外骨骼机器人

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Advanced Robotics

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Exoskeletal meal assistance system (EMAS II) for

patients with progressive muscular disease

Yasuhisa Hasegawa a, Saori Oura a & Junji T akahashi a

a Graduate School of Systems and Information Engineering, University of T sukuba 1-1-1

T ennodai, 305-8573, T sukuba, Japan.

Published online: 09 Oct 2013.

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Advanced Robotics ,2013

V ol.27,No.18,1385–1398,https://www.doczj.com/doc/cd7229777.html,/10.1080/01691864.2013.841311

FULL PAPER

Exoskeletal meal assistance system (EMAS II)for patients with progressive muscular disease

Yasuhisa Hasegawa ?,Saori Oura and Junji Takahashi

Graduate School of Systems and Information Engineering,University of Tsukuba 1-1-1Tennodai,Tsukuba 305-8573,Japan

(Received 28March 2012;accepted 28June 2012)

Patients with muscle weakness such as muscular dystrophy usually need someone’s assistance in their daily activities.In order to reduce the caregiver burden and to improve quality of life (QOL)of the patients,various robotic technologies have been developed.This paper presents an exoskeletal assistance system EMAS II for the patients,which assists the upper extremity for the purpose of daily activities such as eating,writing,or other desk works.The EMAS II assists four DOF;shoulder ?exion-extension,shoulder abduction-adduction,shoulder medial-lateral rotation,and elbow ?exion-extension.The EMAS II has three kinds of user interfaces which are operated by residual functions of the patients,because it is important for patients’health and initiative to use the residual functions.In order to control the four DOFs exoskeleton system using the interfaces with less DOF,the EMAS II simulates upper limb motion patterns of healthy people.The patterns are modeled by extracting correlations between the height of the wrist joint and that of the elbow joint.Therefore,users have only to control the position of their wrist joint to do tasks at a table.Through an experiment with a healthy subject,the feasibility of meal assistance by the EMAS II was con?rmed.Furthermore,the system was applied to a spinal muscular atrophy patient in a clinical trial to check the usability.The experimental results indicated that the EMAS II could support the patient’s upper extremity to do tasks at a table.

Keywords:assistive device;exoskeleton;upper limb;muscular dystrophy;muscular disease;eating;motion support

1.Introduction

Patients with neuromuscular disease are limited in activities of daily living (ADL).For instance,patients with progres-sive muscular dystrophy (PMD)or with spinal muscular atrophy (SMA)have dif?culty in walking,lifting their arms against gravity,and changing overall posture,because of muscle weakness of their trunk,extremity,particularly of their proximal parts.Thus,the patients require caregiver’s support appropriate to their symptoms in many aspects of everyday lives.As a result,the caregiver burden and sacri-?ce of the patient’s independence have been a problem for a long time.In order to avoid the issue,robotic devices have been developed for life-supporting or rehabilitation.

Assistive devices for upper limb disorders can be divided into robot arm type and exoskeleton type.Examples of the robot arm type are the MySpoon,[1]the Handy 1,[2]and the iARM (Assistive Robotic Manipulator).[3]These robots re-place the patients’arm in a variety of tasks such as eating and picking up distant objects with high positioning accuracy.They can be used by the advanced stage patients with limited residual functions.However,disuse of the sections with or without impairment is not desirable from the viewpoint of prevention of joint contracture,encouragement of the patients’initiative,and improvement of the quality of life (QOL).Therefore,the assistive device for those patients

?Corresponding author.Email:hase@iit.tsukuba.ac.jp

should be the one that assists the user’s upper limb,and that is the exoskeleton type.The Armon,[4]which is an example of the exoskeletal system,is a spring-balanced arm support system and a user can lift up his/her arm without being affected by the force of gravity.It has no actuators so that the patient with severe symptoms cannot carry out works such as reaching task even if he/she uses this device.On the other hand,there are exoskeleton type devices using actu-ators such as the ARMin,[5]the ABLE,[6]the BONES,[7]and the Muscle Suit.[8]Although they are developed for rehabilitation of disabled people or assistance for healthy people to do heavy work,each of the devices are too large to be applied in daily lives.When we develop assistive systems for people with progressive muscle weakness or paralysis,we should design a versatile support system which has adjustable support level and can improve the patients’physical condition and initiative.

The EMAS I shown in Figure 1is an exoskeletal meal assistance system which our laboratory has developed for the patients with muscle weakness.There are two DOFs at the shoulder (?exion-extension and medial-lateral rotation),and one DOF at the elbow (?exion-extension).Each joint is light and small because of the wire driven system and is operated by a foot controller as shown in Figure 2.All the parts except a user interface are mounted on a chair.

?2013Taylor &Francis and The Robotics Society of Japan

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Figure 1.EMAS I.

Through an experiment,where a healthy subject regarded as a muscular dystrophy patient ate a meal with the EMAS I,we con?rmed the possibility of the meal assistance using the EMAS I.However,there were two problems:one was that the elbow joint hit table according to the height of the table,and the other was that the foot controller was not easy to use for the muscular dystrophy patient because he/she did not have enough capability of movement on his/her leg.In this paper,we propose the EMAS II which has four actuated joints (shoulder ?exion-extension,shoulder medial-lateral rotation,shoulder adduction-abduction,and the elbow ?exion-extension)and one unactuated joint for the shoulder girdle and upper body motions.While the EMAS I is mounted on a chair or a wheelchair,this EMAS II is mounted on a special stand so as to apply to all types

of wheelchairs.Therefore,a caregiver has only to put the EMAS II next to the wheelchair and put the care receiver’s arm into the orthosis.In addition,we propose three user interfaces,trackball type,joystick type,and BEP type in-terface so that the patient can choose more preferable one according to his/her physical condition or residual func-tions.Because the user interfaces have only three DOFs at most while the exoskeleton has four actuated joints,the controller of the EMAS II needs a condition of constraint to control each joint angle.The constraint condition is set ?nd-ing corresponding between the height of the elbow position and that of the wrist position of healthy people.

The purpose of this study is to develop an assistive system EMAS II for patients with muscle weakness in order to reduce the caregiver burden and to improve the initiative and QOL of the patients.In this study,the system applies to the patients with muscle weakness of proximal parts such as shoulder and elbow.

2.EMAS II

2.1.System architecture

The EMAS II consists of an exoskeleton part,a user interface,a motor unit,a control device,and a power supply as shown in Figure 3.The motor unit contains four gearhead motors,a motor driver circuit,and encoders.Every com-ponent except for the user interface is ?xed on a special stand which is a remodeled walker in order to enable the patients to use the EMAS II remain seated on a wheelchair because the most common early symptom of the disease is lower-extremity muscle weakness and many of the patients spend most of their time on a wheelchair (Figure 4).The exoskeleton part is small and light because of the wire

drive

Figure 2.Foot controller of EMAS I.

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Figure 3.Sideview of the EMAS

II.

Figure 4.The EMAS II with a trackball type interface.

system.Moreover,there are several user interface devices so that the user can choose most preferable one according to his/her physical conditions.The user controls the right upper limb operating the user interface with the opposite hand.

2.2.Mechanism of joints

When healthy people do tasks on a table,they use not only shoulder and elbow rotation motions but also shoulder girdle motions and upper body motions.Therefore,mech-anisms which are given no regard to such motions bring a sense of discomfort to a user and reduction of range of motion.There have been researches of shoulder mechanism

Table 1.Arrangement of joint ID,motion,θdirection,power source.

Joint ID Motion θdirection Power source

J 1

?exion θ+1motor 1extension

θ?1gravity shoulder

J 2medial rotation θ+2motor 2lateral rotation θ?2spring J 3

abduction θ+3motor 3adduction θ?3gravity elbow

J 4

?exion θ+4motor 4extension

θ?4

gravity

with assistance of shoulder girdle movements for exoskele-ton robot.[9]However,the mechanism is too large to apply for assistive devices for ADL.In this study,the assistive system has four actuated joints (shoulder ?exion-extension,shoulder medial-lateral rotation,shoulder abduction-adduction,and elbow ?exion-extension)and one unactuated joint for shoulder girdle and upper body movements.The four joints are driven via wires as shown in Figure 5.Here joint numbers,J 1...J 5,and the positive rotation arrow are assigned to each joint as shown in Figure 6.During the assistance with the EMAS II,shoulder ?exion,medial rotation,abduction,and elbow ?exion motions are driven by motor traction.The shoulder extension,adduction,and elbow extension are driven using gravity force,and the shoulder lateral rotation is driven by torsion spring because the gravity force does not affect that motion.Table 1summa-rizes the joint numbers,the motions,the rotation direction,and the power sources.

