
||||
|
|
@ -340,13 +341,13 @@ class ptmlParser ( Parser ):
|
|||
self._errHandler.reportMatch(self)
|
||||
self.consume()
|
||||
self.state = 36
|
||||
self.match(ptmlParser.Names)
|
||||
self.match(ptmlParser.String)
|
||||
self.state = 37
|
||||
self.match(ptmlParser.T__7)
|
||||
self.state = 39
|
||||
self._errHandler.sync(self)
|
||||
_la = self._input.LA(1)
|
||||
if (((_la) & ~0x3f) == 0 and ((1 << _la) & 55296) != 0):
|
||||
if (((_la) & ~0x3f) == 0 and ((1 << _la) & 63488) != 0):
|
||||
self.state = 38
|
||||
self.action_parm()
|
||||
|
||||
|
|
@ -388,6 +389,12 @@ class ptmlParser ( Parser ):
|
|||
return self.getTypedRuleContext(ptmlParser.BooleanContext,i)
|
||||
|
||||
|
||||
def String(self, i:int=None):
|
||||
if i is None:
|
||||
return self.getTokens(ptmlParser.String)
|
||||
else:
|
||||
return self.getToken(ptmlParser.String, i)
|
||||
|
||||
def getRuleIndex(self):
|
||||
return ptmlParser.RULE_action_parm
|
||||
|
||||
|
|
@ -409,7 +416,7 @@ class ptmlParser ( Parser ):
|
|||
self._la = 0 # Token type
|
||||
try:
|
||||
self.enterOuterAlt(localctx, 1)
|
||||
self.state = 46
|
||||
self.state = 47
|
||||
self._errHandler.sync(self)
|
||||
token = self._input.LA(1)
|
||||
if token in [14]:
|
||||
|
|
@ -424,34 +431,42 @@ class ptmlParser ( Parser ):
|
|||
self.state = 45
|
||||
self.boolean()
|
||||
pass
|
||||
elif token in [13]:
|
||||
self.state = 46
|
||||
self.match(ptmlParser.String)
|
||||
pass
|
||||
else:
|
||||
raise NoViableAltException(self)
|
||||
|
||||
self.state = 56
|
||||
self.state = 58
|
||||
self._errHandler.sync(self)
|
||||
_la = self._input.LA(1)
|
||||
while _la==10:
|
||||
self.state = 48
|
||||
self.state = 49
|
||||
self.match(ptmlParser.T__9)
|
||||
self.state = 52
|
||||
self.state = 54
|
||||
self._errHandler.sync(self)
|
||||
token = self._input.LA(1)
|
||||
if token in [14]:
|
||||
self.state = 49
|
||||
self.state = 50
|
||||
self.match(ptmlParser.Integer)
|
||||
pass
|
||||
elif token in [15]:
|
||||
self.state = 50
|
||||
self.state = 51
|
||||
self.match(ptmlParser.Float)
|
||||
pass
|
||||
elif token in [11, 12]:
|
||||
self.state = 51
|
||||
self.state = 52
|
||||
self.boolean()
|
||||
pass
|
||||
elif token in [13]:
|
||||
self.state = 53
|
||||
self.match(ptmlParser.String)
|
||||
pass
|
||||
else:
|
||||
raise NoViableAltException(self)
|
||||
|
||||
self.state = 58
|
||||
self.state = 60
|
||||
self._errHandler.sync(self)
|
||||
_la = self._input.LA(1)
|
||||
|
||||
|
|
@ -493,7 +508,7 @@ class ptmlParser ( Parser ):
|
|||
self._la = 0 # Token type
|
||||
try:
|
||||
self.enterOuterAlt(localctx, 1)
|
||||
self.state = 59
|
||||
self.state = 61
|
||||
_la = self._input.LA(1)
|
||||
if not(_la==11 or _la==12):
|
||||
self._errHandler.recoverInline(self)
|
||||
|
|
|
|||
|
|
@ -76,9 +76,9 @@ class ptmlTranslator(ptmlListener):
|
|||
|
||||
# Enter a parse tree produced by ptmlParser#action_sign.
|
||||
def enterAction_sign(self, ctx: ptmlParser.Action_signContext):
|
||||
# cond / task
|
||||
# cond / act
|
||||
node_type = str(ctx.children[0])
|
||||
name = str(ctx.Names())
|
||||
name = str(ctx.String())
|
||||
|
||||
# if have params
|
||||
args = []
|
||||
|
|
@ -88,22 +88,21 @@ class ptmlTranslator(ptmlListener):
|
|||
for i in params.children:
|
||||
if isinstance(i, ptmlParser.BooleanContext):
|
||||
args.append(str(i.children[0]))
|
||||
elif str(i)==',':
|
||||
args.append(',')
|
||||
else:
|
||||
args.append(str(i))
|
||||
args.append(f"'{i}'")
|
||||
|
||||
args = "".join(args)
|
||||
|
||||
import sys
|
||||
|
||||
sys.path.append(self.behaviour_lib_path)
|
||||
|
||||
exec("from {} import {}".format(name, name))
|
||||
exec(f"from {name} import {name}")
|
||||
#
|
||||
tag = "cond_" + short_uuid() if node_type == "cond" else "task_" + short_uuid()
|
||||
# tag = "cond_" + short_uuid() if node_type == "cond" else "task_" + short_uuid()
|
||||
|
||||
node = eval(
|
||||
"{}('{}', scene, {})".format(name, tag, args), {"scene": self.scene, **locals()}
|
||||
)
|
||||
print(f'create node: {name}({args})')
|
||||
node = eval(f"{name}({args})")
|
||||
node.set_scene(self.scene)
|
||||
|
||||
# connect
|
||||
self.stack[-1].add_child(node)
|
||||
|
|
|
|||
|
|
@ -1,22 +0,0 @@
|
|||
import os
|
||||
import py_trees as ptree
|
||||
|
||||
from scene import scene
|
||||
from ptmlCompiler import load
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
||||
project_path = ""
|
||||
|
||||
ptml_path = os.path.join(project_path, 'CoffeeDelivery.ptml')
|
||||
behavior_lib_path = os.path.join(project_path, '../../behavior_lib')
|
||||
|
||||
scene = control.Scene(sceneID=0)
|
||||
# load
|
||||
scene.load_BT(ptml_path, behavior_lib_path)
|
||||
# ptree.display.render_dot_tree(bt)
|
||||
# build and tick
|
||||
scene.BT = ptree.trees.BehaviourTree(scene.BT)
|
||||
# todo: tick this bt
|
||||
print(scene.BT)
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
digraph pastafarianism {
|
||||
ordering=out;
