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Overview of some Command Modes for Human-Robot Interaction Systems

Abstract

Interaction and command modes as well as their combination are essential features of modern and futuristic robotic systems interacting with human beings in various dynamical environments. This paper presents a synthetic overview concerning the most command modes used in Human-Robot Interaction Systems (HRIS). It includes the first historical command modes which are namely tele-manipulation, off-line robot programming, and traditional elementary teaching by demonstration. It then introduces the most recent command modes which have been fostered later on by the use of artificial intelligence techniques implemented on more powerful computers. In this context, we will consider specifically the following modes: interactive programming based on the graphical-user-interfaces, voice-based, pointing-on-image-based, gesture-based, and finally brain-based commands.

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Overview of some Command Modes for Human-Robot Interaction Systems

Author: Zaatri, Abdelouahab
Publisher: IADITI Editions
Year: 2022
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Copy igh © 2022 by Au ho /s and Licensed by IADITI. This is an open access a icle dis ibu ed unde he C ea i e Commons A ibu ion License which pe mi s un es ic ed use,
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Jou nal o In o ma ion Sys ems Enginee ing and Managemen
2022, 7(2), 14039
e-ISSN:
2468-4376
h ps://www.jisem-jou nal.com/
Li e a u e Re iew
O e iew o some Command Modes o
Human-Robo In e ac ion Sys ems
Abdelouahab Zaa i1*
1 Uni e si y o Cons an ine-B o he s Men ou i- Cons an ine, Alge ia
*
Co esponding Au ho :
azaa [email protected]
Ci a ion: Abdelouahab Zaa i (2022). O e iew o some Command Modes o Human-Robo In e ac ion Sys ems. Jou nal o In o ma ion Sys ems
Enginee ing
and Managemen , 7
(2),
14039
.
h ps://doi.o g/10.55267/iad .07.12011
ARTICLE INFO
ABSTRACT
Recei ed: 06 Dec. 2021
Accep ed: 18 Feb. 2022
In e ac ion and command modes as well as hei combina ion a e essen ial ea u es o mode n and u u is ic
obo ic sys ems in e ac ing wi h human beings in a ious dynamical en i onmen s. This pape p esen s a
syn he ic o e iew conce ning he mos command modes used in Human-
Robo In e ac ion Sys ems (HRIS). I
includes he i s his o ical command modes which a e namely ele-manipula ion, o -
line obo p og amming,
and adi ional elemen a y eaching by demons a ion. I hen in oduces he mo
s ecen command modes which
ha e been os e ed la e on by he use o a i icial in elligence echniques implemen ed on mo e powe ul
compu e s. In his con ex , we will conside speci ically he ollowing modes: in e ac i e p og amming based on
he g aphical-use -in e aces, oice-based, poin ing-on-image-based, ges u e-based, and inally b ain-
based
commands.
Keywo ds: human- obo in e ac ion, eleope a ion, speech-based commands, image-based commands, ges u e-
based command, b ain-compu e in e ace.
INTRODUCTION
In a mode n echnological sense, he i s obo s which
appea ed du ing he second wo ld wa we e se ial a m
manipula o s. They we e mainly dedica ed o elemanipula e
objec s in haza dous en i onmen s such as nuclea plan s and
o pe o m simple epe i i e indus ial asks. Du ing his
his o ical pe iod, he adi ional modes o command and
con ol we e elemanipula ion, o -line obo p og amming,
lead- h ough and each pendan (Low, 2006; Wallén, 2008).
La e on, since he se en ies, wi h he p og essi e
imp o emen o compu e pe o mances, se ial obo ha e
p o en o be e y e icien o a ious indus ial asks.
Mo eo e , since he eigh ies, pa allel obo s joined he domain
o indus y adding p incipally mo e p ecision and speed
compa ed o se ial obo s (Cecca elli, 2001; Gaspa e o and
Scale a, 2019).
Nex , since he nine ies, new shapes o obo ic sys ems
appea ed and con inuously e ol ed in s uc u es,
unc ionali ies and pe o mances (Zamalloa e al., 2017).
Di e en obo shapes a e expe ienced such as mobile obo s,
cable-based obo s, lexible obo s like snakes, a ious o he
animals-like obo s, d ones, and e en humanoid obo s
(Ramos, 2018). I is a ac ha mode n obo s a e becoming
popula and p o ed o be capable o achie ing ela i ely
complex asks in a ious en i onmen s including unknown,
haza dous and/o emo e a eas. Some examples o such sys ems
a e space explo a ion obo s as o e s, assis i e obo s o elde ly
and disabled people, su ge y obo s, e c. Humanoid obo s a e
pa icula ly ema kable because o hei esemblance o human
beings. They a e going o be used in social en i onmen s wi h he
capabili y o in e ac di ec ly wi h human beings. They will be
also used o escue ope a ions, du ing wa s as soldie s, e c
(Fo d, 2015).
