Abstract

An exoskeleton robotic glove intended for patients who have suffered paralysis of the hand due to stroke or other factors has been developed and integrated. The robotic glove has the potential to aid patients with grasping objects as part of their daily life activities. Grasp stability was studied and researched by various research groups, but mainly focused on robotic grippers by devising conditions for a stable grasp of objects. Maintaining grasp stability is important so as to reduce the chances of the object slipping and dropping. But there was little focus on the grasp stability of robotic exoskeleton gloves, and most of the research was focused on mechanical design. A robotic exoskeleton glove was developed as well as novel methods to improve the grasp stability. The glove is constructed with rigidly coupled four-bar linkages attached to the finger tips. Each linkage mechanism has one-DOF (degree of freedom) and is actuated by a linear series elastic actuator (SEA). Two methods were developed to satisfy two of the conditions required for a stable grasp. These include deformation prevention of soft objects, and maintaining force and moment equilibrium of the objects being grasped. Simulations were performed to validate the performance of the proposed algorithms. A battery of experiments was performed on the integrated prototype in order to validate the performance of the algorithms developed.

References

References
1.
Refour
,
E.
,
Sebastian
,
B.
, and
Ben-Tzvi
,
P.
,
2018
, “
Two-Digit Robotic Exoskeleton Glove Mechanism: Design and Integration
,”
ASME J. Mech. Rob.
,
10
(
2
), p.
025002
. 10.1115/1.4038775
2.
Vanteddu
,
T.
,
Sebastian
,
B.
, and
Ben-Tzvi
,
P.
,
2018
, “
Design Optimization of RML Glove for Improved Grasp Performance
,”
Proceedings of the ASME 2018 Dynamic Systems and Control Conference (DSCC 2018)
,
Atlanta, GA
,
Sept. 30–Oct. 3
, pp.
1
8
.
3.
Lee
,
S. W.
,
Landers
,
K. A.
, and
Park
,
H.
,
2014
, “
Development of a Biomimetic Hand Exotendon Device (BiomHED) for Restoration of Functional Hand Movement Post-Stroke
,”
IEEE Trans. Neural Syst. Rehabil. Eng.
,
22
(
4
), pp.
886
898
. 10.1109/TNSRE.2014.2298362
4.
In
,
H.
,
Kang
,
B. B.
,
Sin
,
M.
, and
Cho
,
K.
,
2015
, “
Exo-Glove: A Wearable Robot for the Hand With a Soft Tendon Routing System
,”
IEEE Rob. Autom. Mag.
,
22
(
1
), pp.
97
105
. 10.1109/MRA.2014.2362863
5.
Nycz
,
C. J.
,
Delph
,
M. A.
, and
Fischer
,
G. S.
,
2015
, “
Modeling and Design of a Tendon Actuated Soft Robotic Exoskeleton for Hemiparetic Upper Limb Rehabilitation
,”
2015 37th Annual International Conference on IEEE Engineering in Medicine and Biology Society (EMBC)
,
Milan
,
Aug. 25–29
, pp.
3889
3892
.
6.
Ben-Tzvi
,
P.
,
Danoff
,
J.
, and
Ma
,
Z.
,
2016
, “
The Design Evolution of a Sensing and Force-Feedback Exoskeleton Robotic Glove for Hand Rehabilitation Application
,”
J. Mech. Rob.
,
8
(
5
), pp.
1
9
. 10.1115/1.4032270
7.
Iqbal
,
J.
,
Khan
,
H.
,
Tsagarakis
,
N. G.
, and
Caldwell
,
D. G.
,
2014
, “
ScienceDirect A Novel Exoskeleton Robotic System for Hand Rehabilitation—Conceptualization to Prototyping
,”
Integr. Med. Res.
,
34
(
2
), pp.
79
89
. 10.1016/j.bbe.2014.01.003
8.
Agarwal
,
P.
,
Fox
,
J.
,
Yun
,
Y.
,
O’Malley
,
M. K.
, and
Deshpande
,
A. D.
,
2015
, “
An Index Finger Exoskeleton With Series Elastic Actuation for Rehabilitation: Design, Control and Performance Characterization
,”
Int. J. Rob. Res.
,
34
(
14
), pp.
1747
1772
. 10.1177/0278364915598388
9.
Howard
,
W. S.
, and
Kumar
,
V.
,
1996
, “
On the Stability of Grasped Objects
,”
IEEE Trans. Rob. Autom.
,
12
(
6
), pp.
904
917
. 10.1109/70.544773
10.
Nakashima
,
A.
,
Yoshimastsu
,
Y.
, and
Hayakawa
,
Y.
,
2010
, “
Analysis and Synthesis of Stable Grasp by Multi-Fingered Robot Hand
,”
IEEE International Conference on Control Application
