Capacitive Sensing for Container and Content Classification | Alexandra Gillespie
Capacitive Sensing for Container and Content Classification
Alexandra Gillespie, RISS 2023 Cohort
Carnegie Mellon University
Robotics Institute Summer Scholars: https://riss.ri.cmu.edu/
Enabling autonomy for those with limited mobility is an important component of caregiving robotics. Fine-motor tasks such as pouring require a lot of dexterity and muscular control, making them difficult for some disabled populations to execute. Robots typically struggle to manipulate fluids or fine granular substances because of the variety of behaviors of different substrates, such as varying viscosity. To manipulate the contents of any given container, one must first identify its contents (what to manipulate) and container (how to appropriately grip and move it). Capacitive sensors, which use electrical fields to detect objects with different dielectric constants than air, have been used in caregiving robotics but have not yet been used in the setting of content detection or manipulation. While alternative approaches to content detection exist, all have substantial limitations and are extremely expensive. The capacitive sensors consist of relatively inexpensive and accessible hardware which is atypical for this sort of detection and classification. The simple classifier used also demonstrates the potential of this technique.
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