华中科技大学学报（自然科学版）2024，Vol.52Issue(5)：136-143,8.DOI:10.13245/j.hust.240623
基于触觉阵列感知的机器人稳定抓取判别方法
Discrimination method for robot stable grasping based on tactile array perception
摘要
Abstract
To address the issue that traditional single-point pressure sensors failed to provide a comprehensive reflection of the robot's grasping contact state,making it difficult to achieve accurate grasping status discrimination,an efficient and highly accurate robot stable grasping discrimination method was proposed based on the multi-point sensing characteristics of tactile array sensors.First,by capturing the distributed force information when the robot interacted with different objects during grasping,a mapping between the distributed force and tactile images was established,thereby constructing a dataset of robot grasping tactile images.Using a multi-layer perceptron framework,a grasping status discrimination model was developed to classify the robot's grasping states.Then,through training and optimizing the multi-layer perceptron model with different numbers of layers and nodes,the optimal parameters for the grasping status discrimination model were obtained.Furthermore,the proposed method was compared with various learning-based grasping discrimination algorithms.Results show that the proposed grasping state discrimination method has a discrimination accuracy of 99.74%and an average time of 2.3 ms,surpassing the baseline algorithms in both discrimination accuracy and speed.Through real-world grasping experiments,the method achieves a discrimination accuracy of 94%,which fully proves its strong robustness in stable grasping discrimination for objects outside of the dataset.关键词
机器人抓取/抓取状态判别/触觉阵列传感器/多层感知机/触觉图像Key words
robot grasping/grasping state discrimination/tactile array sensor/multilayer perceptron/tactile image分类
信息技术与安全科学引用本文复制引用
李彤,阎宇航,安静,陈钢..基于触觉阵列感知的机器人稳定抓取判别方法[J].华中科技大学学报（自然科学版）,2024,52(5):136-143,8.基金项目
江淮前沿技术协同创新中心追梦基金课题资助项目(2023-ZM01Z003) （2023-ZM01Z003）
国家自然科学基金资助项目(62103058,51975059) （62103058,51975059）
科技创新2030"新一代人工智能"重大项目(2018AAA0102904). （2018AAA0102904）