|
||||
graph [fontname="times-roman"];
|
||||
node [fontname="times-roman"];
|
||||
edge [fontname="times-roman"];
|
||||
sequence_oUFBg8fG [fillcolor=orange, fontcolor=black, fontsize=9, label=sequence_oUFBg8fG, shape=box, style=filled];
|
||||
selector_mPAUGPy3 [fillcolor=cyan, fontcolor=black, fontsize=9, label=selector_mPAUGPy3, shape=octagon, style=filled];
|
||||
sequence_oUFBg8fG -> selector_mPAUGPy3;
|
||||
cond_G7w6nx8B [fillcolor=gray, fontcolor=black, fontsize=9, label=cond_G7w6nx8B, shape=ellipse, style=filled];
|
||||
selector_mPAUGPy3 -> cond_G7w6nx8B;
|
||||
task_XjF4V8bW [fillcolor=gray, fontcolor=black, fontsize=9, label=task_XjF4V8bW, shape=ellipse, style=filled];
|
||||
selector_mPAUGPy3 -> task_XjF4V8bW;
|
||||
sequence_n3nzZvgz [fillcolor=orange, fontcolor=black, fontsize=9, label=sequence_n3nzZvgz, shape=box, style=filled];
|
||||
selector_mPAUGPy3 -> sequence_n3nzZvgz;
|
||||
cond_KCt2aubU [fillcolor=gray, fontcolor=black, fontsize=9, label=cond_KCt2aubU, shape=ellipse, style=filled];
|
||||
sequence_n3nzZvgz -> cond_KCt2aubU;
|
||||
task_a8inFHcZ [fillcolor=gray, fontcolor=black, fontsize=9, label=task_a8inFHcZ, shape=ellipse, style=filled];
|
||||
sequence_n3nzZvgz -> task_a8inFHcZ;
|
||||
task_YF2aiEPZ [fillcolor=gray, fontcolor=black, fontsize=9, label=task_YF2aiEPZ, shape=ellipse, style=filled];
|
||||
sequence_n3nzZvgz -> task_YF2aiEPZ;
|
||||
parallel_WEe6n4ym [fillcolor=gold, fontcolor=black, fontsize=9, label="parallel_WEe6n4ym\ntype", shape=parallelogram, style=filled];
|
||||
sequence_n3nzZvgz -> parallel_WEe6n4ym;
|
||||
cond_mRQoZb2w [fillcolor=gray, fontcolor=black, fontsize=9, label=cond_mRQoZb2w, shape=ellipse, style=filled];
|
||||
parallel_WEe6n4ym -> cond_mRQoZb2w;
|
||||
task_MW4BQ2XF [fillcolor=gray, fontcolor=black, fontsize=9, label=task_MW4BQ2XF, shape=ellipse, style=filled];
|
||||
parallel_WEe6n4ym -> task_MW4BQ2XF;
|
||||
selector_tU6G7YK6 [fillcolor=cyan, fontcolor=black, fontsize=9, label=selector_tU6G7YK6, shape=octagon, style=filled];
|
||||
sequence_oUFBg8fG -> selector_tU6G7YK6;
|
||||
cond_UMTzm9kK [fillcolor=gray, fontcolor=black, fontsize=9, label=cond_UMTzm9kK, shape=ellipse, style=filled];
|
||||
selector_tU6G7YK6 -> cond_UMTzm9kK;
|
||||
task_fnpwP2Lu [fillcolor=gray, fontcolor=black, fontsize=9, label=task_fnpwP2Lu, shape=ellipse, style=filled];
|
||||
selector_tU6G7YK6 -> task_fnpwP2Lu;
|
||||
selector_qm8Zexyr [fillcolor=cyan, fontcolor=black, fontsize=9, label=selector_qm8Zexyr, shape=octagon, style=filled];
|
||||
sequence_oUFBg8fG -> selector_qm8Zexyr;
|
||||
cond_g2umcjH4 [fillcolor=gray, fontcolor=black, fontsize=9, label=cond_g2umcjH4, shape=ellipse, style=filled];
|
||||
selector_qm8Zexyr -> cond_g2umcjH4;
|
||||
task_H5nwyj3V [fillcolor=gray, fontcolor=black, fontsize=9, label=task_H5nwyj3V, shape=ellipse, style=filled];
|
||||
selector_qm8Zexyr -> task_H5nwyj3V;
|
||||
selector_9SJMhckE [fillcolor=cyan, fontcolor=black, fontsize=9, label=selector_9SJMhckE, shape=octagon, style=filled];
|
||||
sequence_oUFBg8fG -> selector_9SJMhckE;
|
||||
cond_D8fqA35b [fillcolor=gray, fontcolor=black, fontsize=9, label=cond_D8fqA35b, shape=ellipse, style=filled];
|
||||
selector_9SJMhckE -> cond_D8fqA35b;
|
||||
task_EikNgjy4 [fillcolor=gray, fontcolor=black, fontsize=9, label=task_EikNgjy4, shape=ellipse, style=filled];
|
||||
selector_9SJMhckE -> task_EikNgjy4;
|
||||
}
|
||||
|
|
@ -9,27 +9,27 @@
|
|||
sequence{
|
||||
selector{
|
||||
cond CoffeeCupFound()
|
||||
task FindCoffeeCup()
|
||||
act FindCoffeeCup()
|
||||
sequence{
|
||||
cond SeqTest()
|
||||
task Move(1.2, 2, 2.3, True)
|
||||
task Grasp()
|
||||
act Move(1.2, 2, 2.3, True)
|
||||
act Grasp()
|
||||
parallel 3 {
|
||||
cond Istask()
|
||||
task TestTask()
|
||||
cond Isact()
|
||||
act Testact()
|
||||
}
|
||||
}
|
||||
}
|
||||
selector{
|
||||
cond CoffeeCupGrasped()
|
||||
task GraspCoffeeCup()
|
||||
act GraspCoffeeCup()
|
||||
}
|
||||
selector{
|
||||
cond DestinationAReached()
|
||||
task ReachDestinationA()
|
||||
act ReachDestinationA()
|
||||
}
|
||||
selector{
|
||||
cond CoffeeCupPlaced()
|
||||
task PlaceCoffeeCup()
|
||||
act PlaceCoffeeCup()
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,7 @@
|
|||
selector{
|
||||
sequence{
|
||||
cond Chatting()
|
||||
act DealChat()
|
||||
}
|
||||
act At(Coffee,Table)
|
||||
}
|
||||
|
|
@ -0,0 +1,28 @@
|
|||
import os
|
||||
import py_trees as ptree
|
||||
|
||||
from robowaiter.scene.scene import Scene
|
||||
from robowaiter.behavior_tree.ptml.ptmlCompiler import load
|
||||
|
||||
import os
|
||||
from robowaiter import Robot, task_map
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
TASK_NAME = 'OT'
|
||||
|
||||
# create robot
|
||||
project_path = "../../../"
|
||||
ptml_path = os.path.join(project_path, 'behavior_tree/ptml/test/Test.ptml')
|
||||
behavior_lib_path = os.path.join(project_path, 'behavior_lib')
|
||||
|
||||
robot = Robot(ptml_path, behavior_lib_path)