,
Yokohama, Japan
,
Sept. 8–10
, pp.
1582
1589
.
11.
Lu
,
Y.
,
Zhang
,
C.
,
Cao
,
C.
, and
Liu
,
Y.
,
2017
, “
Analysis of Coordinated Grasping Kinematics and Optimization of Grasping Force of a Parallel Hybrid Hand
,”
Int. J. Adv. Rob. Syst.
,
14
(
3
), pp.
1
14
. 10.1177/1729881417716816
12.
Bekiroglu
,
Y.
,
Laaksonen
,
J.
,
Jorgensen
,
J. A.
,
Kyrki
,
V.
, and
Kragic
,
D.
,
2011
, “
Assessing Grasp Stability Based on Learning and Haptic Data
,”
IEEE Trans. Rob.
,
27
(
3
), pp.
616
629
. 10.1109/TRO.2011.2132870
13.
Kinoshita
,
H.
,
Murase
,
T.
, and
Bandou
,
T.
,
1996
, “
Grip Posture and Forces During Holding Cylindrical Objects With Circular Grips
,”
Ergonomics
,
39
(
9
), pp.
1163
1176
. 10.1080/00140139608964536
14.
Dang
,
H.
, and
Allen
,
P. K.
,
2012
, “
Learning Grasp Stability
,”
2012 IEEE International Conference on Robotics and Automation
,
Saint Paul, MN
,
May 14–18
, pp.
2392
2397
.
15.
Kragten
,
G. A.
,
Baril
,
M.
,
Gosselin
,
C.
, and
Herder
,
J. L.
,
2011
, “
Stable Precision Grasps by Underactuated Grippers
,”
IEEE Trans. Rob.
,
27
(
6
), pp.
1056
1066
. 10.1109/TRO.2011.2163432
16.
Suhaib
,
M.
,
Khan
,
R. A.
, and
Mukherjee
,
S.
,
2011
, “
Contact Force Optimization for Stable Grasp of Multifingered Robotic Grippers
,”
World Congr. Eng.
,
III
, pp.
2194
2197
.
17.
Haas-Heger
,
M.
,
Iyengar
,
G.
, and
Ciocarlie
,
M.
,
2018
, “
Passive Reaction Analysis for Grasp Stability
,”
IEEE Trans. Autom. Sci. Eng.
,
15
(
3
), pp.
955
966
. 10.1109/TASE.2018.2803620
18.
Lee
,
B. J. B.
,
Williams
,
A.
,
Ben-tzvi
,
P.
, and
Member
,
S.
,
2018
, “
Intelligent Object Grasping With Sensor Fusion for Rehabilitation and Assistive Applications
,”
IEEE Trans. Neural Syst. Rehabil. Eng.
,
26
(
8
), pp.
1556
1565
. 10.1109/TNSRE.2018.2848549
19.
Chauhan
,
R. J.
, and
Ben-Tzvi
,
P.
,
2018
, “
Latent Variable Grasp Prediction for Exoskeletal Glove Control
,”
Proceedings of the ASME 2018 Dynamic Systems and Control Conference
,
Atlanta, GA
,
Sept. 30–Oct. 3
, p. V001T07A002.
20.
Chauhan
,
R.
,
Sebastian
,
B.
, and
Ben-Tzvi
,
P.
,
2020
, “
Grasp Prediction Towards Naturalistic Exoskeleton Glove Control
,”
IEEE Trans. Human-Mach. Sys.
, 50(1), pp.
22
31
. 10.1109/thms.2019.2938139
21.
Howard
,
A. M.
, and
Bekey
,
G. A.
,
2000
, “
Intelligent Learning for Deformable Object Manipulation
,”
Auton. Rob.
,
9
(
1
), pp.
51
58
. 10.1023/A:1008924218273
22.
Cretu
,
A.
,
Payeur
,
P.
, and
Petriu
,
E. M.
,
2012
, “
Soft Object Deformation Monitoring and Learning for Model-Based Robotic Hand Manipulation
,”
IEEE Trans. Syst. Man, Cybern. Part B
,
42
(
3
), pp.
740
753
. 10.1109/TSMCB.2011.2176115
23.
Drimus
,
A.
,
Kootstra
,
G.
,
Bilberg
,
A.
, and
Kragic
,
D.
,
2011
, “
Classification of Rigid and Deformable Objects Using a Novel Tactile Sensor
,”
2011 15th International Conference on Advanced Robotics
,
Tallinn
,
June 20–23
, pp.
427
434
.
24.
Khalil
,
F. F.
,
Payeur
,
P.
, and
Cretu
,
A.-M.
,
2010
, “
Integrated Multisensory Robotic Hand System for Deformable Object Manipulation
,”
IASTED Technology Conferences/705: ARP/706: RA/707: NANA/728: CompBIO
,
Cambridge, MA
,
Nov. 1–3
, pp.
159
166
.
25.
Delgado
,
A.
,
Jara
,
C. A.
,
Mira
,
D.
, and
Torres
,
F.
,
2015
, “
A Tactile-Based Grasping Strategy for Deformable Objects Manipulation and Deformability Estimation
,”
2015 12th International Conference on Informatics in Control Automation and Robotics
,
Colmar, France
,
July 21–23
, vol.
2
, pp.
369
374
.
26.
Huang
,
J.
,
Todo
,
I.
, and
Yabut
,
T.
,
2005
, “Position/Force Hybrid Control of a Manipulator With a Flexible Tool Using Visual and Force Information,”
Cutting Edge Robotics
,
Pro Literatur Verlag, Germany
.
27.
Boyd
,
S.
, and
Vandenberghe
,
L.
,
2004
,
Convex Optimization
,
Cambridge University Press
,
Cambridge, UK
.
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