The minimum angles,the maximum angles,the range of motions of all the joints and the range of motions for human ADL are summarized in Table 2.[10]The maximum torques of actuated joints of the system and the that of unimpaired arm are summarized in Table 3.The origin of angular vector [th 1,th 2,th 3,th 4,th 5]=[0,0,0,0,0]is the arm’s neutral position.The minimum angle of the J 4is set at 10degrees in order to avoid the singularity.The range of motions of the EMAS II is narrower than that for ADL,because the EMAS II takes into account the use only for activities which are done at a table.In addition,the maximum joint torques of the EMAS II are smaller than that of healthy upper limb.However,it has enough torque to support a man lifting 0.5[kg ]of bottle on his hand.The feasibility of assistance with limited range of motions and joint torques is discussed in chapter 3.

The unactuated slider mechanism is shown in Figure 7to allow for upper body and shoulder girdle motions.The slide rail passively moves 200mm on a slider,while a slider generally slides on a slide rail.The weight of EMAS II with a user’s arm is directory loaded to the special stand through an attachment which is tilting within a range of 0to 50degree to the ?oor.Here,a coordinate system is de?ned as shown in Figure 8.Then,the working surface of wrist joint,

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Figure 5.Wire

arrangement.

Figure 6.De?nition of positive direction of each joint.

Table 2.Raneg of motion.

The EMAS II The EMAS II The EMAS II Human for ADL Min.Angle Max.Angle Range of Motion

Range of Motion

[degree]

[degree]

[degree]

[degree]

θ107070100θ208080110θ309090135θ4

10130110150

where the height of the wrist joint is ?xed at 200[mm]below the shoulder joint and the elbow joint is located above the level of wrist joint,is shown in Figure 9.

Table 3.Maximum joint torques.

The EMAS II [Nm]

Unimpaired Arm [Nm]

θ147.353.5θ222.953.9θ315.053.6θ4

38.5

81.0

2.3.Derivation of joint angles

When a user uses the EMAS II,he/she inputs three-dimensional wrist position through a user interface while the number of active joint is four.Therefore,at least one condition of constraint is required to control all joints.The

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Figure 7.Unactuated slider for trunk and shoulder

girdle.

Figure 8.Coordinate system of working space.The origin of this coordinate system corresponds approximately to the center of user’s right shoulder

joint.

Figure 9.Range of motion of the EMAS II at a table.The origin is the center of the left shoulder.

condition of constraint is derived from motion measurement of upper body.Although there have been similar researches for motion measurement and analysis of upper limb,[11,12

]

Figure 10.Arrangement of markers for the motion capture.

none of them refer to arm support.We consider eating a meal to be one of the most important tasks to help the patients to lead more independent lives and to reduce the caregiver burden.Therefore,in this study,upper limb mo-tions while people eat a meal without dropping food are measured in order to develop the expression for the condition of constraint.

2.3.1.Meal motion measurement

The meal motions were captured by the PhaseSpace IMPULSE system [13]of PhaseSpace Inc.Nine markers were attached to the EMAS II and a subject,and eight cameras tracked them (Figure 10).The capturing rate was 120frames per second.During the measurement,a subject who was wearing the EMAS II picked up foods from two plates on a table and ate them in ?ve times each.The plates were put in a row in front of the subject and the height of the table was 690[mm].This measurement was done by three subjects (Subjects 1,2,and 3),one was a woman aged twenty-two and two were men aged twenty-two and thirty,respectively.All subjects were physically unimpaired and right dominant.

2.3.2.Measurement results

Figure 11shows one example of the result of the motion measurement,where the second subject scooped food (the gray area)and carried it to the mouth (the white area).From here,we focus on the motion for carrying the food to the mouth for getting the condition of constraint.

One example of the scatter diagrams of the wrist posi-tion (x w ,y w ,z w )and the elbow position (x e ,y e ,z e ),and their approximated curves are shown in Figure 12.Then,it is found that all R-squared values of the approximated curves representing the relationship between z w and z e of

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all subjects are over 0.9.Here,Figure 13shows the scat-ter diagrams and approximated curves of the relationship between z w and z e of all

subjects.

Figure 11.Example of result of the meal motion analysis.

The mean curve of these approximated curves are shown in Figure 14,which is expressed by

z e =?0.0008z w 2+0.5316z w +171.23.

(1)

Using this correlation model,the z e is ?xed from the wrist position.y e and x e are also ?xed as follows:

y e =

?Q ±

Q 2?P R

P

,(2)P =x w 2+y w 2,(3)

Q =z w z e y w ?Ay w ,

(4)R =(A ?z w z e )2+x 2w (z 2e ?L 21),

(5)A =

L 21+L 23?L 22

2,(6)L 3=

x 2w +y 2w +z 2w

,(7)

x e =???L 23+L 21?L 2

2?2(y e y w +z e z w )2x w

,

if x =0

L 21

?y 2e ?z 2e ,

if x =0

,(8)

where L 1is length of user’s upper arm and L 2is that of

forearm,respectively.In addition to the above

expressions,

Figure 12.Example of relationships between the wrist position and the elbow position.

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D

o

w

n

l

o

a

d

e

d

b

y

[

S

h

a

n

g

h

a

i

U

n

i

v

e

r

s

i

t

y

]

a

t

2

3

:

4

5

2

N

o

v

e

m

b

e

r

2

1

3

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Figure 14.Approximation curves of relationship between the

height of the wrist joint and that of the elbow joint.

Table 4.Error of elbow position.Subject Plate RMS of Error [mm]

Subject 1Left 33.12Subject 1Right 19.66Subject 2Left 58.58Subject 2Right 27.79Subject 3Left 51.51Subject 3Right

30.31Mean

36.83

considering the range of motion (Table 2),we obtain the elbow position.

Finally,each joint angle θ1...θ4is given by,

θ1=cos ?1

y w ? 1+L 2

L 1

cos θ4 y e L 2cos θ2sin θ4

,(9)θ2=sin

?1

x w ? 1+L 2

L 1cos θ4 x e L 2sin θ4

,(10)θ3=sin ?1 ?

x e

L 1cos θ2

,and (11)θ4=cos ?1 ?L 21+L 22

?(x w 2+y w 2+z w 2)2L 1L 2

.

(12)The precision of the model is evaluated by comparing the measured elbow position of an elbow joint and the predicted position based on the model.RMS of errors of them are shown in Table 4.The results show that an mean error is 37[mm].In order to make up for the personal difference,the third term is adjusted according to the user’s shape or height of the table used.

2.4.Control approach and user interfaces

When we develop assistive devices,it is also necessary to develop easy-to-use user interfaces which take advantage of

patients’residual functions.In this section,the user inter-faces and control approach of the EMAS II are mentioned.2.4.1.Control approach

The EMAS II has two control modes:manual control and semi-automatic control.A user can control three-dimensional coordinate of his/her wrist position through the user interface with the manual control.On the other hand,the semi-automatic control is developed in order to improve the utility and ef?ciency of the system operation.In this control mode,the user’s upper limb is automatically moved to pre-established position by pressing a switch.For example,if the user set his/her mouth position,she/he can bring food to his/her mouth smoothly and ?nish the meal in a shorter time.The control ?ows of each mode are shown in Figures 15and 16.

2.4.2.Trackball type interface

We propose three kinds of user interfaces.When user uses the trackball interface shown in Figure 17,the controller measures the pulses of the trackball interface at every 5.0[ms ]and determines the wrist position.