|
||||
|
||||
# create task
|
||||
task = task_map[TASK_NAME](robot)
|
||||
|
||||
ptree.display.render_dot_tree(robot.bt.root,name="test")
|
||||
# build and tick
|
||||
# scene.BT = ptree.trees.BehaviourTree(scene.BT)
|
||||
# todo: tick this bt
|
||||
print(robot.bt)
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
grammar ptml;
|
||||
|
||||
root : tree+ EOF;
|
||||
|
||||
tree : internal_node '{' (action_sign|tree)+ '}' ;
|
||||
internal_node : 'sequence' | 'selector' | 'parallel' Integer ;
|
||||
action_sign : ('task'|'cond') Names '(' action_parm? ')';
|
||||
action_parm : (Integer|Float|boolean) (',' (Integer|Float|boolean))* ;
|
||||
// var_decls : var_type Names ;
|
||||
// var_type : 'int' | 'float' | 'bool' | 'string' ;
|
||||
boolean : 'True' | 'False' ;
|
||||
|
||||
Names : [a-zA-Z_][a-zA-Z_0-9]* ;
|
||||
Integer : '-'?[1-9][0-9]* | '0' ;
|
||||
Float : [0-9]+'.'[0-9]* | '.'[0-9]+ ;
|
||||
|
||||
// comments
|
||||
LINE_COMMENT : '//' .*? '\r'?'\n' -> skip ;
|
||||
// useless
|
||||
WS : [ \t\u000C\r\n]+ -> skip ;
|
||||
|
|
@ -1,4 +1,7 @@
|
|||
sequence{
|
||||
cond Chatting()
|
||||
task DealChat()
|
||||
selector{
|
||||
sequence{
|
||||
cond Chatting()
|
||||
act DealChat()
|
||||
}
|
||||
act At("Coffee","Table")
|
||||
}
|
||||
|
|
|
|||
|
|
@ -59,15 +59,16 @@ class Scene:
|
|||
collision: str, info: str
|
||||
"""
|
||||
|
||||
def __init__(self,robot, sceneID=0):
|
||||
def __init__(self,robot=None, sceneID=0):
|
||||
self.sceneID = sceneID
|
||||
self.use_offset = True
|
||||
self.start_time = time.time()
|
||||
self.time = 0
|
||||
|
||||
# init robot
|
||||
robot.set_scene(self)
|
||||
robot.load_BT()
|
||||
if robot:
|
||||
robot.set_scene(self)
|
||||
robot.load_BT()
|
||||
self.robot = robot
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -17,13 +17,16 @@ class SceneOT(Scene):
|
|||
super().__init__(robot)
|
||||
|
||||
def _reset(self):
|
||||
self.reset_sim()
|
||||
|
||||
self.add_walker(1085, 2630, 220)
|
||||
self.control_walker([self.walker_control_generator(0, False, 100, 755, 1900, 180)])
|
||||
|
||||
|
||||
def _run(self):
|
||||
pass
|
||||
|
||||
def _step(self):
|
||||
pass
|
||||
|
||||
if int(self.time) == 5:
|
||||
print("顾客说：给我一杯咖啡")
|
||||
self.chat_bubble('顾客说：给我一杯咖啡')
|
||||
self.state['chat_list'].append('给我一杯咖啡')
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import os
|
||||
from robowaiter import Robot, task_map
|
||||
|
||||
TASK_NAME = 'GQA'
|
||||
TASK_NAME = 'OT'
|
||||
|
||||
# create robot
|
||||
project_path = "./robowaiter"
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import py_trees as ptree
|
||||
from typing import Any
|
||||
|
||||
# base Behavior
|
||||
# _base Behavior
|
||||
class Bahavior(ptree.behaviour.Behaviour):
|
||||
scene = None
|
||||
def __init__(self, name: str, scene):
|
||||
|
|
@ -15,7 +15,7 @@ class Bahavior(ptree.behaviour.Behaviour):
|
|||
return super().initialise()
|
||||
|
||||
def _update(self) -> ptree.common.Status:
|
||||
print("this is just a base behavior node.")
|
||||
print("this is just a _base behavior node.")
|
||||
|
||||
|
||||
def update(self) -> ptree.common.Status:
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import py_trees as ptree
|
||||
from typing import Any
|
||||
from robowaiter.behavior_lib.Behavior import Bahavior
|
||||
from robowaiter.behavior_lib._base.Behavior import Bahavior
|
||||
|
||||
class Chatting(Bahavior):
|
||||
def __init__(self, name: str, scene):
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import py_trees as ptree
|
||||
from typing import Any
|
||||
from robowaiter.behavior_lib.Behavior import Bahavior
|
||||
from robowaiter.behavior_lib._base.Behavior import Bahavior
|
||||
|
||||
class CoffeeCupFound(Bahavior):
|
||||
def __init__(self, name: str, scene):
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import py_trees as ptree
|
||||
from typing import Any
|
||||
from robowaiter.behavior_lib.Behavior import Bahavior
|
||||
from robowaiter.behavior_lib._base.Behavior import Bahavior
|
||||
|
||||
class CoffeeCupGrasped(Bahavior):
|
||||
def __init__(self, name: str, scene):
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import py_trees as ptree
|
||||
from typing import Any
|
||||
from robowaiter.behavior_lib.Behavior import Bahavior
|
||||
from robowaiter.behavior_lib._base.Behavior import Bahavior
|
||||
from robowaiter.llm_client.ask_llm import ask_llm
|
||||
|
||||
class DealChat(Bahavior):
|
||||
|
|
@ -0,0 +1,21 @@
|
|||
import py_trees as ptree
|
||||
from typing import Any
|
||||
|
||||
class Grasp(ptree.behaviour.Behaviour):
|
||||
|
||||
def __init__(self, name: str, scene):
|
||||
super().__init__(name)
|
||||
|
||||
def setup(self, **kwargs: Any) -> None:
|
||||
return super().setup(**kwargs)
|
||||
|
||||
def initialise(self) -> None:
|
||||
return super().initialise()
|
||||
|
||||
def _update(self) -> ptree.common.Status:
|
||||
print('Start checking IsChatting...')
