This paper is focused on the design of interaction control of robotic machines for rehabilitative motor therapy of the upper limb. The control approach tries to address requirements deriving from the application field and adopts a bioinspired approach for regulating robot behavior in the interaction with the patient. An inner-outer loop control scheme is proposed. In order to tune the level of force and improve robot adaptability in the interaction with the patient, a classical outer force control loop is used. For the inner loop, a novel control law for low-level tuning of robot compliance is introduced, that is borrowed from studies on the biological mechanisms for regulating the elastic properties of the human arm. A dedicated simulation tool, which models the dynamics of an operational robotic machine interacting with a human subject, has been developed. Validation of basic adaptability and safety requirements of the control scheme is carried out in simple tasks, e.g., reaching and contact/noncontact transitions, as well as in simulated situations of typical motor exercises. In particular, the simulation tests demonstrate the adaptive capabilities of the proposed control schemes, e.g., in counterbalancing patient incorrect movements related to the various levels of disability. Moreover, preliminar experimental tests carried out on a real robotic system demonstrated the possibility of using the proposed approach for guaranteeing safe interaction with the patient.

1.
Hogan
,
N.
,
Krebs
,
H. I.
,
Charnnarong
,
J.
,
Srikrishna
,
P.
, and
Sharon
,
A.
, 1992, “
MIT-MANUS: A Workstation for Manual Therapy and Training I
,”
IEEE International Workshop on Robot and Human Communication
, Tokyo.
2.
Krebs
,
H. I.
,
Hogan
,
N.
,
Aisen
,
M. L.
, and
Volpe
,
B. T.
, 1998, “
Robot-Aided Neurorihabilitation
,”
IEEE Trans. Rehabil. Eng.
1063-6528,
6
, pp.
75
87
.
3.
Colombo
,
C.
,
Joerg
,
M.
,
Schreier
,
R.
, and
Dietz
,
V.
, 2000, “
Treadmill Training of Paraplegic Patients Using a Robotic Orthosis
,”
J. Rehabil. Res. Dev.
0748-7711,
37
, pp.
693
700
.
4.
Kiguchi
,
K.
, and
Fukuda
,
T.
, 2004, “
A 3DOF Exoskeleton for Upper-Limb Motion Assist—Consideration of the Effect of Biarticular Muscles
,”
2004 IEEE International Conference on Robotics and Automation
, New Orleans, LA, pp.
2424
2429
.
5.
Costa
,
N.
,
Brown
,
M.
, and
Caldwell
,
D. G.
, 2004, “
A Lower Body Exoskeletal Rehabilitation System
,”
3rd IARP-IEEE/RAS Joint Workshop on Technical Challenge for Dependable Robots in Human Environments
, Manchester, England.
6.
Reinkensmeyer
,
D.
,
Hogan
,
N.
,
Krebs
,
H. I.
,
Lehman
,
S. L.
, and
Lum
,
P. S.
, 2000, “
Rehabilitators, Robots and Guides: New Tools for Neurological Rehabilitation
,” In:
Biomechanics and Neural Control of Posture and Movement
,
J.
Winters
and
P. E.
Crago
, eds.
Springer-Verlag
, Berlin, pp.
516
534
.
7.
Siciliano
,
B.
, and
Villani
,
L.
, 1999,
Robot Force Control
,
Kluwer Academic
, Boston.
8.
Gorinevsky
,
D. M.
,
Formalsky
,
A. M.
, and
Schneider
,
A. Y.
, 1997,
Force Control of Robotics Systems
,
CRC Press
, Boca Raton.
9.
Bicchi
,
A.
, 2004, “
Fast and ‘Soft-Arm’ Tactics. Dealing With the Safety-Performance Tradeoff in Robot Arms Design and Control
,”
IEEE Rob. Autom. Mag.
1070-9932,
11
, pp.
22
33
.
10.
Zinn
,
M.
,
Kathib
,
O.
,
Roth
,
B.