During low-speed rotation,the controller determines the

target wrist position,W re f (x ref w ,y re f w ,z ref

w )in the coordi-nate system shown in Figure 8,as shown below:

x ref w =x w +C 1x rot ,(13)

y ref w =y w +C 1y rot ,

and

(14)z ref w =z w +C 2z rot ,

(15)

where W (x w ,y w ,z w )is the current wrist position,

R (x rot ,y rot ,z rot )is the amount of change of the rotation of the trackball,and C 1,C 2are the arbitrary constants.On the other hand,during high-speed rotation,the controller continues only to measure the pulses until the rotation speed becomes lower than a threshold.Meanwhile,the arm is controlled to be held in the same position.Then,the con-troller determines the target wrist position and straight-line

trajectory.Let R t (x t rot ,y t rot

)denote the number of total rotations of the ball,a denote the arrival time and C 3,C 4denote an arbitrary constant.Then,the target position and arrival time is calculated as below:

x p =x w +C 3x n x t

rot ,

(16)

y p =y w +C 3y n y t rot ,and (17)

t =C 4|n |

.(18)

Finally,change of velocity v (v x ,v y )with time is deter-mined by the expression shown below:

|˙v |=?4b

t

2 x ?t 2

2+b ,(19)

b =3l

2t

,and

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Figure 15.Control ?ow of the manual

control.

Figure 16.Control ?ow of the semi-automatic

control.

Figure 17.Trackball type interface.l =

(x p ?x w )2+(y p ?y w )2.(21)

In this way,switching the action at low-speed and high-speed rotation,the user can move the arm over a long distance at once or move the arm delicately depending on the situation.Moreover,pressing the switch at the corner of the trackball interface,the control mode is shifted to the semi-automatic mode,and the wrist position is moved to the pre-established position without any operation.When the EMAS II is ?nished moving the arm,the control mode is shifted to the manual mode again.

2.4.

3.Joystick type interface

Figure 18shows the joystick type interface which has two

joysticks.

Figure 18.Joystick type interface.

The controller measures the voltages V (x V ,y V ,z V )from each joystick which denote the tilt of the joysticks.Then,the target wrist position is determined as below:

W re f =W +C 5V ,

(22)

where C 5is the arbitrary constant.If the voltage which denotes the right-and-left tilt of the right joystick exceeds a threshold,the control mode is shifted to the semi-automatic mode.

Operations of the trackball type interface and the joystick type interface in x and y directions similarly corresponds to a wrist motion in x and y,respectively,so that a user could control positions of the wrist joint intuitively through less training iterations.

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Figure 19.BEP type interface

2.4.4.BEP based interface

The Bio-Electric-Potential (BEP)based interface is devel-oped.BEP signals are often used as an instinctive user interface for assistive devices.There have previously been researches about motion discrimination of upper limb and control of assistive arm by BEP.[14]However,in case where a patient with muscle weakness operates assistive devices using only BEP signals,the control of three-dimensional position of the arm is of great dif?culty because it requires a model to decode arm motion from BEP signals of multiple muscles.In many cases,BEP signals of the patient are too weak to use for a user interface.However,in some cases,BEPwith large signal-to-noise ratio may be measured from part of the muscles.In this research,we propose a BEP based interface intended for the patient whose del-toid and biceps can give off BEP signals with relatively large S/N ratio.A user is supposed to have capability to control the anteroposterior position of the wrist joint with this BEP based interface.When he/she controls the three-dimensional position by using BEP signals,the trackball type or joystick type interface is used as a supplementary interface.The sheet shown in Figure 19is consisting of matrix of six active electrodes.Again of the active electrode is 10,000.

One of the sheets is attached to the skin surface above deltoid,and the other is above biceps.Although strength of the BEP signals vary depending on the position of the electrodes,positioning of the sensor sheet does not require high accuracy because of the grid-like arranged multiple electrodes.For the control of EMAS II,the controller mea-sures the BEP signals and integrates the signals (IBEP).Let ch (ch =1...12)denote the channel number of electrode and T (=300[ms ])denote an integration time,and then the IBEP is de?ned by

I B E P ch (t )=

t

t ?T

|B E P ch (τ)|d τ.(ch =1...12).(23)Table 5.Relationship between motion and magnitude of IBEP.

I B E P b sum

I B E P b sum >T H b

I B E P d sum

Stop

Back I B E P d sum >T H d

Forward

Back

Figure 20.Knobs for threshold adjustment.

Next,the sum of all channels of deltoid,I B E P d sum

,and that of all channels of biceps,I B E P b sum

,are calculated.They are compared with threshold T H d and T H b ,respectably.Finally,the arm motion is determined according to the mag-nitude relation of each value and the threshold as shown in Table 5.The thresholds are adjustable according to the strength of the BEP signals of each user using two knobs (Figure 20).The thresholds and the sum of current bioelec-tric potential are displayed on a monitor shown in Figure 21.The direction of the motion is selected by the above approach,however,the moving velocity is constant with

the value of I B E P d sum and I B E P b sum

.3.Experiments

3.1.Position accuracy

3.1.1.Experimental settings

In order to evaluate the position accuracy of EMAS II,the wrist position is measured using the motion capture system.During this experiment,two bottles ?lled up with one liter of water were loaded to the EMAS II in order to mimic weight of user’s arm (Figure 22).The EMAS II repeated reciprocation of the wrist part between table and mouth for 10times.As the index,the position error of the wrist joint is considered.Let (x enc ,y enc ,z enc )denote the wrist position calculated from the motor encoders,(x cap ,y cap ,z cap )de-note the wrist position calculated using data from the motion capture system,then the E enc and E cap were de?ned as follows:

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Figure 21.Display for BEP:From ch.1to ch.6:IBEPs of deltoid.From ch.7to ch.12:IBEPs of biceps.Heavy line of D is sum of IBEPs of deltoid.Thin line of D is the thresholds,T H d .Heavy line of B is sum of IBEPs of biceps.Thin line of B is the thresholds,T H b

.

Figure 22.The EMAS II with bottles.Two bottles work as weights of user’s upper limb.

E enc = (x ref ?x enc )2+(y ref ?y enc )2+(z ref ?z enc )2,

(24)

E cap =

(x ref ?x cap )2+(y ref ?y cap )2+(z ref ?z cap )2.

(25)

3.1.2.Measurement of position accuracy

Figure 23shows the three kinds of wrist joint trajectories,reference wrist position,the actual wrist position

calculated

Figure 23.Wrist joint position.

from the encoders of the motors,and the actual wrist po-sition measured by the motion capture system.The wrist position data from the motion capture system were offset so that their mean values correspond to each other because the coordinate origins of the EMAS II and the motion cap-ture system were different.Rapid change of the reference position can be found at intervals,but that comes from the change of the control mode and is not a problem.Figure 24shows that the wrist joint positioning error E cap was 39.0[mm]at most,the mean of E cap was 17.6[mm],and standard deviation of E cap was 11.0[mm].Meanwhile,the error E enc was 39.6[mm]at most,the mean of E enc was

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Figure 24.Position error of the wrist joint.

Table 6.Foods for the experiment.Curry 130[g]Rice 200[g]Potato salad

120[g]

Yoghurt

70[g]

Water

200[ml]

16.6[mm],and standard deviation of E enc was 13.0[mm].The sources of errors were steady-state error of the PD control and the effect of friction and expansion of the cables.However,it will be little problem to eat a meal because the user can adjust the position by manual control mode.3.2.Meal assistance experiment with healthy person 3.2.1.Experimental settings

A healthy subject regarded as a muscular dystrophy patient ate a meal with the EMAS II.List of foods for an experiment was shown in Table 6

.

Figure 25.Each action of eating.

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Table 7.Subjective assessment of user interface by a patient.Type of user interface Feedback from a patient

Joystick type Controllable,but the levers are slightly stiff.

Trackball type Trackball is easier than the joystick type,but the dial to control height of wrist is dif?cult to be handled.

BEP type

Support of ?ex motion of elbow joint is intuitively started.Support for extension of the elbow joint did not always start.

Each plate was ?xed to a tray of 420-by-295[mm]on a table.The height of the table was 700[mm],which meets the Japanese Industrial Standards (JIS).The subject was asked to pick foods from two plates with equal frequency.In order to verify usability of the user interface device and the assistive system,the time spent on meal was selected as an index.It is recommended to ?nish a meal within 30minutes,because a sense of satiety is automatically induced in 30minutes.

3.2.2.Results of the meal assistance

Figure 25shows the each action during the ?rst cycle of eating in the second experiment:

Action 1Pick up a spoon in manual control mode Figure

25(a)

Action 2Operate the hand position to pick a food on a plate

in manual control mode Figure 25(b)

Action 3Bring the spoon up to the mouth in automatic

control mode Figure 25(c)

Action 4Bring the spoon back to the same plate as before

in automatic control mode Figure 25(d)The user ?nished her meal in 18min.40sec.with 40times of to-and-fro motions between her mouth and plates.3.3.Clinical trial with a patient

We applied the EMAS II for a progressive spinal muscular atrophy (PSMA)patient.The feedback from the patient on usability of the user interfaces is listed on Table 7.

Moreover,the patient also gave us opinions about ade-quacy of the shoulder mechanism.

?The range of movement of the shoulder ?exion motion was enough to do desk works.?The working space on a table was narrow.

3.4.Discussion

Through the ?rst and second experiments,we con?rmed that the EMAS II is available for meal assistance although the absolute positioning error of the wrist joint was less than 40mm.At the clinical trial,we obtained some improvements

about usability of the user interfaces and shoulder design.Stiffness of the joystick needs to be adjustable for a user,and the dial for the trackball type interface needs to be explored other alternatives.In addition,in order to use the BEP type interface,we have to select appropriate muscles to be used as a signal for corresponding motions.

4.Conclusions

This paper introduced the EMAS II that helps the patients with muscular disease doing tasks at table such as eating meals.The user is assumed to have enough capabilities to control his hand and wrist joint.The EMAS II requires patient’s operation,by using their residual functions.The left hand and wrist joint operate the user interface device;whereas the right hand and wrist joint pick or scoop foods.The user’s involvement in meal activities contributes not only to maintain their musculoskeletal conditions but also to keep fundamental dignity of individuals.

The correlation between the height of the wrist joint and that of the elbow joint are formulated based on the motion analysis of a healthy person,and then natural arm motions using multiple degrees of freedom of the EMAS II were achieved based on the formula.Through a pilot experiment,it is con?rmed that the healthy person who imitated a muscle dystrophy patient ?nished his/her meal in 20minutes.Finally,through a clinical trial,we con?rmed the usability of the user interfaces and adequacy of the exoskeleton design.Acknowledgements

This research is supported by the Cabinet Of?ce,Government of Japan and the Japan Society for the Promotion of Science (JSPS)through the Funding Program for World-Leading Innovative R&D on Science and Technology (FIRST Program).

Notes on

contributors

Yasuhisa Hasegawa received the BE and ME degrees from Nagoya University,Japan,in 1994and 1996,respectively.From 1996to 1998,he worked for Mitsubishi Heavy Industries Ltd,Japan.He joined Nagoya University,in 1998,as a Research Associate and received the Dr degree in Engineering from Nagoya University,in 2001.From 2003to 2004,he was an Assistant Professor at Gifu

University.He moved to the University of Tsukuba,in 2004.He

D o w n l o a d e d b y [S h a n g h a i U n i v e r s i t y ] a t 23:45 02 N o v e m b e r 2013

1398Y.Hasegawa et al.

is currently an Associate Professor of University of Tsukuba.He is mainly engaged in the research ?elds of physically assistive robots,dynamic motion control for bio-inspired robots.He is currently an executive board member of Robotics Society of Japan.He received Best Paper Awards at the 2003IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003),the 2004International Symposium on Micro-Nano Mechanics and Human Science (MHS 2004),and IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM

2013).

Saori Oura received BE and ME degree from University of Tsukuba,Japan in 2010and 2012,respectively.From 2012,she works for Honda R&D Co.,

Ltd.

Junji Takahashi received his PhD degree in engineering from Nagoya University,Japan in 2010.He was formerly a Research Fellow on GCOE (Cybernics)project at the Graduate School in Systems and Information Engineering in University of Tsukuba,and a postdoctoral Research Fellow of the Depart-ment of Micro-Nano Systems Engineering in Nagoya University.He is currently an Assistant

Professor of Aoyama Gakuin University.His research interests are Mechatronics,Distributed Autonomous Robotic Systems,Human Robot Interaction,and Bio-signal Processing.He is a member of IEEE,RSJ,and SICE.He received a Best Paper Award at the 9th International Symposium on Distributed Autonomous Robotic Systems (DARS2008),a prize of encouragement from the Chubu Branch of The Society of Instrument and Control Engineers (SICE),2012.

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外骨骼机器人研究发展综

—－可编辑修改，可打印—— 别找了你想要的都有！ 精品教育资料——全册教案，，试卷，教学课件，教学设计等一站式服务——

全力满足教学需求，真实规划教学环节 最新全面教学资源，打造完美教学模式 外骨骼机器人研究发展综述 李罗川

摘要 外骨骼机器人又称可穿戴机器人，是一种结合了人的智能和机械动力装置的机械能量的机器人。外骨骼机器人融合了传感、控制、驱动、信息融合、移动计算等综合技术为作为操作者的人提供一种可穿戴的机械机构。本文介绍了外骨骼机器人的发展历史以及国内外研究现状，对外骨骼机器人的关键技术：机械结构设计，驱动单元，控制策略进行了研究，分析了其技术难点最后对其发展前景进行了说明。 关键词：外骨骼机器人关键技术

引言 (5) 1.发展历史及现状 (6) 1.1国外发展历史现状 (6) 1.2国内发展历史现状 (9) 2.关键技术分析 (11) 2.1外骨骼机器人的结构设计 (11) 2.2外骨骼机器人驱动单元 (12) 2.3外骨骼机器人的控制策略 (12) 3.外骨骼机器人技术难点分析 (15) 4.前景展望 (17) 4.1 外骨骼机器人的研究方向 (17) 4.2外骨骼机器人技术的应用 (17)

现代机器人所具有的机械动力装置使得机器人可以轻易地完成很多艰苦的任务，比如举起、搬运沉重的负载等。虽然现代机器人控制技术有了长足的发展，还远达不到人的智力水平，包括决策能力和对环境的感知能力。与此同时，人类所具有的智能是任何生物和机械装置所无法比拟的，人所能完成的任务不受人的智能的约束，而仅受人的体能的限制。因此，将人的智能与机器人所具有的强大的机械能量结合起来，综合为一个系统，将会带来前所未有的变化，这便是外骨骼机器人的设计思想。外骨骼机器人实质上是一种可穿戴机器人，穿戴在操作者的身体外部，为操作者提供了诸如保护、身体支撑等功能，同时又融合了传感、控制、驱动、信息融合等机器人技术，使得外骨骼能够在操作者的控制下完成一定的功能和任务。本文通过介绍外骨骼机器人的发展历史及研究现状进一步分析了外骨骼机器人的关键技术，并对其技术难点以及发展前景作了说明，以期在全面认识外骨骼机器人基础上对其开展进一步深入研究。

外骨骼机器人设计、控制机理研究

第二十一届“冯如杯”学生课外学术科技作品竞赛项目论文 外骨骼机器人设计、控制机理研究 院（系）名称自动化科学与电气工程学院 专业名称自动化 学生姓名刘旭郑博文徐健伟 学号刘旭38030410 郑博文38030423 徐健伟38030518 指导教师刘正华副教授 2011年4月1日