|
||||
return ptree.common.Status.SUCCESS
|
||||
|
||||
def terminate(self, new_status: ptree.common.Status) -> None:
|
||||
return super().terminate(new_status)
|
||||
|
||||
|
|
@ -0,0 +1,21 @@
|
|||
import py_trees as ptree
|
||||
from typing import Any
|
||||
|
||||
class MoveTo(ptree.behaviour.Behaviour):
|
||||
|
||||
def __init__(self, name: str, scene, a, b, c, d):
|
||||
super().__init__(name)
|
||||
|
||||
def setup(self, **kwargs: Any) -> None:
|
||||
return super().setup(**kwargs)
|
||||
|
||||
def initialise(self) -> None:
|
||||
return super().initialise()
|
||||
|
||||
def _update(self) -> ptree.common.Status:
|
||||
print('Start checking IsChatting...')
|
||||
return ptree.common.Status.SUCCESS
|
||||
|
||||
def terminate(self, new_status: ptree.common.Status) -> None:
|
||||
return super().terminate(new_status)
|
||||
|
||||
|
|
@ -0,0 +1,95 @@
|
|||
|
||||
#叶结点
|
||||
class Leaf:
|
||||
def __init__(self,type,content,mincost):
|
||||
self.type=type
|
||||
self.content=content #conditionset or action
|
||||
self.parent=None
|
||||
self.parent_index=0
|
||||
self.mincost=mincost
|
||||
|
||||
# tick 叶节点，返回返回值以及对应的条件或行动对象self.content
|
||||
def tick(self,state):
|
||||
if self.type=='cond':
|
||||
if self.content <= state:
|
||||
return 'success',self.content
|
||||
else:
|
||||
return 'failure',self.content
|
||||
if self.type=='act':
|
||||
if self.content.pre<=state:
|
||||
return 'running',self.content #action
|
||||
else:
|
||||
return 'failure',self.content
|
||||
|
||||
def __str__(self):
|
||||
print( self.content)
|
||||
return ''
|
||||
|
||||
def print_nodes(self):
|
||||
print(self.content)
|
||||
|
||||
def count_size(self):
|
||||
return 1
|
||||
|
||||
|
||||
#可能包含控制结点的行为树
|
||||
class ControlBT:
|
||||
def __init__(self,type):
|
||||
self.type=type
|
||||
self.children=[]
|
||||
self.parent=None
|
||||
self.parent_index=0
|
||||
|
||||
|
||||
def add_child(self,subtree_list):
|
||||
for subtree in subtree_list:
|
||||
self.children.append(subtree)
|
||||
subtree.parent=self
|
||||
subtree.parent_index=len(self.children)-1
|
||||
|
||||
# tick行为树，根据不同控制结点逻辑tick子结点
|
||||
def tick(self,state):
|
||||
if len(self.children) < 1:
|
||||
print("error,no child")
|
||||
if self.type =='?':#选择结点，即或结点
|
||||
for child in self.children:
|
||||
val,obj=child.tick(state)
|
||||
if val=='success':
|
||||
return val,obj
|
||||
if val=='running':
|
||||
return val,obj
|
||||
return 'failure','?fails'
|
||||
if self.type =='>':#顺序结点，即与结点
|
||||
for child in self.children:
|
||||
val,obj=child.tick(state)
|
||||
if val=='failure':
|
||||
return val,obj
|
||||
if val=='running':
|
||||
return val,obj
|
||||
return 'success', '>success'
|
||||
if self.type =='act':#行动结点
|
||||
return self.children[0].tick(state)
|
||||
if self.type =='cond':#条件结点
|
||||
return self.children[0].tick(state)
|
||||
|
||||
def getFirstChild(self):
|
||||
return self.children[0]
|
||||
|
||||
def __str__(self):
|
||||
print(self.type+'\n')
|
||||
for child in self.children:
|
||||
print (child)
|
||||
return ''
|
||||
|
||||
def print_nodes(self):
|
||||
print(self.type)
|
||||
for child in self.children:
|
||||
child.print_nodes()
|
||||
|
||||
# 递归统计树中结点数
|
||||
def count_size(self):
|
||||
result=1
|
||||
for child in self.children:
|
||||
result+= child.count_size()
|
||||
return result
|
||||
|
||||
|
|
@ -0,0 +1,210 @@
|
|||
import copy
|
||||
import random
|
||||
from robowaiter.behavior_tree.obtea.BehaviorTree import Leaf,ControlBT
|
||||
|
||||
class CondActPair:
|
||||
def __init__(self, cond_leaf,act_leaf):
|
||||
self.cond_leaf = cond_leaf
|
||||
self.act_leaf = act_leaf
|
||||
|
||||
#定义行动类，行动包括前提、增加和删除影响
|
||||
class Action:
|
||||
def __init__(self,name='anonymous action',pre=set(),add=set(),del_set=set(),cost=1):
|
||||
self.pre=copy.deepcopy(pre)
|
||||
self.add=copy.deepcopy(add)
|
||||
self.del_set=copy.deepcopy(del_set)
|
||||
self.name=name
|
||||
self.cost=cost
|
||||
|
||||
def __str__(self):
|
||||
return self.name
|
||||
|
||||
#生成随机状态
|
||||
def generate_random_state(num):
|
||||
result = set()
|
||||
for i in range(0,num):
|
||||
if random.random()>0.5:
|
||||
result.add(i)
|
||||
return result
|
||||
#从状态和行动生成后继状态
|
||||
def state_transition(state,action):
|
||||
if not action.pre <= state:
|
||||
print ('error: action not applicable')
|
||||
return state
|
||||
new_state=(state | action.add) - action.del_set
|
||||
return new_state
|
||||
|
||||
|
||||
#本文所提出的完备规划算法
|
||||
class OptBTExpAlgorithm:
|
||||
def __init__(self,verbose=False):
|
||||
self.bt = None
|
||||
self.nodes=[]
|
||||
self.traversed=[]
|
||||
self.mounted=[]
|
||||
self.conditions=[]
|
||||
self.conditions_index=[]
|
||||
self.verbose=verbose
|
||||
|
||||
def clear(self):
|
||||
self.bt = None
|
||||
self.nodes = []
|
||||
self.traversed = []
|
||||
self.conditions = []
|
||||
self.conditions_index = []
|
||||
|
||||
#运行规划算法，从初始状态、目标状态和可用行动，计算行为树self.bt
|
||||
def run_algorithm(self,goal,actions):
|
||||
if self.verbose:
|
||||
print("\n算法开始！")
|
||||
|
||||
|
||||
self.bt = ControlBT(type='cond')
|
||||
# 初始行为树只包含目标条件
|
||||
gc_node = Leaf(type='cond', content=goal,mincost=0) # 为了统一，都成对出现
|
||||
ga_node = Leaf(type='act', content=None, mincost=0)
|
||||
subtree = ControlBT(type='?')
