3 from __future__
import print_function
5 from robocup_knowledge
import knowledge_loader
6 common = knowledge_loader.load_knowledge(
"common")
8 not_understood_sentences = [
9 "I'm so sorry! Can you please speak clearly and fluently? And wait for the ping!",
10 "I am deeply sorry. Please try again, but wait for the ping!",
11 "You and I have communication issues. Speak clearly!",
12 "All this noise is messing with my audio. Try again."
15 initial_pose =
"initial_pose"
16 starting_pose =
"eegpsr_starting_point1"
17 exit_waypoint =
"exit_3_rips"
28 T[A] -> COURTESY_PREFIX C[A] | C[A]
30 C[{"actions": <A1, A2, A3>}] -> VP[A1] VP[A2] and VPT[A3]
34 COURTESY_PREFIX -> robot please | could you | could you please
45 PPN_PERSON -> him | her
48 NUMBER -> one | two | three
50 MANIPULATION_PP -> on | to
53 for room
in common.location_rooms:
54 grammar +=
"\nROOM[{'type': 'room', 'id': '%s'}] -> %s" % (room, room)
57 grammar +=
'\nLOCATION[{"id": "%s"}] -> %s' % (loc, loc)
59 grammar +=
'\n ROOM_OR_LOCATION[X] -> ROOM[X] | LOCATION[X]'
61 for obj
in common.object_names:
62 grammar +=
"\nNAMED_OBJECT[{'type': '%s'}] -> %s" % (obj, obj)
65 grammar +=
'\nMANIPULATION_AREA_LOCATION[{"id": "%s"}] -> MANIPULATION_PP the %s' % (loc, loc)
67 for cat
in common.object_categories:
68 grammar +=
"\nOBJECT_CATEGORY[{'category': '%s'}] -> %s" % (cat, cat)
70 for name
in common.names:
71 grammar +=
"\nNAMED_PERSON[{'type': 'person', 'id': '%s'}] -> %s" % (name, name)
72 grammar +=
"\nPERSON_AT_LOCATION[{'type': 'person', 'id': '%s', 'location': {'id': 'gpsr_entrance', 'type': 'waypoint'}}] -> %s at the entrance" % (
75 grammar +=
"\nPERSON_AT_LOCATION[{'type': 'person', 'id': '%s', 'location': {'id': %s}}] -> %s at the %s" % (name, loc, name, loc)
77 grammar +=
'\nLOCATION[{"id": "gpsr_entrance", "type": "waypoint"}] -> entrance'
86 V_FIND -> find | locate | look for | pinpoint | spot
88 TYPE_OR_CATEGORY -> NAMED_OBJECT | OBJECT_CATEGORY
89 UNNAMED_PERSON -> a person | someone
91 VP[{"action": "find", "object": {'type': 'person'}}] -> V_FIND UNNAMED_PERSON
92 VP[{"action": "find", "object": X}] -> V_FIND NAMED_PERSON[X]
93 VP[{"action": "find", "object": X, "source-location": Y}] -> V_FIND NAMED_PERSON[X] MEETING_PP the ROOM_OR_LOCATION[Y]
95 VP[{"action": "find", "object": X, "source-location": Y}] -> V_FIND DET TYPE_OR_CATEGORY[X] in the ROOM[Y]
97 VP[{"action": "find"}] -> V_FIND DET object
98 VP[{"action": "find", "source-location": Y}] -> V_FIND DET object in the ROOM[Y]
100 VP[{"action": "find", "object": X}] -> V_FIND DET TYPE_OR_CATEGORY[X]
111 V_FOLLOW -> come behind | come after | follow | go after | go behind
113 VP[{"action": "follow", "target": {"type": "reference"}}] -> V_FOLLOW PPN_PERSON
123 V_GUIDE -> guide | escort | take | lead | accompany | conduct
125 VPS[{"action": "guide", "object": {"type": "reference"}}] -> V_GUIDE PPN_PERSON
126 VP[{"action": "guide", "target-location": Y, "object": {"type": "reference"}}] -> V_GUIDE PPN_PERSON to the ROOM_OR_LOCATION[Y]
137 V_GOTO -> go to | navigate to | enter to
139 VP[{"action": "navigate-to", "target-location": X}] -> V_GOTO the ROOM_OR_LOCATION[X]
150 V_PICKUP -> get | grasp | take | pick up | grab | retrieve
152 VP[{"action": "pick-up", "object": X}] -> V_PICKUP DET TYPE_OR_CATEGORY[X]
