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Commit 1ec5a206 authored by bav6096's avatar bav6096
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more cleanup

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CMakeLists.txt
+ 3
− 3
View file @ 1ec5a206
...@@ -161,10 +161,10 @@ include_directories( ...@@ -161,10 +161,10 @@ include_directories(
## Mark executable scripts (Python etc.) for installation ## Mark executable scripts (Python etc.) for installation
## in contrast to setup.py, you can choose the destination ## in contrast to setup.py, you can choose the destination
catkin_install_python(PROGRAMS catkin_install_python(PROGRAMS
nodes/watchdog
nodes/monitor_distance nodes/monitor_distance
nodes/monitor_test2 nodes/monitor_test_1
nodes/monitor_test1 nodes/monitor_test_2
nodes/monitor_test_3
DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION} DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
) )
......
launch/monitor_distance.launch 0 → 100644
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View file @ 1ec5a206
<launch>
<node pkg="monitoring" type="monitor_distance" name="monitor_distance" />
</launch>
\ No newline at end of file
launch/system.launch → launch/monitoring.launch
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View file @ 1ec5a206
<launch> <launch>
<!--
<include file="$(find monitoring)/launch/translator.launch" />
-->
<include file="$(find monitoring)/launch/monitor_distance.launch" />
<include file="$(find monitoring)/launch/monitor_test_1.launch" /> <include file="$(find monitoring)/launch/monitor_test_1.launch" />
<include file="$(find monitoring)/launch/monitor_test_2.launch" /> <include file="$(find monitoring)/launch/monitor_test_2.launch" />
<include file="$(find monitoring)/launch/monitor_test_3.launch" /> <include file="$(find monitoring)/launch/monitor_test_3.launch" />
<include file="$(find monitoring)/launch/translator.launch" />
<include file="$(find monitoring)/launch/watchdog.launch" />
</launch> </launch>
\ No newline at end of file
launch/watchdog.launch deleted 100644 → 0
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− 14
View file @ f04ca230
<launch>
<node pkg="monitoring" type="watchdog" name="watchdog">
<!-- example of how to set an aggregation strategy for a metric -->
<rosparam param="aggregation_strategy_metrics">
example_1: 10
example_2: 10
test_domain_1: 1
test_domain_2: 2
</rosparam>
<!-- set the default aggregation strategy for domains -->
<param name="aggregation_strategy_domains" value="1" type="int" />
<param name="wdg_freq" value="2.0" type="double" />
</node>
</launch>
\ No newline at end of file
nodes/monitor_distance
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View file @ 1ec5a206
#!/usr/bin/env python #!/usr/bin/env python
import rospy import rospy
from sensor_msgs.msg import LaserScan from sensor_msgs.msg import LaserScan
from monitoring.monitor import Monitor from monitoring.monitor import Monitor
...@@ -16,6 +17,7 @@ if __name__ == '__main__': ...@@ -16,6 +17,7 @@ if __name__ == '__main__':
rospy.init_node("monitor_distance") rospy.init_node("monitor_distance")
monitor = Monitor() monitor = Monitor()
distance = float("inf")
rate = rospy.Rate(10) rate = rospy.Rate(10)
while not rospy.is_shutdown(): while not rospy.is_shutdown():
......
nodes/watchdog deleted 100755 → 0
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View file @ f04ca230
#!/usr/bin/env python
import rospy
from monitoring.watchdog import Watchdog
if __name__ == '__main__':
try:
rospy.init_node("watchdog")
watchdog = Watchdog()
rospy.spin()
except rospy.ROSInterruptException:
pass
src/monitoring/watchdog.py deleted 100755 → 0
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− 142
View file @ f04ca230
#!/usr/bin/env python
import rospy
from monitoring.msg import Monitoring
class Watchdog:
def __init__(self):
self.sub = rospy.Subscriber("/monitoring", Monitoring, self.update_log)
# Stores the most current values of each metric.
self.log = {}
# Strategies that specify how the critical level of each metric should be aggregated in a domain.
# It is possible to specify a different aggregation strategy for every single domain.
self.aggregation_strategy_metrics = rospy.get_param("/watchdog/aggregation_strategy_metrics")
# Dictionary that stores the aggregated critical levels of the metrics of a domain.
self.aggregated_metrics = {}
# Strategy that specifies how the critical levels of all domains should be aggregated.
self.aggregation_strategy_domains = rospy.get_param("/watchdog/aggregation_strategy_domains")
# Variable that stores the aggregated critical level of all domains.
self.aggregated_domains = None
# Frequency at which the metrics in the log are aggregated.
wdg_freq = rospy.get_param("/watchdog/wdg_freq", 1.0)
if not wdg_freq > 0.0:
rospy.logwarn(
"Watchdog: The frequency at which the metrics of the robot are aggregated must be greater then 0! "
"Using 1 as frequency!")
wdg_freq = 1.0
self.timer = rospy.Timer(rospy.Duration(1.0 / wdg_freq), self.update_condition)
# TODO: Think about efficiency!
def update_log(self, monitoring):
origin = monitoring.origin
metric = monitoring.metric
domain = metric.domain
label = metric.label
value = metric.value
unit = metric.unit
error = metric.error
if domain in self.log:
if origin in self.log[domain]:
self.log[domain][origin].update({label: {"value": value, "unit": unit, "error": error}})
else:
self.log[domain][origin] = {}
self.log[domain][origin][label] = {"value": value, "unit": unit, "error": error}
else:
self.log[domain] = {}
self.log[domain][origin] = {}
self.log[domain][origin][label] = {"value": value, "unit": unit, "error": error}
def update_condition(self, event):
self.aggregate_metrics()
self.aggregate_domains()
# TODO: Add more modes!
def aggregate_metrics(self):
for domain in self.log:
if domain in self.aggregation_strategy_metrics:
# Strategy 1: Take the highest error level of any metric in a domain.
if self.aggregation_strategy_metrics[domain] == 1:
highest_error = 0.0
for origin in self.log[domain]:
for label in self.log[domain][origin]:
local_error = self.log[domain][origin][label]["error"]
if local_error > highest_error:
highest_error = local_error
self.aggregated_metrics.update({domain: highest_error})
# Strategy 2: Take the lowest error level of any metric in a domain.
elif self.aggregation_strategy_metrics[domain] == 2:
lowest_error = 1.0
for origin in self.log[domain]:
for label in self.log[domain][origin]:
local_error = self.log[domain][origin][label]["error"]
if local_error < lowest_error:
lowest_error = local_error
self.aggregated_metrics.update({domain: lowest_error})
else:
rospy.logwarn("Watchdog: The specified method for aggregating metrics is not recognised!")
# Default strategy: Take the average error level of every metric in a domain.
else:
count = 0.001
aggregated_error = 0.0
for origin in self.log[domain]:
for label in self.log[domain][origin]:
count = count + 1
aggregated_error = aggregated_error + self.log[domain][origin][label]["error"]
quotient = aggregated_error / count
self.aggregated_metrics.update({domain: quotient})
# TODO: Add more modes!
def aggregate_domains(self):
# Strategy 1: Take the highest error level of any domain.
if self.aggregation_strategy_domains == 1:
highest_error = 0.0
for domain in self.aggregated_metrics:
local_error = self.aggregated_metrics[domain]
if local_error > highest_error:
highest_error = local_error
self.aggregated_domains = highest_error
# Strategy 2: Take the lowes error level of any domain.
elif self.aggregation_strategy_domains == 2:
lowest_error = 1.0
for domain in self.aggregated_metrics:
local_error = self.aggregated_metrics[domain]
if local_error < lowest_error:
lowest_error = local_error
self.aggregated_domains = lowest_error
# Default strategy: Take the average error level of every domain.
else:
count = 0.001
aggregated_error = 0.0
for domain in self.aggregated_metrics:
count = count + 1
aggregated_error = aggregated_error + self.aggregated_metrics[domain]
quotient = aggregated_error / count
self.aggregated_domains = quotient
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