, and
Salisbury
,
J. K.
, 2004, “
Playing It Safe: A New Actuation Concept for Human-Friendly Robot Design
,”
IEEE Rob. Autom. Mag.
1070-9932,
11
, pp.
12
21
.
11.
Formica
,
D.
,
Zollo
,
L.
, and
Guglielmelli
,
E.
, 2005, “
Adaptive Compliance for Enhancing Dependability of Rehabilitation Robotic Machines
,”
4th IARP/IEEE-RAS/EURON Workshop on Technical Challenges for Dependable Robots in Human Environments
, Nagoya, Japan.
12.
Colombo
,
G.
, 2004, “
Treadmill Training With the Robotic Orthosis ‘Lokomat’: New Technical Features and Results From Multicenter Trial in Chronic Spinal Cord Injury
,”
Int. J. Rehabil. Res.
0342-5282,
27
, pp.
92
93
.
13.
Salisbury
,
J. K.
, 1980, “
Active Stiffness Control of a Manipulator in Cartesian Coordinates
,”
19th IEEE Conference on Decision and Control
, Albuquerque, NM,
1
, pp.
95
100
.
14.
Kazerooni
,
H.
,
Houpt
,
P. K.
, and
Shecridan
,
T. B.
, 1986, “
Robust Compliant Motion for Manipulators. Part 1. The Fundamental Concepts of Compliant Motion. Part 2. Design Methods
,”
IEEE J. Rob. Autom.
0882-4967,
2
, pp.
83
105
.
15.
Zollo
,
L.
,
Siciliano
,
B.
,
Laschi
,
C.
,
Teti
,
G.
, and
Dario
,
P.
, 2003, “
An Experimental Study on Compliance Control for a Redundant Personal Robot Arm
,”
Rob. Auton. Syst.
0921-8890,
44
, pp.
101
129
.
16.
Hogan
,
N.
, 1985, “
Impedance Control: An Approach to Manipulation, Part I, II, II
,”
ASME J. Dyn. Syst., Meas., Control
0022-0434,
107
, pp.
1
24
.
17.
Krebs
,
H. I.
,
Palazzolo
,
J. J.
,
Dipietro
,
L.
,
Ferraro
,
M.
,
Krol
,
J.
,
Rannekleiv
,
K.
,
Volpe
,
B. T.
, and
Hogan
,
N.
, 2003, “
Rehabilitation Robotics: Performance-Based Progressive Robot-Assisted Therapy
,”
Autonomous Robots
,
Kluwer Academics
, Dordrecht, Vol.
15
, pp.
7
20
.
18.
Mussa-Ivaldi
,
F. A.
,
Hogan
,
N.
, and
Bizzi
,
E.
, 1985, “
Neural, Mechanical, and Geometric Factors Subserving Arm Posture in Humans
,”
J. Neurosci.
0270-6474,
5
, pp.
2732
2743
.
19.
Katayama
,
M.
, and
Kawato
,
M.
, 1991, “
Virtual Trajectory and Stiffness Ellipse During Force Trajectory Control Using a Parallel-Hierarchical Neural Network Model
,” 5th international Conference on Advanced Robotics, PISA,
2
, pp.
1187
1194
.
20.
Katayama
,
M.
, and
Kawato
,
M.
, 1993, “
Virtual Trajectory and Stiffness Ellipse During Multijoint Arm Movement Predicted by Neural Inverse Models
,”
Biol. Cybern.
0340-1200,
69
, pp.
353
362
.
21.
Gomi
,
H.
, and
Kawato
,
M.
, 1997, “
Human Arm Stiffness and Equilibrium-Point Trajectory During Multi-Joint Movement
,”
Biol. Cybern.
0340-1200,
76
, pp.
163
171
.
22.
Gomi
,
H.
, and
Osu
,
R.
, 1998, “
Task-Dependent Viscoelasticity of Human Multijoint Arm and Its Spatial Characteristics for Interaction With Environments
,”
J. Neurosci.
0270-6474,
18
, pp.