|
||||
subtree.add_child([copy.deepcopy(gc_node)]) # 子树首先保留所扩展结
|
||||
self.bt.add_child([subtree])
|
||||
|
||||
# self.conditions.append(goal)
|
||||
cond_anc_pair = CondActPair(cond_leaf=gc_node,act_leaf=ga_node)
|
||||
self.nodes.append(copy.deepcopy(cond_anc_pair)) # the set of explored but unexpanded conditions
|
||||
self.traversed = [goal] # the set of expanded conditions
|
||||
|
||||
|
||||
while len(self.nodes)!=0:
|
||||
|
||||
# Find the condition for the shortest cost path
|
||||
pair_node = None
|
||||
min_cost = float ('inf')
|
||||
index= -1
|
||||
for i,cond_anc_pair in enumerate(self.nodes):
|
||||
if cond_anc_pair.cond_leaf.mincost < min_cost:
|
||||
min_cost = cond_anc_pair.cond_leaf.mincost
|
||||
pair_node = copy.deepcopy(cond_anc_pair)
|
||||
index = i
|
||||
break
|
||||
|
||||
if self.verbose:
|
||||
print("选择扩展条件结点：",pair_node.cond_leaf.content)
|
||||
# Update self.nodes and self.traversed
|
||||
self.nodes.pop(index) # the set of explored but unexpanded conditions. self.nodes.remove(pair_node)
|
||||
c = pair_node.cond_leaf.content # 子树所扩展结点对应的条件（一个文字的set）
|
||||
|
||||
# Mount the action node and extend BT. T = Eapand(T,c,A(c))
|
||||
if c!=goal:
|
||||
sequence_structure = ControlBT(type='>')
|
||||
sequence_structure.add_child(
|
||||
[copy.deepcopy(pair_node.cond_leaf), copy.deepcopy(pair_node.act_leaf)])
|
||||
subtree.add_child([copy.deepcopy(sequence_structure)]) # subtree 是回不断变化的，它的父亲是self.bt
|
||||
if self.verbose:
|
||||
print("完成扩展 a_node= %s,对应的新条件 c_attr= %s,mincost=%d" \
|
||||
% (cond_anc_pair.act_leaf.content.name, cond_anc_pair.cond_leaf.content,
|
||||
cond_anc_pair.cond_leaf.mincost))
|
||||
|
||||
if self.verbose:
|
||||
print("遍历所有动作, 寻找符合条件的动作")
|
||||
# 遍历所有动作, 寻找符合条件的动作
|
||||
current_mincost = pair_node.cond_leaf.mincost # 当前的最短路径是多少
|
||||
|
||||
for i in range(0, len(actions)):
|
||||
if not c & ((actions[i].pre | actions[i].add) - actions[i].del_set) <= set():
|
||||
if (c - actions[i].del_set) == c:
|
||||
if self.verbose:
|
||||
print("———— 满足条件可以扩展")
|
||||
c_attr = (actions[i].pre | c) - actions[i].add
|
||||
|
||||
# 剪枝操作,现在的条件是以前扩展过的条件的超集
|
||||
valid = True
|
||||
for j in self.traversed: # 剪枝操作
|
||||
if j <= c_attr:
|
||||
valid = False
|
||||
if self.verbose:
|
||||
print("———— --被剪枝")
|
||||
break
|
||||
|
||||
if valid:
|
||||
# 把符合条件的动作节点都放到列表里
|
||||
if self.verbose:
|
||||
print("———— -- %s 符合条件放入列表" % actions[i].name)
|
||||
c_attr_node = Leaf(type='cond', content=c_attr, mincost=current_mincost + actions[i].cost)
|
||||
a_attr_node = Leaf(type='act', content=actions[i], mincost=current_mincost + actions[i].cost)
|
||||
cond_anc_pair = CondActPair(cond_leaf=c_attr_node, act_leaf=a_attr_node)
|
||||
self.nodes.append(copy.deepcopy(cond_anc_pair)) # condition node list
|
||||
self.traversed.append(c_attr) # 重点 the set of expanded conditions
|
||||
|
||||
if self.verbose:
|
||||
print("算法结束！\n")
|
||||
return True
|
||||
|
||||
def print_solution(self):
|
||||
print("========= BT ==========") # 树的bfs遍历
|
||||
nodes_ls = []
|
||||
nodes_ls.append(self.bt)
|
||||
while len(nodes_ls) != 0:
|
||||
parnode = nodes_ls[0]
|
||||
print("Parrent:", parnode.type)
|
||||
for child in parnode.children:
|
||||
if isinstance(child, Leaf):
|
||||
print("---- Leaf:", child.content)
|
||||
elif isinstance(child, ControlBT):
|
||||
print("---- ControlBT:", child.type)
|
||||
nodes_ls.append(child)
|
||||
print()
|
||||
nodes_ls.pop(0)
|
||||
print("========= BT ==========\n")
|
||||
|
||||
# 返回所有能到达目标状态的初始状态
|
||||
def get_all_state_leafs(self):
|
||||
state_leafs=[]
|
||||
|
||||
nodes_ls = []
|
||||
nodes_ls.append(self.bt)
|
||||
while len(nodes_ls) != 0:
|
||||
parnode = nodes_ls[0]
|
||||
for child in parnode.children:
|
||||
if isinstance(child, Leaf):
|
||||
if child.type == "cond":
|
||||
state_leafs.append(child.content)
|
||||
elif isinstance(child, ControlBT):
|
||||
nodes_ls.append(child)
|
||||
nodes_ls.pop(0)
|
||||
|
||||
return state_leafs
|
||||
|
||||
|
||||
# 树的dfs
|
||||
def dfs_ptml(self,parnode):
|
||||
for child in parnode.children:
|
||||
if isinstance(child, Leaf):
|
||||
if child.type == 'cond':
|
||||
self.ptml_string += "cond "
|
||||
c_set_str = ', '.join(map(str, child.content)) + "\n"
|
||||
self.ptml_string += c_set_str
|
||||
elif child.type == 'act':
|
||||
self.ptml_string += 'act '+child.content.name+"\n"
|
||||
elif isinstance(child, ControlBT):
|
||||
if parnode.type == '?':
|
||||
self.ptml_string += "selector{\n"
|
||||
self.dfs_ptml(parnode=child)
|
||||
elif parnode.type == '>':
|
||||
self.ptml_string += "sequence{\n"
|
||||
self.dfs_ptml( parnode=child)
|
||||
self.ptml_string += '}\n'
|
||||
|
||||
|
||||
def get_ptml(self):
|
||||
self.ptml_string = "selector{\n"
|
||||
self.dfs_ptml(self.bt.children[0])
|
||||
self.ptml_string += '}\n'
|
||||
return self.ptml_string
|
||||
|
||||
|
||||
def save_ptml_file(self,file_name):
|
||||
self.ptml_string = "selector{\n"
|
||||
self.dfs_ptml(self.bt.children[0])
|
||||
self.ptml_string += '}\n'
|
||||
with open(f'./{file_name}.ptml', 'w') as file:
|
||||
file.write(self.ptml_string)
|
||||
return self.ptml_string
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 54 KiB |
|
|
@ -0,0 +1,125 @@
|
|||
|
||||
|
||||
## 代码说明
|
||||
|
||||
### 1. `BehaviorTree.py` 实现行为树叶子结点和非叶子结点的定义
|
||||
|
||||
- **Leaf**：表示叶节点，可以是动作（`act`）或条件（`cond`）。
|
||||
- **ControlBT**：代表可能包含控制节点的行为树。它们可以是选择器（`?`）、序列（`>`）、动作节点（`act`）或条件节点（`cond`）。
|
||||
- 上述两个类都包含 `tick` 方法。
|
||||
|
||||
### 2. `OptimalBTExpansionAlgorithm.py` 实现最优行为树扩展算法
|
||||
|
||||
|
||||
|
||||
定义行动类
|
||||
```python
|
||||
#定义行动类，行动包括前提、增加和删除影响
|
||||
class Action:
|
||||
def __init__(self,name='anonymous action',pre=set(),add=set(),del_set=set(),cost=1):
|
||||
self.pre=copy.deepcopy(pre)
|
||||
self.add=copy.deepcopy(add)
|
||||
self.del_set=copy.deepcopy(del_set)
|
||||
self.name=name
|
||||
self.cost=cost
|
||||
|
||||
def __str__(self):
|
||||
return self.name
|
||||
```
|
||||
|
||||
调用算法
|
||||
```python
|
||||
algo = OptBTExpAlgorithm(verbose=True)
|
||||
algo.clear()
|
||||
algo.run_algorithm(start, goal, actions) # 使用算法得到行为树在 algo.bt
|
||||
algo.print_solution() # 打印行为树
|
||||
val, obj = algo.bt.tick(state) # 执行行为树
|
||||
algo.save_ptml_file("bt.ptml") # 保存行为树为 ptml 文件
|
||||
```
|
||||
|
||||
### 3. **`tools.py`** 实现打印数据、行为树测试等模块
|
||||
|
||||
使用方法
|
||||
|
||||
```python
|
||||
print_action_data_table(goal,start,actions) # 打印所有变量
|
||||
|
||||
# 行为树鲁棒性测试，随机生成规划问题
|
||||
# 设置生成规划问题集的超参数：文字数、解深度、迭代次数
|
||||
seed=1
|
||||
literals_num=10
|
||||
depth = 10
|
||||
iters= 10
|
||||
BTTest(seed=seed,literals_num=literals_num,depth=depth,iters=iters)
|
||||
```
|
||||
|
||||
### 4. `example.py` 中设计规划案例 goals, start, actions
|
||||
|
||||
```python
|
||||
def MoveBtoB ():
|
||||
actions=[]
|
||||
a = Action(name="Move(b,ab)")
|
||||
a.pre={'Free(ab)','WayClear'}
|
||||
a.add={'At(b,ab)'}
|
||||
a.del_set= {'Free(ab)','At(b,pb)'}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name="Move(s,ab)")
|
||||
a.pre={'Free(ab)'}
|
||||
a.add={'Free(ab)','WayClear'}
|
||||
a.del_set={'Free(ab)','At(s,ps)'}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name="Move(s,as)")
|
||||
a.pre={'Free(as)'}
|
||||
a.add={'At(s,ps)','WayClear'}
|
||||
a.del_set={'Free(as)','At(s,ps)'}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
start = {'Free(ab)','Free(as)','At(b,pb)','At(s,ps)'}
|
||||
goal= {'At(b,ab)'}
|
||||
return goal,start,actions
|
||||
```
|
||||
|
||||
### 5. `opt_bt_exp_main.py` 为主函数，在此演示如何调用最优行为树扩展算法得到完全扩展最优行为树
|
||||
|
||||
初始化的时候：传入 actions (包含 pre,add,del,cost).
|
||||
调用的时候，传入 goal 状态集合 (set类型)，返回完全最优扩展行为树的 ptml 形式 (string类型)
|
||||
|
||||
```python
|
||||
actions=[
|
||||
Action(name='PutDown(Table,Coffee)', pre={'Holding(Coffee)','At(Robot,Table)'}, add={'At(Table,Coffee)','NotHolding'}, del_set={'Holding(Coffee)'}, cost=1)
|
||||
…………
|
||||
]
|
||||
algo = BTOptExpInterface(actions)
|
||||
|
||||
goal = {'At(Table,Coffee)'}
|
||||
ptml_string = algo.process(goal,start)
|
||||
print(ptml_string)
|
||||
|
||||
```
|
||||
两种检测方法，用于检测当前状态 `start` 能否到达目标状态 `goal`
|
||||
|
||||
```python
|
||||
# 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!")
|
||||
|
||||
```
|
||||
|
||||
|
|
@ -0,0 +1,174 @@
|
|||
|
||||
from zoo.opt_bt_expansion.OptimalBTExpansionAlgorithm import Action
|
||||
|
||||
|
||||
|
||||
def MakeCoffee():
|
||||
actions=[
|
||||
Action(name='Put(Table,Coffee)', pre={'Holding(Coffee)','At(Table)'}, add={'At(Table,Coffee)','NotHolding'}, del_set={'Holding(Coffee)'}, cost=1),
|
||||
Action(name='Put(Table,VacuumCup)', pre={'Holding(VacuumCup)','At(Table)'}, add={'At(Table,VacuumCup)','NotHolding'}, del_set={'Holding(VacuumCup)'}, cost=1),
|
||||
|
||||
Action(name='Grasp(Coffee)', pre={'NotHolding','At(Coffee)'}, add={'Holding(Coffee)'}, del_set={'NotHolding'}, cost=1),
|
||||
|
||||
Action(name='MoveTo(Table)', pre={'Exist(Table)'}, add={'At(Table)'}, del_set={'At(FrontDesk)','At(Coffee)','At(CoffeeMachine)'}, cost=1),
|
||||
Action(name='MoveTo(Coffee)', pre={'Exist(Coffee)'}, add={'At(Coffee)'}, del_set={'At(FrontDesk)','At(Table)','At(CoffeeMachine)'}, cost=1),
|
||||
Action(name='MoveTo(CoffeeMachine)', pre={'Exist(CoffeeMachine)'}, add={'At(CoffeeMachine)'}, del_set={'At(FrontDesk)','At(Coffee)','At(Table)'}, cost=1),
|
||||
|
||||
Action(name='OpCoffeeMachine', pre={'At(CoffeeMachine)','NotHolding'}, add={'Exist(Coffee)','At(Coffee)'}, del_set=set(), cost=1),
|
||||
]
|
||||
|
||||
start = {'At(FrontDesk)','Holding(VacuumCup)','Exist(Table)','Exist(CoffeeMachine)','Exist(FrontDesk)'}
|
||||
goal = {'At(Table,Coffee)'}
|
||||
return goal,start,actions
|
||||
|
||||
# 本例子中，将 VacuumCup 放到 FrontDesk，比 MoveTo(Table) 再 Put(Table,VacuumCup) 的 cost 要小
|
||||
def MakeCoffeeCost():
|
||||
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),
|
||||
]
|
||||
|
||||
start = {'At(Robot,Bar)','Holding(VacuumCup)','Available(Table)','Available(CoffeeMachine)','Available(FrontDesk)'}
|
||||
goal = {'At(Table,Coffee)'}
|
||||
|
||||
return goal,start,actions
|
||||
|
||||
|
||||
# test
|
||||
def Test():
|
||||
actions=[
|
||||
Action(name='a1', pre={6}, add={0,2,4}, del_set={1,5}, cost=1),
|
||||
Action(name='a2', pre=set(), add={0,1}, del_set=set(), cost=1),
|
||||
Action(name='a3', pre={1,6}, add={0,2,3,5}, del_set={1,6}, cost=1),
|
||||
Action(name='a4', pre={0,2,3}, add={4,5}, del_set={0,6}, cost=1),
|
||||
Action(name='a5', pre={0,1,4}, add={2,3,6}, del_set={0}, cost=1),
|
||||
]
|
||||
|
||||
start = {1,2,6}
|
||||
goal={0,1,2,4,6}
|
||||
return goal,start,actions
|
||||
|
||||
# def Test():
|
||||
# actions=[
|
||||
# Action(name='a1', pre={2}, add={1}, del_set=set(), cost=1),
|
||||
# Action(name='a2', pre=set(), add={1}, del_set={0,2}, cost=1),
|
||||
# Action(name='a3', pre={1}, add=set(), del_set={0,2}, cost=1),
|
||||
# Action(name='a4', pre=set(), add={0}, del_set=set(), cost=1),
|
||||
# Action(name='a5', pre={1}, add={0,2}, del_set={1}, cost=1),
|
||||
# Action(name='a6', pre={1}, add=set(), del_set={0,1,2}, cost=1),
|
||||
# Action(name='a7', pre={1}, add={2}, del_set={0, 2}, cost=1),
|
||||
# ]
|
||||
#
|
||||
# start = {1,2}
|
||||
# goal={0,1}
|
||||
# return goal,start,actions
|
||||
|
||||
|
||||
# todo: 最原始的例子
|
||||
def MoveBtoB_num ():
|
||||
actions=[]
|
||||
a = Action(name='a1')
|
||||
a.pre={1,4}
|
||||
a.add={"c_goal"}
|
||||
a.del_set={1,4}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name='a2')
|
||||
a.pre={1,2,3}
|
||||
a.add={"c_goal"}
|
||||
a.del_set={1,2,3}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name='a3')
|
||||
a.pre={1,2}
|
||||
a.add={4}
|
||||
a.del_set={2}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name='a4')
|
||||
a.pre={"c_start"}
|
||||
a.add={1,2,3}
|
||||
a.del_set={"c_start",4}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
start = {"c_start"}
|
||||
goal={"c_goal"}
|
||||
return goal,start,actions
|
||||
|
||||
|
||||
# todo: 最原始的例子
|
||||
def MoveBtoB ():
|
||||
actions=[]
|
||||
a = Action(name="Move(b,ab)") #'movebtob'
|
||||
a.pre={'Free(ab)','WayClear'} #{1,2}
|
||||
a.add={'At(b,ab)'} #{3}
|
||||
a.del_set= {'Free(ab)','At(b,pb)'} #{1,4}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name="Move(s,ab)") #'moveatob'
|
||||
a.pre={'Free(ab)'} #{1}
|
||||
a.add={'Free(ab)','WayClear'} #{5,2}
|
||||
a.del_set={'Free(ab)','At(s,ps)'} #{1,6}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name="Move(s,as)") #'moveatoa'
|
||||
a.pre={'Free(as)'} #{7}
|
||||
a.add={'At(s,ps)','WayClear'} #{8,2}
|
||||
a.del_set={'Free(as)','At(s,ps)'} #{7,6}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
start = {'Free(ab)','Free(as)','At(b,pb)','At(s,ps)'} #{1,7,4,6}
|
||||
goal= {'At(b,ab)'} #{3}
|
||||
return goal,start,actions
|
||||
|
||||
|
||||
# 小蔡师兄论文里的例子
|
||||
def Cond2BelongsToCond3():
|
||||
actions=[]
|
||||
a = Action(name='a1')
|
||||
a.pre={1,4}
|
||||
a.add={"c_goal"}
|
||||
a.del_set={1,4}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name='a2')
|
||||
a.pre={1,2,3}
|
||||
a.add={"c_goal"}
|
||||
a.del_set={1,2,3}
|
||||
a.cost = 100
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name='a3')
|
||||
a.pre={1,2}
|
||||
a.add={4}
|
||||
a.del_set={2}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
a=Action(name='a4')
|
||||
a.pre={"c_start"}
|
||||
a.add={1,2,3}
|
||||
a.del_set={"c_start",4}
|
||||
a.cost = 1
|
||||
actions.append(a)
|
||||
|
||||
start = {"c_start"}
|
||||
goal={"c_goal"}
|
||||
return goal,start,actions
|
||||
|
||||
|
|
@ -1,7 +1,4 @@
|
|||
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 zoo.opt_bt_expansion.OptimalBTExpansionAlgorithm import Action,OptBTExpAlgorithm,state_transition # 调用最优行为树扩展算法
|
||||