摘要 外骨骼，类似某些动物的外壳，是一种能穿在人身上,提供额外的动力的机械装备，能够实现行动障碍人士的康复训练以及负重行走等功能。它主要分为三个部分：机械部分，软件部分，电气部分。其中机械部分的主要作用是承担负重，保证系统能实现运动的功能；软件部分主要用于整个系统的数据采集、控制信号的发出；电气部分主要用于给系统供电、完成信号采集、发送和运动的功能。我们设计制作了一种外骨骼机器人。本文针对此项作品主要介绍了当前外骨骼机器人的研究现状和本作品的制作背景，阐述了一种负重型外骨骼机器人的设计过程及相关结构。本文是对“外骨骼机器人设计、控制机理研究”作品的比较全面的介绍。 关键词外骨骼，机器人，PID控制，电机控制，虚拟样机 Abstract Exoskeletons, like the shells of some sorts of animals, are a kind of mechanical equipment that can help the disabled to learn to move normally and provide the users with extra strength to bear more than he can actually do walking or running. In general, it can be divided into three parts, mechanical part, software part and electrical t part. Among these, the mechanical part is used to bear the weight, the software part is to get state data and send out control signal and the electrical part is to power the system, pick signal and move. We have already made a sort of this, and with regard to it, this article is mainly about the previous studying condition and the background of this work. In addition, the procedure of our designing and working with the kind of exoskeletons is specifically described. This article is a comprehensive introduction to our work …The design of a sort of exoskeletons and study of how to control it?. Abstract Exoskeletons, Robort , PID Control, Motor control, Virtual prototype

外骨骼机器人发展

外骨骼技术研制始于1960 年代的美国，最早的研究成果是美国通用公司研发的Hardiman 外骨骼系统，其主要采用电机驱动控制，可以轻易举起重物。 1978 年，美国麻省理工学院研究出“被动式外骨骼助力机器人”。MIT的外骨骼下肢助力机器人能够在负载36公斤的情况下行走1m/s，其中80%的负重被传递到地面上。它的关节自由度配置包括髋关节有3 个自由度，膝关节 1 个自由度。穿戴者与机器人在肩膀、腕关节、大腿和脚部连接，机器人总重量是11.7Kg。驱动方式不采用电力驱动，只利用弹簧储能和变阻尼器驱动关节驱动。髋关节伸/屈运动时，伸运动时弹簧释放能量，屈运动时弹簧储存能量，膝关节利用磁流变阻尼器，踝关节利用碳纤维弹簧缓冲脚后跟对地面的冲力。传感器系统是由安装在外骨骼下肢助力机器人外壳的应变桥式应变片传感器和安装在膝关

节的电位计组成。 2004年，伯克利分校研制出的下肢外骨骼机器人BLEEX是DARPA项目的第一台带移动电源和能够负重的下肢外骨骼机器人。BLEEX由--个用于负重的背包式外架、两条动力驱动的仿生金属腿及相应动力设备组成，使用背包中的液压传动系统和箱式微型空速传感仪作为液压泵的能量来源，以全面增强人体机能。BLEEX的每条腿具有7个自由度(髋关节3个，膝关节1个，踝关节3个)，在该装置中总共有40多个传感器以及液压驱动器，它们组成了一个类似人类神经系统的局域网。BLEEX的负重量能达至75kg，并以0．9m／s的速度行走，在没有负重的情况下，能以1．3m／s的速度行走。

目前，洛克希德·马丁公司和伯克利分校共同研制了新一代外骨骼机器人HULC 。这款新型外骨骼继承了BLEEX 的优点，对一些液压传动装置和结构进行了优化设计，不但能够直立行进，还可完成下蹲和匍匐等多种相对复杂的动作，穿上HULC 后能够明显降低人体对氧气的消耗量。在一次充满电后，HULC 可保证穿着者以4．8km ／h 的速度背负90kg 重物持续行进一个小时。而穿着HULC 的冲刺速度则可达到16km ／h 。HULC 穿戴起来也非常方便，士兵只需将腿伸进靴子下方的足床，然后用皮带绑住腿部、腰部以及肩部即可，完全脱下需30秒的时间。

外骨骼助力机器人研究

外骨骼助力机器人研究现状与关键技术 分析 王庆江 深圳第二高级技工学校广东深圳 518000 摘要：运用比较传统的运载方法以及在工具受到多方面因素的制约，在比较复杂的地形条件之下，传统运载工具不能够很好的工作，而外骨骼助力机器人有效地解决了这个问题，是一个非常明显的突破。因此，在当前世界各地，外骨骼助力机器人的研究有着非常好的前景。本文从不同方面分析外骨骼助力机器人的发展状况，主要分析了外骨骼助力机器人所涉及到的关键技术，并且作出深入的研究。 关键词：外骨骼助力机器人；研究现状；关键技术外骨骼助力机器人是一种全新的现代化装置，这种机器人融合多种信息,控制系统传感系统集于一身,并且为穿戴人员控制好功能和任务。外骨骼助力机器人是一种前沿技术装备，受到多方的关注并且取得了突出的效果。在我国，外骨骼助力机器人研究借鉴先进技术，并且不断地创新，主要研究外骨骼助力机器人在我国国内的发展现状以及其关键技术分析。 1.在国内外，外骨骼助力机器人的研究现状分析 随着时代的进步以及科技的不断发展，最新型的材料和技术充分应用在外骨骼助力机器人的发明上，促使外骨骼助

力机器人得到很好的发展。在一些发达国家，对外骨骼助力机器人进行改良，并且不断创新，经过努力，在我国国内对于外骨骼助力机器人的发明和创新也取得了很明显的成效。下面将归纳分析目前为止国内外外骨骼助力机器人的研究状况。 1.1国外对于外骨骼助力机器人的研究状况分析 表1 国外对于外骨骼助力机器人的研究表 1.2我国国内对于外骨骼助力机器人的研究状况分析 表2 国内对于外骨骼助力机器人的研究表 2.外骨骼助力机器人关键技术分析 2.1驱动技术 2.1.1液压驱动 通过运用液压驱动能够在很大程度上帮助外骨骼助力

下肢外骨骼机器人研究现状及发展趋势

下肢外骨骼机器人研究现状及发展趋势 外骨骼机器人是可以穿戴在人身体外部的人机一体化机械结构，它与穿戴者一起行走，为其提供助力和保护。详述了下肢外骨骼机器人在各领域的应用，并分别列举各领域的应用实例，分析了下肢外骨骼机器人在设计过程中要解决的关键技术，介绍了外骨骼机器人几种不同的驱动方式，并进行对比分析其优缺点，对下肢外骨骼机器人技术的发展趋势进行预测。 标签：下肢外骨骼；机器人；可穿戴 Abstract：Exoskeleton robot is a human-machine integrated mechanical structure which can be worn on the outside of the human body. It walks with the wearer to provide assistance and protection. The applications of the lower limb exoskeleton robot in various fields are described in detail，and the key technologies in the design of the lower limb exoskeleton robot are analyzed. This paper introduces several different driving modes of exoskeleton robot，analyzes their advantages and disadvantages，and forecasts the development trend of lower limb exoskeleton robot technology. Keywords：lower limb exoskeleton；robot；wearable 引言 在自然界中，外骨骼是一种能够保护和支撑生物柔软內部器官的外部结构，比如螃蟹、蜗牛、昆虫等生物的甲壳。由此，科学们提出了外骨骼机器人的概念-用于保护穿戴者并为其提供额外的动力。比如家庭用辅助型外骨骼机器人可协助年老体弱者正常行走；医用康复外骨骼机器人可使残疾人像正常人那样重新站立起来；军用负重式外骨骼可使士兵在携带负载的情况下依旧健步如飞。由此可见，外骨骼机器人既有研究价值，也有很高的实用价值，已成为国内外科学家们研究的一个重点方向，其发展前景十分广阔[1]。 1 下肢外骨骼机器人研究现状 随着科学技术的发展，比如在仿生学技术、智能控制技术、传感器技术和材料技术等相关领域的突破，外骨骼机器人技术的研究也取得了很大的进步[2]。下面简要介绍下肢外骨骼机器人的研究现状。 外骨骼机器人主要分为三大类。第一类是助力型外骨骼机器人，主要面向健康人群，提高人的负载能力，用于军事领域，可增强士兵负重能力。这方面比较成功的是洛克希德·马丁公司研制出的HULC型外骨骼机器人[3]（如图1 所示）。它总质量约为32kg，主要通过电池提供能量，蓄电池在充满电之后可使士兵在负载90kg并以16km/h的速度行驶的情况下行走一个半小时。其特点

