New: 新增了自动生成bt-expansion目标状态的实现
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# the empty string '' represents robot holds nothing
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Object = ['Coffee', 'Water', 'Dessert', 'Softdrink', 'BottledDrink', 'Yogurt', 'ADMilk', 'MilkDrink', 'Milk',
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'VacuumCup', '']
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Place = ['Bar', 'WaterTable', 'CoffeeTable', 'Bar2', 'Table1', 'Table2', 'Table3']
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Entity = ['Robot', 'Customer']
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Operable = ['AC', 'ACTemperature', 'HallLight', 'TubeLight', 'Curtain']
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import random
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def single_predict_generation(oplist_1, oplist_2, predict_pattern) -> str:
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index_1 = random.randint(0, len(oplist_1) - 1)
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if oplist_2:
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index_2 = random.randint(0, len(oplist_2) - 1)
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match predict_pattern:
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case 'at':
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return f'At({oplist_1[index_1]}, {oplist_2[index_2]})'
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case 'is':
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return f'Is({oplist_1[index_1]}, {oplist_2[index_2]})'
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case 'hold':
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return f'Holding({oplist_1[index_1]})'
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case 'on':
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return f'On({oplist_1[index_1]}, {oplist_2[index_2]})'
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case _:
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raise RuntimeError('Incorrect predict pattern!')
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def generate_goal_states(vln_num: int, vlm_num: int, opentask_num: int):
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# res stores lists of sets, while each state represent in set.
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res = []
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# goal states for VLN
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for i in range(vln_num):
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res.append({single_predict_generation(['Robot'], Place, 'at')})
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# goal states for VLM
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for i in range(int(vlm_num)):
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for j in range(int(vlm_num)):
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res.append(
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{
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single_predict_generation(['Robot'], Place, 'at'),
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single_predict_generation(Operable, ['0', '1'], 'is')
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}
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)
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# goal states for Open-task-1
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for i in range(int(opentask_num)):
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for j in range(int(opentask_num)):
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res.append(
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{
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single_predict_generation(['Robot'], Place, 'at'),
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single_predict_generation(Object, Place, 'on')
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}
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)
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# print(res)
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# print(len(res))
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return res
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generate_goal_states(30, 6, 6)
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