Abstract
Tactile sensing provides robots the ability of object recognition,fine operation,natural interaction,etc.However,in the actual scenario,robotic tactile recognition of similar objects still faces difficulties such as low efficiency and accuracy,resulting from a lack of high-performance sensors and intelligent recog-nition algorithms.In this paper,a flexible sensor combining a pyramidal microstructure with a gradient conformal ionic gel coating was demonstrated,exhibiting excellent signal-to-noise ratio(48 dB),low detection limit(1 Pa),high sensitivity(92.96 kPa-1),fast response time(55 ms),and outstanding stability over 15,000 compression-release cycles.Furthermore,a Pressure-Slip Dual-Branch Convolutional Neural Network(PSNet)architecture was proposed to separately extract hardness and texture features and per-form feature fusion.In tactile experiments on different kinds of leaves,a recognition rate of 97.16％was achieved,and surpassed that of human hands recognition(72.5％).These researches showed the great potential in a broad application in bionic robots,intelligent prostheses,and precise human-computer interaction.
基金项目
Open Project of the State Key Laboratory of Trauma and Chemical Poisoning(SKL202102)
Key R&D and Transformation of Science and Technology Projects in Tibet Autonomous Region(XZ2022RH001)
Chongqing Talents Program(CQYC2020030146)
Project of Chongqing Science and Technology Bureau(cstc2021 ycjhbgzxm0345)
Chongqing Bayu Scholar Program(DP2020036)
Chongqing Entrepreneurship and Innovation Support Program for Overseas Students Returning to China()
NETL
NSTL
万方数据