Adaptive Tracking Control of Soft Robots using Integrated Sensing Skin and Recurrent Neural Networks.

摘要: In this paper, we study integrated estimation and control of soft robots. A significant challenge in deploying closed loop controllers is reliable proprioception via sensing Despite the considerable advances accomplished fabrication, modelling, model-based robots, still its infancy. To that end, paper introduces a new method estimating degree curvature robot using stretchable skin. The skin spray-coated piezoresistive layer on latex membrane. mapping from strain signal to estimated by recurrent neural network. We investigate uni-directional bending as well bi-directional single-segment robot. Moreover, an adaptive controller developed track presence dynamic uncertainties. Subsequently, skin, experimentally demonstrate successful tracking