发展外骨骼机器人的必要性

军队发展外骨骼机器人必要性外骨骼机器人技术是融合传感、控制、信息、融合、移动计算,为作为操作者的人提供一种可穿戴的机械机构的综合技术。他是指套在人体外面的机器人，也称“可穿戴的机器人”。人体外骨骼助力机器人起源于美国1966年的哈德曼助力机器人的设想及研发，到今天整体仍处于研发阶段，能源供给装置以及高度符合人体动作敏捷及准确程度要求的控制系统和力的传递装置都有待大力投入研发和试验尝试。他是是一种模仿人体结构特点设计的外穿型机械骨骼，内部配备有液压传动装置和可像关节一样弯曲的结构设计，不但能够直立行进，还可完成下蹲和匍匐等多种相对复杂的动作。他把重量通过电池驱动的金属骨骼转移到地面上。先进的便携式微型计算机可以使得这种外骨骼与人的运动保持协调一致。他成倍的增加人类 的体能。 一必要性1：不堪重负的士兵 这是美军陆军的标准装备。 注意，这只是标准装备，事实上，执行具体任务时，负重远比这多。例如机枪手要携重得多的m249轻机枪，和大量的机枪弹。还有士兵要背负沉重的火箭筒，甚至野战

时携带睡袋等装备。这都是沉重的负担。许多士兵已经换上各种疾病。例如颈椎病，。极大地体力消耗和精神压力困扰绝大多数士兵。而外骨骼可以是这一切轻松解决。 他可以使士兵轻松背负七八十公斤的中午而没有疲劳之感，外骨骼承担了负重的任务。健康问题极大得到了解决。 二必要性2：超级战士

以美军HULC为例，HULC动力源为两块总重量3.6千克的锂聚合物电池。在一次充满电后，HULC可保证穿着者以4.8公里/小时的速度背负90千克重物持续行进一个小时。而穿着HULC的冲刺速度则可达到16公里/小时。士兵配备他以后，就可以负载重型防弹衣长途跋涉而不觉疲惫，而防弹衣对士兵生命尤为重要，他可给士兵全方位。有重点的防护，真正做到刀枪不入。而且士兵再也不会为永远不足的弹药发愁了。几十公斤的负重可以保证足够的弹药，甚至可以携带迫击炮等较强的火力。在遭到围攻时，极大的奔跑速度让敌人望尘莫及。这是真正的超级战士。 现在，建设高效的军队成为世界主流，这要求用尽可能少的士兵去执行更多的任务，完全使用机器人在现阶段不现实，而外骨骼正好填补了这个缺口。美国的HULC1已经接近实用化。 现在战争更多集中在反恐领域，这就使大规模战争成为历史。特种部队被更多使用。他们执行的大多是高危高风险的任务。队员素质要求高，一般从侦察部队和空降部队中挑选体格健壮、机智勇敢、文化程度高、具有献身精神和有一定作战经验的人员。执行渗透，侦查，抓获，斩首等价值极高的任务。他们抵达战区必须隐蔽，往往经过丛林等荒无人烟的地带，装备外骨骼后，他们抵达战区仍然精力旺盛，成功率提高。充足的是保持战斗力的关键。 对于炮弹装填手，意义非凡。他们可以毫不费力的举起几十公斤的炮弹，而不会得腰肌劳损。迫击炮手可以更灵活的移动。一名士兵

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外骨骼机器人研究发展综述 李罗川

摘要 外骨骼机器人又称可穿戴机器人，是一种结合了人的智能和机械动力装置的机械能量的机器人。外骨骼机器人融合了传感、控制、驱动、信息融合、移动计算等综合技术为作为操作者的人提供一种可穿戴的机械机构。本文介绍了外骨骼机器人的发展历史以及国内外研究现状，对外骨骼机器人的关键技术：机械结构设计，驱动单元，控制策略进行了研究，分析了其技术难点最后对其发展前景进行了说明。 关键词：外骨骼机器人关键技术

目录 引言 (4) 1.发展历史及现状 (5) 1.1国外发展历史现状 (5) 1.2国内发展历史现状 (9) 2.关键技术分析 ...................................................................................................................... 1..1 . 2.1外骨骼机器人的结构设计..................................................................................... 1..1... 2.2外骨骼机器人驱动单元.......................................................................................... 1..2... 2.3外骨骼机器人的控制策略..................................................................................... 1.. 3... 3............................................................................................................ 外骨骼机器人技术难点分析................................................................................................................. 1..6... 4............................................................................................................ 前景展望 ........................................................................................................................................................ 1..8 . 4.1外骨骼机器人的研究方向..................................................................................... 1..8... 4.2外骨骼机器人技术的应用 .................................................................................. 1...8..

一年半超过Cyberdyne：这家公司要用大家电的价格卖外骨骼机器人

一年半超过Cyberdyne：这家公司要用大家电的价格卖外骨 骼机器人 讲外骨骼机器人的故事，一般有两种方式，一种是“超级英雄”：机甲战衣令你成为托尼·斯塔克。另一种故事角度就是“拯救”：外骨骼机器人能增强人的肌肉和行动能力，令很多下肢行动不便甚至瘫痪的人群重获行走能力。无论是从哪个角度说，外骨骼产品都是“酷”的，不管是关于变得强大的梦想，还是关于重获健康的渴望。在11 月17 日深圳高交会上，雷锋网见到了一款国内的外骨骼机器人设备S1 （Scream One，尖叫1 号），其开发者是上海尖叫智能科技公司，这是他们的第一代量产机型。这次高交会，尖叫科技举办了一场小型技术交流会，讲述的就是关于“拯救”的故事。加入了人工智能技术的“随动派”我们熟知的外骨骼机器人公司，有以色列Rewalk 和日本公司Cyberdyne，但是两家产品有很大不一样。Rewalk 是“拐杖派”，是机器带着人走，所以为了保持上肢的平衡，需要患者拄着拐杖。患者适应机器的步伐，需要很长的一段时间。Cyberdyne 是“随动派”，人的行走意志处于主导地位，它们家的产品HAL 通过搜集人体表面的肌肉电信号，来对机器人传达行走的意志，从而帮助人行走。（左图：Rewalk，右图：HAL）但二者有一个共同点，那就是在软件方面使用的是纯编程的技术。缺

点也正是这里：代码写得再好，也无法完全适应人体步态的变化。而尖叫科技的外骨骼产品，则属于加入了人工智能技术的“随动派”，S1 号不用拐杖，能实时与人体交互，获得最贴合的移动方式。（样机行动图）本次所展示的S1 号机型，有12 个传感器分布在腰部、腿部两侧、脚底等部位，每一天用户使用的过程中，传感器搜集人体不同维度的信息，包括肌肉电、光栅、肌肉表面舒张压力等。这些信息传到位于腰部的本地CPU，当设备连上WIFI 之后，CPU 数据上传到云端，云端的深度学习网络会对新的数据进行学习，从而“定制化”地为每一个用户调整行走模型。2 个月迭代一次，单机为一台大家电的价格尖叫科技是2015 年初成立的，几乎每2 个月就迭代一次产品，S1 是其第六代产品。S1 大约重10kg ，针对不同人群有不同的尺码，类似于商场里卖的衣服，分S、M、L号。被问及产品的价格时，CTO 李牧然表示：“我们希望三年内能达到一台大家电的价格，当然这不是初始定价，但这是我们努力的方向。”这就意味着，尖叫的外骨骼产品的未来定价大约会在几万人民币，这在交流会的现场引发一阵不小慨叹声。因为Rewalk 和Cyberdyne 公司的产品，售价分别高达约7 万美金和20 多万美金。这样低的价格，很大程度上得益于其研发周期短，这与大环境的时代优势密不可分。首先是前辈们的技术积累：Rewalk 研发了7 年，Cyberdyne 研发了十几年时间，这些公司虽