153 VP[{"action": "pick-up", "object": X, "source-location": Y}] -> V_PICKUP DET TYPE_OR_CATEGORY[X] from the LOCATION[Y]
163 OPERATOR[{"type": "person", "id": "operator"}] -> me
164 BRING_NAME -> OPERATOR | NAMED_PERSON
166 OBJECT_TO_BE_BROUGHT -> NAMED_OBJECT | DET NAMED_OBJECT
168 V_BRING -> bring | deliver | give | hand over | hand
172 VP[{"action": "hand-over", "target-location": Y, "object": Z}] -> V_BRING OPERATOR[Y] DET NAMED_OBJECT[Z]
173 VP[{"action": "hand-over", "source-location": X, "target-location": Y, "object": Z}] -> V_BRING OPERATOR[Y] DET NAMED_OBJECT[Z] from the LOCATION[X]
174 VP[{"action": "hand-over", "source-location": X, "target-location": Y, "object": Z}] -> V_BRING to PERSON_AT_LOCATION[Y] DET NAMED_OBJECT[Z] from the LOCATION[X]
176 VP[{"action": "hand-over", "target-location": Y, "object": Z}] -> V_BRING DET NAMED_OBJECT[Z] to PERSON_AT_LOCATION[Y]
177 VP[{"action": "hand-over", "target-location": Y, "object": Z}] -> V_BRING DET NAMED_OBJECT[Z] to OPERATOR[Y]
179 VPS[{"action": "hand-over", "target-location": X, "object": {"type": "reference"}}] -> V_BRING PPN_OBJECT to PERSON_AT_LOCATION[X]
180 VPS[{"action": "hand-over", "target-location": X, "object": {"type": "reference"}}] -> V_BRING PPN_OBJECT to OPERATOR[X]
190 V_PLACE -> put | place | leave | set
192 VP[{"action": "place", "object": X, "target-location": Y}] -> V_PLACE NAMED_OBJECT[X] MANIPULATION_AREA_LOCATION[Y]
193 VP[{"action": "place", "object": X, "target-location": Y}] -> V_PLACE DET NAMED_OBJECT[X] MANIPULATION_AREA_LOCATION[Y]
195 VP[{"action": "place", "target-location": X, "object": {"type": "reference"}}] -> V_PLACE PPN_OBJECT on the LOCATION[X]
196 VP[{"action": "place", "object": {"type": "reference"}}] -> V_PLACE PPN_OBJECT to the ROOM
207 V_SAY_UNDEFINED -> speak | say something
209 VPS[{"action": "say"}] -> V_SAY_UNDEFINED
210 VPS[{"action": "say", "sentence": X}] -> V_SAY SAY_SENTENCE[X]
213 grammar +=
'\nSAY_SENTENCE["time"] -> the time'
214 grammar +=
'\nSAY_SENTENCE["team_name"] -> your teams name'
215 grammar +=
'\nSAY_SENTENCE["country"] -> your teams country'
216 grammar +=
'\nSAY_SENTENCE["team_affiliation"] -> your teams affiliation'
217 grammar +=
'\nSAY_SENTENCE["day_of_month"] -> the day of the month'
218 grammar +=
'\nSAY_SENTENCE["day_of_week"] -> the day of the week'
219 grammar +=
'\nSAY_SENTENCE["today"] -> what day is today'
220 grammar +=
'\nSAY_SENTENCE["tomorrow"] -> what day is tomorrow'
221 grammar +=
'\nSAY_SENTENCE["joke"] -> a joke'
222 grammar +=
'\nSAY_SENTENCE["something_about_self"] -> something about yourself'
223 grammar +=
'\nSAY_SENTENCE["electric_sheep"] -> whether you dream or not on electric sheep'
232 V_ANSWER_QUESTION -> answer a question
233 VPS[{"action": "answer-question"}] -> V_ANSWER_QUESTION
237 if __name__ ==
"__main__":
238 print(
"GPSR Grammar:\n\n{}\n\n".format(grammar))
240 from grammar_parser.cfgparser
import CFGParser
243 grammar_parser = CFGParser.fromstring(grammar)
245 if len(sys.argv) > 2:
246 sentence =
" ".join(sys.argv[2:])
248 sentence = grammar_parser.get_random_sentence(
"T")
250 print(
"Parsing sentence:\n\n{}\n\n".format(sentence))
252 result = grammar_parser.parse(
"T", sentence)
254 print(
"Result:\n\n{}".format(result))