from opt_bt_expansion.examples import *
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,167 @@
|
|||
|
||||
|
||||
from tabulate import tabulate
|
||||
import numpy as np
|
||||
import random
|
||||
from zoo.opt_bt_expansion.OptimalBTExpansionAlgorithm import Action,OptBTExpAlgorithm
|
||||
import time
|
||||
|
||||
|
||||
def print_action_data_table(goal,start,actions):
|
||||
data = []
|
||||
for a in actions:
|
||||
data.append([a.name ,a.pre ,a.add ,a.del_set ,a.cost])
|
||||
data.append(["Goal" ,goal ," " ,"Start" ,start])
|
||||
print(tabulate(data, headers=["Name", "Pre", "Add" ,"Del" ,"Cost"], tablefmt="fancy_grid")) # grid plain simple github fancy_grid
|
||||
|
||||
|
||||
# 从状态随机生成一个行动
|
||||
def generate_from_state(act,state,num):
|
||||
for i in range(0,num):
|
||||
if i in state:
|
||||
if random.random() >0.5:
|
||||
act.pre.add(i)
|
||||
if random.random() >0.5:
|
||||
act.del_set.add(i)
|
||||
continue
|
||||
if random.random() > 0.5:
|
||||
act.add.add(i)
|
||||
continue
|
||||
if random.random() >0.5:
|
||||
act.del_set.add(i)
|
||||
|
||||
def print_action(act):
|
||||
print (act.pre)
|
||||
print(act.add)
|
||||
print(act.del_set)
|
||||
|
||||
|
||||
|
||||
#行为树测试代码
|
||||
def BTTest(seed=1,literals_num=10,depth=10,iters=10,total_count=1000):
|
||||
print("============= BT Test ==============")
|
||||
random.seed(seed)
|
||||
# 设置生成规划问题集的超参数：文字数、解深度、迭代次数
|
||||
literals_num=literals_num
|
||||
depth = depth
|
||||
iters= iters
|
||||
total_tree_size = []
|
||||
total_action_num = []
|
||||
total_state_num = []
|
||||
total_steps_num=[]
|
||||
#fail_count=0
|
||||
#danger_count=0
|
||||
success_count =0
|
||||
failure_count = 0
|
||||
planning_time_total = 0.0
|
||||
# 实验1000次
|
||||
for count in range (total_count):
|
||||
|
||||
action_num = 1
|
||||
|
||||
# 生成一个规划问题，包括随机的状态和行动，以及目标状态
|
||||
states = []
|
||||
actions = []
|
||||
start = generate_random_state(literals_num)
|
||||
state = start
|
||||
states.append(state)
|
||||
#print (state)
|
||||
for i in range (0,depth):
|
||||
a = Action()
|
||||
generate_from_state(a,state,literals_num)
|
||||
if not a in actions:
|
||||
a.name = "a"+str(action_num)
|
||||
action_num+=1
|
||||
actions.append(a)
|
||||
state = state_transition(state,a)
|
||||
if state in states:
|
||||
pass
|
||||
else:
|
||||
states.append(state)
|
||||
#print(state)
|
||||
|
||||
goal = states[-1]
|
||||
state = start
|
||||
for i in range (0,iters):
|
||||
a = Action()
|
||||
generate_from_state(a,state,literals_num)
|
||||
if not a in actions:
|
||||
a.name = "a"+str(action_num)
|
||||
action_num+=1
|
||||
actions.append(a)
|
||||
state = state_transition(state,a)
|
||||
if state in states:
|
||||
pass
|
||||
else:
|
||||
states.append(state)
|
||||
state = random.sample(states,1)[0]
|
||||
|
||||
# 选择测试本文算法btalgorithm，或对比算法weakalgorithm
|
||||
algo = OptBTExpAlgorithm()
|
||||
#algo = Weakalgorithm()
|
||||
start_time = time.time()
|
||||
# print_action_data_table(goal, start, list(actions))
|
||||
if algo.run_algorithm(start, goal, actions):#运行算法，规划后行为树为algo.bt
|
||||
total_tree_size.append( algo.bt.count_size()-1)
|
||||
# algo.print_solution() # 打印行为树
|
||||
else:
|
||||
print ("error")
|
||||
end_time = time.time()
|
||||
planning_time_total += (end_time-start_time)
|
||||
|
||||
#开始从初始状态运行行为树，测试
|
||||
state=start
|
||||
steps=0
|
||||
val, obj = algo.bt.tick(state)#tick行为树，obj为所运行的行动
|
||||
while val !='success' and val !='failure':#运行直到行为树成功或失败
|
||||
state = state_transition(state,obj)
|
||||
val, obj = algo.bt.tick(state)
|
||||
if(val == 'failure'):
|
||||
print("bt fails at step",steps)
|
||||
steps+=1
|
||||
if(steps>=500):#至多运行500步
|
||||
break
|
||||
if not goal <= state:#错误解，目标条件不在执行后状态满足
|
||||
#print ("wrong solution",steps)
|
||||
failure_count+=1
|
||||
|
||||
else:#正确解，满足目标条件
|
||||
#print ("right solution",steps)
|
||||
success_count+=1
|
||||
total_steps_num.append(steps)
|
||||
algo.clear()
|
||||
total_action_num.append(len(actions))
|
||||
total_state_num.append(len(states))
|
||||
|
||||
print ("success:",success_count,"failure:",failure_count)#算法成功和失败次数
|
||||
print("Total Tree Size: mean=",np.mean(total_tree_size), "std=",np.std(total_tree_size, ddof=1))#1000次测试树大小
|
||||
print ("Total Steps Num: mean=",np.mean(total_steps_num),"std=",np.std(total_steps_num,ddof=1))
|
||||
print ("Average number of states:",np.mean(total_state_num))#1000次问题的平均状态数
|
||||
print ("Average number of actions",np.mean(total_action_num))#1000次问题的平均行动数
|
||||
print("Planning Time Total:",planning_time_total,planning_time_total/1000.0)
|
||||
print("============ End BT Test ===========")
|
||||
|
||||
# xiao cai
|
||||
# success: 1000 failure: 0
|
||||
# Total Tree Size: mean= 35.303 std= 29.71336526001515
|
||||
# Total Steps Num: mean= 1.898 std= 0.970844240101644
|
||||
# Average number of states: 20.678
|
||||
# Average number of actions 20.0
|
||||
# Planning Time Total: 0.6280641555786133 0.0006280641555786133
|
||||
|
||||
# our start
|
||||
# success: 1000 failure: 0
|
||||
# Total Tree Size: mean= 17.945 std= 12.841997192488865
|
||||
# Total Steps Num: mean= 1.785 std= 0.8120556843187752
|
||||
# Average number of states: 20.678
|
||||
# Average number of actions 20.0
|
||||
# Planning Time Total: 1.4748523235321045 0.0014748523235321046
|
||||
|
||||
# our
|
||||
# success: 1000 failure: 0
|
||||
# Total Tree Size: mean= 48.764 std= 20.503626574406358
|
||||
# Total Steps Num: mean= 1.785 std= 0.8120556843187752
|
||||
# Average number of states: 20.678
|
||||
# Average number of actions 20.0
|
||||
# Planning Time Total: 3.3271877765655518 0.0033271877765655516
|
||||
|
||||
Loading…
Reference in New Issue