Real-time Friction Estimation for Grip Force Control

被引:10
|
作者
Khamis, Heba [1 ]
Xia, Benjamin [1 ]
Redmond, Stephen J. [1 ,2 ,3 ]
机构
[1] UNSW Sydney, Grad Sch Biomed Engn, Sydney, NSW, Australia
[2] Univ Coll Dublin, UCD Sch Elect & Elect Engn, UCD Ctr Biomed Engn, Dublin, Ireland
[3] Univ Coll Dublin, SFI Insight Ctr Data Analyt, Dublin, Ireland
基金
澳大利亚研究理事会; 爱尔兰科学基金会;
关键词
SENSOR; PAPILLARRAY; RESPONSES; DESIGN; OBJECT; SKIN;
D O I
10.1109/ICRA48506.2021.9561640
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An important capability of humans when performing dexterous precision gripping tasks is our ability to feel both the weight and slipperiness of an object in real-time, and adjust our grip force accordingly. In this paper, we present for the first time a fully-instrumented version of our PapillArray tactile sensor concept, which can sense grip force, object weight, and incipient slip and friction, all in real-time. We demonstrate the real-time estimation of friction and measurement of 3D force from PapillArray sensors mounted on each finger of a two-finger gripper, combined with a closed-loop grip-force control algorithm that dynamically applies a near-optimal grip force to avoid dropping objects of varying weight and friction. A vertical lifting task was performed using an object with varying weight and friction, and with some common household items. After intentionally adding a 20% safety margin on the target grip force, the actual grip force applied was only 9-30 % greater than that required to avoid slip. Future work will focus on incorporating real-time torque measurement into the grip force feedback control. This will significantly advance the state-of-the-art in artificial tactile sensing and bring us closer to robotic dexterity.
引用
收藏
页码:1608 / 1614
页数:7
相关论文
共 50 条
  • [1] Live Demonstration: Dynamic Grip-force Control using Real-time Friction Estimation from Incipient Slip Events
    Khamis, Heba
    Xia, Benjamin
    Redmond, Stephen J.
    [J]. 2020 IEEE SENSORS, 2020,
  • [2] Real-time slacking as a default mode of grip force control: implications for force minimization and personal grip force variation
    Smith, Brendan W.
    Rowe, Justin R.
    Reinkensmeyer, David J.
    [J]. JOURNAL OF NEUROPHYSIOLOGY, 2018, 120 (04) : 2107 - 2120
  • [3] Deep Real-Time Decoding of bimanual grip force from EEG & fNIRS
    Ortega, Pablo
    Zhao, Tong
    Faisal, Aldo
    [J]. 2021 10TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2021, : 714 - 717
  • [4] Real-time estimation of road friction coefficient for the electric vehicle
    Lin Cheng
    Wang Gang
    Cao Wan-ke
    Zhou Feng-jun
    [J]. PROCEEDINGS OF THE 2012 THIRD WORLD CONGRESS ON SOFTWARE ENGINEERING (WCSE 2012), 2012, : 172 - 175
  • [5] Particle Filter for Real-time Estimation and Compensation of Nonlinear Friction
    Suzuki, Yoshihiko
    Fukui, Jun'ya
    Chen, Gan
    Takami, Isao
    [J]. 2018 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA), 2018, : 1779 - 1784
  • [6] REAL-TIME PEAK FORCE CONTROL IN CNC MILLING
    Nouri, Mehdi
    Fussell, Barry K.
    [J]. 2016 INTERNATIONAL SYMPOSIUM ON FLEXIBLE AUTOMATION (ISFA), 2016, : 255 - 262
  • [7] HAPTIC MODELING OF STOMACH FOR REAL-TIME PROPERTY AND FORCE ESTIMATION
    Sun, Zhenglong
    Wang, Zheng
    Phee, Soo Jay
    [J]. JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY, 2013, 13 (03)
  • [8] REAL-TIME ESTIMATION OF MUSCLE FORCE FROM A MULTICHANNEL EMG
    SHI, Y
    TOMPKINS, WJ
    HECOX, K
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1985, 32 (10) : 875 - 875
  • [9] Real-time Sensorless Estimation of Position and Force for Solenoid Actuators
    Nagai, Sakahisa
    Nozaki, Takahiro
    Kawamura, Atsuo
    [J]. IEEJ JOURNAL OF INDUSTRY APPLICATIONS, 2016, 5 (02) : 32 - 38
  • [10] Real-Time Finger Force Estimation Robust to a Perturbation of Electrode Placement for Prosthetic Hand Control
    Cho, Younggeol
    Kim, Pyungkang
    [J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2022, 30 (1233-1243) : 1233 - 1243