外骨骼机器人研究发展综教学提纲

外骨骼机器人研究发 展综

外骨骼机器人研究发展综述 李罗川

摘要 外骨骼机器人又称可穿戴机器人，是一种结合了人的智能和机械动力装置的机械能量的机器人。外骨骼机器人融合了传感、控制、驱动、信息融合、移动计算等综合技术为作为操作者的人提供一种可穿戴的机械机构。本文介绍了外骨骼机器人的发展历史以及国内外研究现状，对外骨骼机器人的关键技术：机械结构设计，驱动单元，控制策略进行了研究，分析了其技术难点最后对其发展前景进行了说明。 关键词：外骨骼机器人关键技术

目录 引言 (5) 1.发展历史及现状 (6) 1.1国外发展历史现状 (6) 1.2国内发展历史现状 (10) 2.关键技术分析 (12) 2.1外骨骼机器人的结构设计 (12) 2.2外骨骼机器人驱动单元 (13) 2.3外骨骼机器人的控制策略 (14) 3.外骨骼机器人技术难点分析 (17) 4.前景展望 (19) 4.1 外骨骼机器人的研究方向 (19) 4.2外骨骼机器人技术的应用 (19)

引言 现代机器人所具有的机械动力装置使得机器人可以轻易地完成很多艰苦的任务，比如举起、搬运沉重的负载等。虽然现代机器人控制技术有了长足的发展，还远达不到人的智力水平，包括决策能力和对环境的感知能力。与此同时，人类所具有的智能是任何生物和机械装置所无法比拟的，人所能完成的任务不受人的智能的约束，而仅受人的体能的限制。因此，将人的智能与机器人所具有的强大的机械能量结合起来，综合为一个系统，将会带来前所未有的变化，这便是外骨骼机器人的设计思想。外骨骼机器人实质上是一种可穿戴机器人，穿戴在操作者的身体外部，为操作者提供了诸如保护、身体支撑等功能，同时又融合了传感、控制、驱动、信息融合等机器人技术，使得外骨骼能够在操作者的控制下完成一定的功能和任务。本文通过介绍外骨骼机器人的发展历史及研究现状进一步分析了外骨骼机器人的关键技术，并对其技术难点以及发展前景作了说明，以期在全面认识外骨骼机器人基础上对其开展进一步深入研究。

发展中的外骨骼机器人及其关键技术

２０１８年１１月 第４６卷第２１期 机床与液压 ＭＡＣＨＩＮＥＴＯＯＬ＆ＨＹＤＲＡＵＬＩＣＳ Ｎｏｖ ２０１８ Ｖｏｌ ４６Ｎｏ ２１ ＤＯＩ：１０．３９６９／ｊ ｉｓｓｎ １００１－３８８１ ２０１８ ２１ ０１５ 收稿日期：２０１７－０６－２０ 作者简介：石晓博（１９９１ ），男，硕士研究生，主要研究方向为下肢外骨骼康复机器人步态规划研究三Ｅ－ｍａｉｌ：５４７３６３９９２＠ ｑｑ ｃｏｍ三 通信作者：郭士杰，Ｅ－ｍａｉｌ：３０８６８１９８２＠ｑｑ ｃｏｍ三 发展中的外骨骼机器人及其关键技术 石晓博，郭士杰，李军强，赵海文 （河北工业大学机械工程学院，天津３００１３０） 摘要：外骨骼助力机器人是一种可穿戴的机械装置，应用人机工程学二仿生学等相关知识将人的智力和机器人的体力完美地结合在了一起，拥有巨大的发展潜力三为了更好地了解外骨骼助力机器人的发展成果及现阶段存在的问题，现将其发展分为蒸汽时代二电气时代二信息时代三大部分进行介绍，并从机械结构技术二驱动技术二控制技术二人机交互技术以及安全性技术等外骨骼助力机器人关键技术入手，找出现阶段面临的问题，并指明未来的发展方向三 关键词：外骨骼；关键技术；助力机器人；科技时代 中图分类号：ＴＰ２４一一文献标志码：Ａ一一文章编号：１００１－３８８１（２０１８）２１－０７０－７ ＤｅｖｅｌｏｐｉｎｇＥｘｏｓｋｅｌｅｔｏｎＲｏｂｏｔｓａｎｄＫｅｙＴｅｃｈｎｏｌｏｇｉｅｓ ＳＨＩＸｉａｏｂｏ，ＧＵＯＳｈｉｊｉｅ，ＬＩＪｕｎｑｉａｎｇ，ＺＨＡＯＨａｉｗｅｎ （ＣｏｌｌｅｇｅｏｆＭｅｃｈａｎｉｃａｌＥｎｇｉｎｅｅｒｉｎｇ，ＨｅｂｅｉＵｎｉｖｅｒｓｉｔｙｏｆＴｅｃｈｎｏｌｏｇｙ，Ｔｉａｎｊｉｎ３００１３０，Ｃｈｉｎａ） Ａｂｓｔｒａｃｔ：Ｅｘｏｓｋｅｌｅｔｏｎｐｏｗｅｒｍｅｃｈａｎｉｓｍｉｓａｋｉｎｄｏｆｗｅａｒａｂｌｅａｓｓｉｓｔｅｄｒｏｂｏｔｓ，ａｐｐｌｉｅｄｅｒｇｏｎｏｍｉｃｓ，ｂｉｏｎｉｃｓａｎｄｏｔｈｅｒｒｅｌａｔｅｄ ｋｎｏｗｌｅｄｇｅｔｏｐｅｒｓｏｎ ｓｉｎｔｅｌｌｉｇｅｎｃｅａｎｄｒｏｂｏｔｐｈｙｓｉｃａｌｐｅｒｆｅｃｔｉｏｎｔｏｇｅｔｈｅｒ，ｈａｓｈｕｇｅｄｅｖｅｌｏｐｍｅｎｔｐｏｔｅｎｔｉａｌ．Ｉｎｏｒｄｅｒｔｏｂｅｔｔｅｒｕｎｄｅｒｓｔａｎｄｔｈｅｅｘｏｓｋｅｌｅｔｏｎａｓｓｉｓｔｅｄｒｏｂｏｔｄｅｖｅｌｏｐｍｅｎｔａｃｈｉｅｖｅｍｅｎｔｓａｎｄｅｘｉｓｔｉｎｇｐｒｏｂｌｅｍｓａｔｐｒｅｓｅｎｔｓｔａｇｅ，ｉｔｓｄｅｖｅｌｏｐｍｅｎｔｗａｓｄｉｖｉｄｅｄｉｎｔｏｓｔｅａｍ ａｇｅ，ｔｈｅａｇｅｏｆｅｌｅｃｔｒｉｃｉｔｙ，ａｎｄｔｈｅｉｎｆｏｒｍａｔｉｏｎａｇｅｏｆｔｈｒｅｅｍａｉｎｐａｒｔｓ，ａｎｄｉｎｔｒｏｄｕｃｅｄ．Ａｎｄｓｔａｒｔｅｄｆｒｏｍｔｈｅｍｅｃｈａｎｉｃａｌｓｔｒｕｃｔｕｒｅ， ｄｒｉｖｅｔｅｃｈｎｏｌｏｇｙ，ｃｏｎｔｒｏｌｔｅｃｈｎｏｌｏｇｙ，ｔｈｅｈｕｍａｎ?ｃｏｍｐｕｔｅｒｉｎｔｅｒａｃｔｉｏｎｔｅｃｈｎｏｌｏｇｙ，ａｎｄｓｅｃｕｒｉｔｙｔｅｃｈｎｏｌｏｇｙ，ａｓｅｘｏｓｋｅｌｅｔｏｎｓｐｏｗｅｒｋｅｙｔｅｃｈｎｏｌｏｇｉｅｓｏｆｔｈｅａｓｓｉｓｔｅｄｒｏｂｏｔ，ｔｈｅｐｒｅｓｅｎｔｐｒｏｂｌｅｍｓｃｏｎｆｒｏｎｔｅｄａｒｅｆｏｕｎｄ，ａｎｄｐｏｉｎｔｅｄｏｕｔｔｈｅｆｕｔｕｒｅｄｅｖｅｌｏｐｍｅｎｔｄｉｒｅｃｔｉｏｎ． Ｋｅｙｗｏｒｄｓ：Ｅｘｏｓｋｅｌｅｔｏｎ；Ｋｅｙｔｅｃｈｎｏｌｏｇｙ；Ａｓｓｉｓｔｅｄｒｏｂｏｔ；Ｅｒａｏｆｓｃｉｅｎｃｅａｎｄｔｅｃｈｎｏｌｏｇｙ ０一前言 外骨骼（Ｅｘｏｓｋｅｌｅｔｏｎ）这一名词来源于生物学中昆虫和壳类动物的坚硬外壳，其作用在于支撑二运动二防护三项功能紧密结合［１］三与此对应，外骨骼助力机器人是模仿生物界外骨骼而提出的一种新型机电一体化装置 ［２］ ，结合机械结构二控制二驱动方式二人 机交互等关键技术，在为穿戴者提供诸如保护二协同动作等功能的基础上，还能够在穿戴者的控制下完成人类自身无法完成的任务三 文中将外骨骼助力机器人的发展分为３个阶段，即蒸汽时代二电气时代二信息时代三通过介绍每个时代外骨骼主力机器人的发展情况，从而指出现阶段存在的问题，然后从外骨骼助力机器人相关关键技术入手，从根本上分析出现问题的原因，并寻求高效的解决方案三 １一外骨骼助力机器人的发展 外骨骼助力机器人从出现到发展至今，大概分为 ３个阶段，即蒸汽时代二电气时代二信息时代三 １ １一蒸汽时代 １９世纪中后期，人类完成了第一次技术革命， 开启了以蒸汽机代替人力的时代三人类萌生了用蒸汽机驱动人体运动的想法，但由于蒸汽机存在体积过大二容易烫伤等缺点，同时受材料匮乏二工艺落后的 制约，使这一时期的外骨骼仅仅停留在概念设计上三如１８３０年英国著名插画师ＲｏｂｅｒｔＳＥＹＭＯＵＲ所绘的‘ＷａｌｋｉｎｇＢｙＳｔｅａｍ“中提到的穿戴在人体上的蒸汽机行走机，如图１所示三这一阶段提出的外骨骼由于技术发展的限制没有实际应用的价值，但还是为后来的外骨骼设计拓宽了思路三