In he cou se o his ex ensi e e olu ion o mode n obo ic
sys ems, adap i e and sma Human Robo In e ac ion (HRI)
ises una oidably o be essen ial o ensu ing he success o
pe o ming complex asks and missions. As a consequence, HRI
has eme ged and s ands mo e and mo e as a opic o a
pa amoun impo ance. In he same con ex , command modes
play a undamen al ole in any dedica ed amewo k o human-
obo in e ac ion as hey a e subs an ial ea u es by which
communica ion, in e ac ion, coope a ion and expec ed mu ual
unde s anding be ween humans and obo s become possible. In
ac , his opic is an essen ial key o success ul de elopmen o
mode n and u u is ic HRIS (She idan, 2016) and jus i ies he
in e es o p esen his o e iew abou he mos used command
modes o HRIS.
This pape b ie ly p esen s some o he mos ele an HRI
echniques ha a e used o gene a e obo commands. I includes
elemanipula ion ha e ol ed owa ds ele obo ics, o -line
obo p og amming, in e ac i e-based command, oice-based
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Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
command, ges u e-based command, poin ing on image-based command, and b ain-based in e ac ion and command.
TRADITIONAL MODES OF HRI
The e a e ac ually di e en echniques h ough which a
human can in e ac wi h and command obo s. Howe e , a he
beginning o he eme gence o obo ics, he e we e ew
elemen a y in e ac ion and command modes.
Teleope a ion
Teleope a ion cons i u es he i s mode o in e ac ion
and command ha has been employed in eleope a ing
obo ic sys ems. I s a ed a ound he 1945 wi h he i s
mas e -sla e manipula o designed o manipula e
adioac i e ma e ial in ho cells (She idan, 1992).
Teleope a ion is a manual con ol pe o med by an ope a o
who is usually si ua ed in a local si e con olling emo ely a
obo which is si ua ed in i s wo kspace en i onmen . The
mos common con igu a ion o eleope a ion is ha o he
mas e -sla e whe e he human ope a o (mas e ) di ec ly
con ols he emo e obo (sla e) by means o a hand
con olle . T adi ionally, he ask moni o ing was assu ed by
di ec ision i possible and by came as. Figu e 1 illus a es
he gene al o ganiza ion o a eleope a ion sys em p esen ed
in (She idan, 1992). On he le side, one can dis inguish he
human ope a o (mas e ) who is eleope a ing and
supe ising he ask. On he igh side, one can dis inguish
he subo dina e (sla e) which is execu ing he ecei ed
commands.
Howe e , his mode con inuously in ol ed he
ope a o ’s a en ion in a di ec coupling. I , hus, gene a ed
a igue and a bo ing eeling du ing epe i i e asks, leading
o cogni i e a igue o he ope a o . Besides ha , o he
d awbacks can a ec eleope a ion such as he weakness o
senso y eedback, he limi ed communica ion bandwid h, he
ope a o 's subjec i e expe ience and p esen wo k
condi ions. The e is also one issue ha e y se iously a ec s
and educes he pe o mance o eleope a ion and which is
ha d o add ess. I is he con ol ins abili y ha is caused by
ime delays o he eedback signal be ween he ope a o and
he elemanipula ed obo (Lichia dopol, 2007; She idan,
1992; Zaa i, 2000).
Thus, o o e come hese p oblems, i was necessa y o
inco po a e a ce ain deg ee o au onomy in o he sys em in
o de o elie he ope a o . So, wi h he con inuously
inc easing powe p ocessing o compu e s and IA, he
de elopmen o adi ional eleope a ion leaded o
ele obo ics and o supe iso y con ol sys ems. These las
echniques we e de eloped since he se en ies and we e
en iched wi h mo e HRI echniques, sma , adap i e and
mul imodal use in e aces (Oussalah and Zaa i, 2003; Zaa i
and Van B ussel, 1997). The mos common echniques which
ha e been used la e on o elie eleope a ion we e:
elep esence, elep og amming, semi-au onomous con ol,
in elligen assis ance o suppo ope a o s and augmen ed
eali y (Lichia dopol, 2007; Makha ae a and Va ol, 2020; W.
S. Kim e al., 1992).
O -line P og amming Mode
Con a ily o elemanipula ion echniques whe e he
human ope a o is ully engaged in he in e ac ion wi h he
obo ; o o -line p og amming echniques, he ask execu ion
is ully managed by an au oma ic con olle so ha he ope a o
is le almos in an obse e ole. The o -line obo
p og amming echnique is simila o compu e p og amming
languages which a e usually used o simula ion. I consis s o
w i ing a ex ual p og am (code) ha con ains he
speci ica ions o ask execu ion. The p og am is a so wa e
which is w i en independen ly o he obo cell (o -line). To
execu e he ask by he obo , he ope a o in e ac s wi h a
compu e om whe e he uploads he p og am and launches i s
execu ion. Once he p og am s a s, he compu e manages
au oma ically he ask by means o he obo con olle
acco ding o he p og am ins uc ions. In he beginning phase
o obo ics, he ope a o is le ou o he ask ope a ions unable
o in e ene. Ne e heless, while supe ising he ask
execu ion, he/she can only in e ene i necessa y by means o
an eme gency bu on o s op he ask execu ion by disabling he
powe supply.
