Tactile Decoding of Edge Orientation With Artificial Cuneate Neurons in Dynamic Conditions.

ABSTRACT: Generalization ability in tactile sensing for robotic manipulation is a prerequisite to effectively perform tasks in ever-changing environments. In particular, performing dynamic tactile perception is currently beyond the ability of robotic devices. A biomimetic approach to achieve this dexterity is to develop machines combining compliant robotic manipulators with neuroinspired architectures displaying computational adaptation. Here we demonstrate the feasibility of this approach for dynamic touch tasks experimented by integrating our sensing apparatus in a 6 degrees of freedom robotic arm via a soft wrist. We embodied in the system a model of spike-based neuromorphic encoding of tactile stimuli, emulating the discrimination properties of cuneate nucleus neurons based on pathways with diff

SUBMITTER: Rongala UB 

PROVIDER: S-EPMC6614200 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature