  Modern Visual-Based Tactile Sensors (VBTSs) use cost-effective cameras to
track elastomer deformation, but struggle with ambient light interference.
Solutions typically involve using internal LEDs and blocking external light,
thus adding complexity. Creating a VBTS resistant to ambient light with just a
camera and an elastomer remains a challenge. In this work, we introduce WStac,
a self-illuminating VBTS comprising a mechanoluminescence (ML) whisker
elastomer, camera, and 3D printed parts. The ML whisker elastomer, inspired by
the touch sensitivity of vibrissae, offers both light isolation and high ML
intensity under stress, thereby removing the necessity for additional LED
modules. With the incorporation of machine learning, the sensor effectively
utilizes the dynamic contact variations of 25 whiskers to successfully perform
tasks like speed regression, directional identification, and texture
classification. Videos are available at: https://sites.google.com/view/wstac/.
