Brayden Hollis

2 accepted papers

2018

Compressed Learning for Tactile Object Recognition

Brayden Hollis, Stacy Patterson, Jeff Trinkle

RA-L 2018

We present a framework for object recognition using robotic skins with embedded arrays of tactile sensing elements. Our approach is based on theoretical foundations in compressed sensing and compressed learning. In our framework, tactile data is compressed during acquisition, potentially in-hardware

Cited by 21 Source ↗Scholar ↗

2016

Compressed sensing for tactile skins

Brayden Hollis, Stacy Patterson, Jeff Trinkle

ICRA 2016poster

Whole body tactile perception via tactile skins offers large benefits for robots in unstructured environments. To fully realize this benefit, tactile systems must support real-time data acquisition over a massive number of tactile sensor elements. We present a novel approach for scalable tactile dat…

Cited by 14 Source ↗Scholar ↗