8965
8978
.
23.
Gomi
,
H.
, 1998, “
Anisotropic Stiffness Reduction During Constrained Multijoint Arm Movement
,”
20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
, Vol.
20
, pp.
2336
2337
.
24.
Osu
,
R.
, and
Gomi
,
H.
, 1999, “
Multijoint Muscle Regulation Mechanism Examined by Measured Human Arm Stiffness and EMG Signals
,”
J. Neurophysiol.
0022-3077,
81
, pp.
1458
1468
.
25.
Zollo
,
L.
,
Siciliano
,
B.
,
Guglielmelli
,
E.
, and
Dario
,
P.
, 2003, “
A Bio-Inspired Approach for Regulating Visco-Elastic Properties of a Robot Arm
,”
2003 IEEE International Conference on Robotics and Automation
,
Taipei
, Taiwan, pp.
14
19
.
26.
Zollo
,
L.
,
Dipietro
,
L.
,
Siciliano
,
B.
,
Guglielmelli
,
E.
, and
Dario
,
P.
, 2005, “
A Bio-Inspired Approach for Regulating and Measuring Visco-Elastic Properties of a Robot Arm
,”
J. Rob. Syst.
0741-2223,
22
, pp.
397
419
.
27.
Formica
,
D.
,
Zollo
,
L.
, and
Guglielmelli
,
E.
, 2005, “
Torque-Dependent Compliance Control in the Joint Space of a Cartesian Robotic Machine for Motor Therapy
,”
9th IEEE International Conference on Rehabilitation Robotics
, Chicago, pp.
341
344
.
28.
Bhushan
,
N.
, and
Shadmehr
,
R.
, 1999, “
Computational Nature of Human Adaptive Control During Learning of Reaching Movements in Force Fields
,”
Biol. Cybern.
0340-1200,
81
, pp.
39
60
.
29.
Krebs
,
H. I.
,
Hogan
,
N.
,
Volpe
,
B. T.
,
Aisen
,
M. L.
,
Edelstein
,
L.
, and
Diels
,
C.
, 1999, “
Overview of Clinical Trials with MIT-MANUS: A Robot-Aided Neuro-Rehabilitation Facility
,”
Technol. Health Care
0928-7329,
7
, pp.
419
423
.
30.
Krebs
,
H. I.
,
Volpe
,
B. T.
,
Aisen
,
M. L.
, and
Hogan
,
N.
, 2000, “
Increasing Productivity and Quality of Care: Robot-Aided Neuro-Rehabilitation
,”
J. Rehabil. Res. Dev.
0748-7711,
37
, pp.
639
652
.
31.
Fasoli
,
S. E.
,
Krebs
,
H. I.
,
Stein
,
J.
,
Frontera
,
W. R.
, and
Hogan
,
N.
, 2003, “
Effect of Robotic Therapy on Motor Impairment and Recovery in Chronic Stroke
,”
Arch. Phys. Med. Rehabil.
0003-9993,
84
, pp.
477
482
.
32.
Hogan
,
N.
, 1985, “
The Mechanics of Multi-Joint Posture and Movement Control
,”
Biol. Cybern.
0340-1200,
52
, pp.
315
331
.
33.
Miall
,
R. C.
, 1998, “
Motor Control, Biological and Theoretical
,”
The Handbook of Brain Theory and Neural Networks
,
M. A.
Arbib
, Ed.,
pp.
597
600
.
34.
Micera
,
S.
,
Carrozza
,
M.
,
Guglielmelli
,
E.
,
Cappiello
,
G.
,
Zaccone
,
F.
,
Freschi
,
C.
,
Colombo
,
R.
,
Mazzone
,
A.
,
Delconte
,
C.
,
Pisano
,
F.
,
Minuco
,
G.
, and
Dario
,
P.
, 2005, “
A Simple Robotic System for Neurorehabilitation
,”
Adv. Rob.
0169-1864,
19
, pp.
271
284
.
You do not currently have access to this content.