bug fix for tilt backlash

The tilt backlash model is supposed to compare the current tilt
angle of the head with the head_tilt_backlash_transition_angle
to determine if head_tilt_looking_up element of the backlash state
is true or false. This is due to the head resting against
different sides of the tilt joint based on whether it's looking up
or looking down.

At some point, an error was introduced in which
head_tilt_looking_up was set based on the recent relative motion
of the head tilt joint. This is the way backlash state is
determined for the telescoping arm and head panning.
In contrast, the head tilt backlash state depends on gravity
and where the center of mass of the head is relative to the
tilt joint's axis of rotation. As such, the head tilt backlash
state depends on the tilt angle of the head.

We are not currently focusing our development on stretch_demos and stretch_funmap.

Add missing dependency on realsense (for devel branch)

Add missing dependency on realsense

Checking the calibration now collects fewer higher quality observations.

When checking or performing a new fit, the fit error is checked against a threshold that likely indicates a problem with the calibration.

Code to check the existing calibration. It does the following:

+ Collects a reduced number of new observations with which to check the current calibration.

+ Visualizes and computes the fit of the current calibration to the new observations.

Future work:

+ Improve the reduced number of observations to increase efficiency.

+ Check the numeric results of the fit and provide a warning if the quality is low.

Merge develop into master

added comments & deleted unused code

Merge branch 'bugfix/required_realsense_xacro_arg'

+ Users may define out-of-range goals intentionally if they want to move any joint to its limit without knowing the joint's calibrated limit for a specific robot

+ issue with gripper not opening due to commanded opening aperture violating gripper joint bounds
+ added documentation
+ discards object candidate points based on the height of object and the height of the volume of interest used for perception (height of the robot's camera)
+ appears to correct issue when surface is against a wall, which seemed to result in the wall being detected as a large object on the surface

URDF meshes are now organized per the robot batch ID and copied into place using the update_meshes script