def update_kb(self):
kus = KnowledgeUpdateServiceArrayRequest()
# Get info from KB functions and propositions (to know type of variable)
# Fill update
self.dump_cache_mutex.acquire(True)
self.mutex.acquire(True)
sensed_predicates = self.sensed_topics.copy()
self.mutex.release()
self.srv_mutex.acquire(True)
sensed_predicates.update(self.sensed_services.copy())
self.srv_mutex.release()
for predicate, (val, changed,
updated) in sensed_predicates.iteritems():
if updated:
continue
if predicate in self.sensed_topics:
self.mutex.acquire(True)
self.sensed_topics[predicate] = (
self.sensed_topics[predicate][0], False, True
) # Set to not changed and updated KB
self.mutex.release()
else:
self.srv_mutex.acquire(True)
self.sensed_services[predicate] = (
self.sensed_services[predicate][0], False, True
) # Set to not changed and updated KB
self.srv_mutex.release()
predicate_info = predicate.split(':')
ki = KnowledgeItem()
ki.attribute_name = predicate_info.pop(0)
if type(val) is bool:
ki.knowledge_type = ki.FACT
ki.is_negative = not val
else:
ki.knowledge_type = ki.FUNCTION
ki.function_value = val
# TODO what to do if no parameters specified? iterate over all the instantiated parameters and add them?
for i, param in enumerate(predicate_info):
kv = KeyValue()
kv.key = 'p' + str(i)
kv.value = param
ki.values.append(kv)
kus.update_type += np.array(kus.ADD_KNOWLEDGE).tostring()
kus.knowledge.append(ki)
self.dump_cache_mutex.release()
# Update the KB with the full array
if len(kus.update_type) > 0:
try:
self.update_kb_srv.call(kus)
except Exception as e:
rospy.logerr(
"KCL (SensingInterface) Failed to update knowledge base: %s"
% e.message)
def _make_predicate(type_name, parameters):
new_type_name, is_negative = _is_predicate_negative(type_name)
kb_item = KnowledgeItem()
kb_item.knowledge_type = KB_ITEM_FACT
kb_item.is_negative = is_negative
kb_item.attribute_name = new_type_name
kb_item.values = dict_to_keyval(parameters)
return kb_item
def publish_predicates(self, preds):
ka = []
for p in preds:
k = KnowledgeItem()
k.knowledge_type = k.FACT
k.attribute_name = p.head.lower()
for i in xrange(len(p.args)):
kv = KeyValue()
kv.key = self.predicate_key_name[(k.attribute_name, i)]
kv.value = p.args[i].lower()
k.values.append(kv)
ka.append(k)
k.is_negative = not p.isTrue
self.publish(ka)
def publish_predicates(self, preds): ka = [] for p in preds: k = KnowledgeItem() k.knowledge_type = k.FACT k.attribute_name = p.head.lower() for i in xrange(len(p.args)): kv = KeyValue() kv.key = self.predicate_key_name[(k.attribute_name, i)] kv.value = p.args[i].lower() k.values.append(kv) ka.append(k) k.is_negative = not p.isTrue self.publish(ka)
def predicate_maker(attr_name, attr_key, attr_value, is_negative=None):
ki = KnowledgeItem()
ki.knowledge_type = 1
ki.attribute_name = attr_name
ki_values = []
if type(attr_key) == list:
for key, value in zip(attr_key, attr_value):
kv = KeyValue()
kv.key = key
kv.value = value
ki_values.append(kv)
else:
kv = KeyValue()
kv.key = attr_key
kv.value = attr_value
ki_values.append(kv)
ki.values = ki_values
if is_negative:
ki.is_negative = is_negative
return ki