外骨骼机器人研究综述

外骨骼机器人研究综述 摘要 外骨骼机器人(Exoskeleton Robot)实质上是一种可穿戴机器人，即穿戴在操作者身体外部的一种机械机构，同时又融合了传感、控制、信息耦合、移动计算等机器人技术,在为操作者提供了诸如保护、身体支撑等功能的基础上，还能够在操作者的控制下完成一定的功能和任务。本文简要介绍外骨骼机器人的研究现状以及发展趋势。 需求分析 随着社会的发展，老龄化加重，已超过人口总数的10%。老年人普遍存在体力不支，行动不便，力量、耐力不足等情况，研发一种可穿戴舒适的外骨骼机器人，助老年人行走、上下楼梯、适当负重等十分必要，同时，可穿戴式外骨骼机器人也适用于残疾人或身体机能薄弱者，这将会大大减少照顾老弱病残者的人力资源，减轻社会与家庭的压力，具有社会与经济价值。 传统的交通工具是远行与负重的主要方式，但存在对路面要求高，不适应于军事、消防营救等领域，士兵与消防人员需长距离行走、背负重物、野外作业等，这些特殊活动交通工具都没法完成，且对运动者的身体素质要求非常高。研制一种可穿戴外骨骼机构，可以提供充足的能量和耐力来增强长时间行走和负重等能力，从而完成一些特殊任务。 可穿戴式外骨骼机器人由于自身的商用与军事应用价值，已经成为近年来国内外学者的一个重点研究方向。理想外骨骼机器人有能够在操作者需要的时候及时提供帮助但永远不妨碍其行动的自动化机器人装置替代他的手足，能承受货物背负任务且与人体完全结合，准确预判佩戴者的意图，具有防护并增强操作者负重和运动能力的作用。理想外骨骼机器人的研制困难可想而知。 研究现状 早期人类为减少人员伤亡所制作的盔甲其实已经属于外骨骼的雏形，提高了士兵的个人防护能力，但其存在自重与被动阻力，极大消耗了使用者的体力。 1960年，通用电气公司研制一种名为“哈曼迪1”的可佩戴单兵装备，采用液压驱动。该公司第一个提出并开展增强人体机能的主动助力型外骨骼机器研究。其外骨骼体积巨大且笨重，安全性能低，也只能取代单只手功能。 1978年，麻省理工学院研究了“增强人体机能的外骨骼”，负重问题有所改善，其驱动能源与便携式问题尚未解决，没有完整的成果。 1991年，日本神纳川理工学院开发了一套独立的可穿助力外套（如图1所示），使用肌肉压力传感器，分析佩戴者的运动情况，通过微型气泵、便携式镍镉电池及嵌入式微处理器，提供足够的助力。该开发产品是专为护士研制，可使人的力量增加0.5~1倍。

外骨骼机器人

This article was downloaded by: [Shanghai University] On: 02 November 2013, At: 23:45 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Advanced Robotics Publication details, including instructions for authors and subscription information: https://www.doczj.com/doc/cd7229777.html,/loi/tadr20 Exoskeletal meal assistance system (EMAS II) for patients with progressive muscular disease Yasuhisa Hasegawa a, Saori Oura a & Junji T akahashi a a Graduate School of Systems and Information Engineering, University of T sukuba 1-1-1 T ennodai, 305-8573, T sukuba, Japan. Published online: 09 Oct 2013. PLEASE SCROLL DOWN FOR ARTICLE

气动技术及外骨骼机器人浅析

气动技术与外骨骼机器人 机械电子工程吴 一、外骨骼的介绍 1.1 电影中的外骨骼 在科幻小说，以及很多的科幻题材的影视剧中，我们经常能够看到这样一种特殊的机甲：它能够穿戴在人体外表，具备辅助动力，借以提高人类的战斗力。这样的装备即被称作可穿戴机器人。 《阿凡达》中的机器人《钢铁侠》中的可穿戴式机器人 1.2 外骨骼简介 外骨骼的概念：外骨骼技术实质上可以理解为是一种可穿戴式机器人技术，为操作者提供了诸如保护，身体支撑、运动辅助等功能。 技术：传感、控制、信息、融合、移动计算。 应用：将人类的智力和机器人的“体力”结合在一起，使得外骨骼能够在操作者参与的控制模式下完成仅靠操作者或者外骨骼自身能力无法单独完成的务任。 特点：

（1）、与通常的智能系统相比，柔性外骨骼和操作者组成的人一外骨骼系统并非简单地给系统添加人工智能或者决策能力，而是借鉴人机智能系统理论，有效地将人和机器在感知、决策以及执行等多个层次上进行有机地结合， （2）、充分发挥人的智能在整个任务操作过程中的作用以及机器的执行能力。 人机智能外骨骼系统的基本控制框图 控制系统中操作者，就是人本身，也成为控制系统中的一个组成部分，即“人在回路中(Man in Loop)”。这样，将人与机械的合理结合，相比自主控制的机器人，既能够保证更强的整体性能，又极降低了技术门槛。

1.3外骨骼的应用 1、军事领域： 士兵佩戴可穿戴机器人后，将成为一名超级士兵，拥有无 穷的力量，可携载更多的武器装备，火力威力增强，防护水平 提高，同时可克服任何障碍，高速前进，不会产生疲劳感。无 论是前线作战的士兵，还是负责后勤的工兵，都能够保持高强 度、长时间的作战，同时也降低了后勤运输的压力。这样，在 不增加军队人数的情况下，可将部队战斗力翻倍，甚至更高。对 一支军队的整体作战能力而言，将是一个极大的提升。 美国五角大楼早在20世纪70年代，就经研究认为，未来士兵应当全面实现机械化和自动机器人化，并责成国防高级研究计划局负责，拨款5000万美元从事这一领域可穿戴机器人项目的研究。