Soft robot perception using embedded soft sensors and recurrent neural networks

Recent work has begun to explore the design of biologically inspired soft robots composed of soft, stretchable materials for applications including the handling of delicate materials and safe interaction with humans. However, the solid-state sensors traditionally used in robotics are unable to capture the high-dimensional deformations of soft systems. Embedded soft resistive sensors have the potential to address this challenge. However, both the soft sensors-and the encasing dynamical system-often exhibit nonlinear time-variant behavior, which makes them difficult to model. In addition, the problems of sensor design, placement, and fabrication require a great deal of human input and previous knowledge. Drawing…

• OO
  Office of Naval Research

  Award: N000141712062