perception_monitor.py File Reference

Go to the source code of this file.

Classes
class	kelsey_sandbox.perception_monitor.ArmPerceptionMonitor
	Monitors perception channels on the robot arms. More...
class	kelsey_sandbox.perception_monitor.PeriodicLogger
	Periodically logs the output of a callback function by calling it at a certain rate and gathering up the results into a list. More...
class	kelsey_sandbox.perception_monitor.PeriodicMonitor
	Periodically monitors the output of a callback function by calling it at a certain rate and compares it with a provided model to insure the value doesn't vary greatly within a degree of tolerance provided by the variance function. More...
Namespaces
namespace	kelsey_sandbox::perception_monitor
Functions
def	kelsey_sandbox::perception_monitor.accel_state_processor
	Processes the AccelerometerState message, returning an average of the sample values and the timestamp in nanoseconds.
def	kelsey_sandbox::perception_monitor.generate_mean_grasp
	Generates model functions of all the perceptions over several identical trajectories.
def	kelsey_sandbox::perception_monitor.joints_state_processor
	Callback for /joint_states topic.
def	kelsey_sandbox::perception_monitor.log
def	kelsey_sandbox::perception_monitor.pressure_state_processor
def	kelsey_sandbox::perception_monitor.split_signals
Variables
tuple	kelsey_sandbox::perception_monitor.apm = ArmPerceptionMonitor(0, 0.001)
list	kelsey_sandbox::perception_monitor.joint_nm_list
list	kelsey_sandbox::perception_monitor.l_jt_idx_list = [31, 32, 30, 34, 33, 35, 36]
list	kelsey_sandbox::perception_monitor.means = models["accelerometer"]
tuple	kelsey_sandbox::perception_monitor.models = apm.generate_models()
string	kelsey_sandbox::perception_monitor.node_name = "arm_perception_monitor"
list	kelsey_sandbox::perception_monitor.r_jt_idx_list = [17, 18, 16, 20, 19, 21, 22]
float	kelsey_sandbox::perception_monitor.std_dev = 2.5
list	kelsey_sandbox::perception_monitor.vars = models["accelerometer"]
list	kelsey_sandbox::perception_monitor.xmmax = [m + np.sqrt(v) * std_dev for m, v in zip(xm, xv)]
list	kelsey_sandbox::perception_monitor.xmmin = [m - np.sqrt(v) * std_dev for m, v in zip(xm, xv)]
tuple	kelsey_sandbox::perception_monitor.xv = map(np.sqrt, xv)
list	kelsey_sandbox::perception_monitor.ymmax = [m + np.sqrt(v) * std_dev for m, v in zip(ym, yv)]
list	kelsey_sandbox::perception_monitor.ymmin = [m - np.sqrt(v) * std_dev for m, v in zip(ym, yv)]
tuple	kelsey_sandbox::perception_monitor.yv = map(np.sqrt, yv)
list	kelsey_sandbox::perception_monitor.zmmax = [m + np.sqrt(v) * std_dev for m, v in zip(zm, zv)]
list	kelsey_sandbox::perception_monitor.zmmin = [m - np.sqrt(v) * std_dev for m, v in zip(zm, zv)]
tuple	kelsey_sandbox::perception_monitor.zv = map(np.sqrt, zv)