Con a y o adi ional eleope a ion; ex ual
p og amming, while i is ully au oma ic, lacks lexibili y o
pe o ming complex asks which equi e some skills. I is no
p ac ical in uns uc u ed en i onmen s. Mo eo e , because o
he unce ain ies inhe en o modelling eal en i onmen s,
obo s and senso s. This mode is no applicable a all in
unknown and emo e en i onmen s. I is howe e well
adap ed o p og amming simple asks (Mi si e al., 2005; Pan
e al., 2012; Yong and Bonney, 1999).
O he echniques: eaching by demons a ing
Beside eleope a ion and o -line p og amming, he e a e
wo o he adi ional me hods ha we e used o acili a e he
p og amming o obo s o pe o ming some simple epe i i e
bu ela i ely complex manipula ion asks. They a e based on
eaching by demons a ion, and hey a e namely he lead
h ough me hod and each pendan me hod.
"Lead h ough me hod:" is a me hod ha is also e e ed o
as hand guidance p og amming me hod. I is an in ui i e
me hod ha in ol es he human ope a o o demons a e he
ask by pe o ming i manually by guiding he obo end-
e ec o . Du ing he demons a ion phase, he ope a o mo es
by means o his own hands he obo 's he end-e ec o and
guides he obo while pe o ming he ask. The obo
con olle s o es he ajec o y p o ided du ing he
demons a ion. This enables he obo o play back
au oma ically he demons a ed ask du ing he p oduc ion
cycle. The walk h ough me hod was usually app op ia e o
some ype o asks such as sp ay pain ing and a c welding
(A gall e al., 2009; Eakins e al., 2013; Qi and Zhang, 2009).
"Teach pendan me hod:" like he lead- h ough me hod,
each pendan me hod consis s o eaching he obo how o
pe o m he gi en ask, bu by means o a each pendan which
is used as an in e ace ool ha se es o guide he obo . The
each pendan is a hand-held de ice ha is used o con ol he
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Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
obo wi hou con ac and emo ely. I is p o ided in he o m
o a po able de ice like a able wi h bu ons, swi ches and
dials co esponding o speci ic unc ions designed o
con olling he obo .
Du ing he eaching o lea ning phase, he ope a o holds
and uses he each pendan o d i e he obo s ep by s ep o
any desi ed loca ions which a e equi ed o pe o ming he
ask. The ea e , he ele an poses a e s o ed, and inally,
du ing he p oduc ion cycle, he obo epea s au onomously
he mo emen s and ac ions ha lead o pe o m he ask a
speci ied speed. (Fukui e al., 2009; Joseph, 1998).
The lead h ough and each pendan me hods in ol e he
human ope a o in he ask, bu only du ing he eaching
phase which is pe o med ou o he p oduc ion cycle. A e
lea ning he p ocesses, he obo ac ions a e con e ed in o
ex ual p og ams which a e used he ea e o au oma ically
pe o m he ask (A gall e al., 2009).
INTERACTIVE COMMANDS BASED ON
GUI
I we conside he p e iously p esen ed adi ional
in e ac ion modes, we no ice ha he e was a need o ee he
ope a o om his con inuous engagemen du ing ull
eleope a ion and in e sely o gi e him he possibili y o
in e ene when needed du ing he ull au oma ic ask
execu ion o he p og amming mode. To his end, he
in e ac i e con ol mode, which has eme ged a ound 1995, has
p o ided an al e na i e o he use o in e ene du ing ask
execu ion and e en o swi ch om one command mode o
ano he . I was os e ed by he appa i ion o so wa e
in e acing acili ies. I has been made possible conjoin ly wi h
he de elopmen o he objec -o ien ed p og amming
echniques and hei co esponding languages such as C++, Ja a,
Py hon, e c. Basically, in e ac i e p og amming enables o buil
up G aphical Use In e aces (GUI) on compu e sc eens ha
con ain g aphical objec s like windows, panels, bu ons, slide s,
pop-up menus, e c. Each g aphical objec can be linked o a
unc ion ha can be execu ed each ime he use ac i a es he
co esponding objec om he GUI. The gene a ion o unc ions
can be done by mouse clicks on pa icula widge s, by yping
speci ic cha ac e keys o he compu e keyboa d o by sc een
ouch (Figu e 2). The GUI enables also he p esen a ion o da a
in di e en o ma s and s uc u es ( ex s, images, ideos)
(Appels al e al., 2018; Mye s, 1995).
F om he HRI poin o iew, he in oduc ion o in e ac i e
p og amming echniques was welcomed as i gi es he
possibili y o gene a e in e ac i ely commands ia GUI while he
obo is e en pe o ming ope a ions wi hou necessa ily
s opping i . I enables also he e lec ion o eedback in o ma ion
ia he GUI.
As shown in Figu e 2, many needed unc ions can be
p og ammed and launched ia he GUI. Posi ion commands,
join commands, eloci y commands, o ce commands, ei he
cons ained o no can be gene a ed in e ac i ely. Wi hin his
in e ac i e mode, he ope a o can ca y ou pick-and-place asks
wi h obo manipula o s o di ec a mobile obo o some
des ina ion. Fo ins ance, o achie e asks wi h his mode, he
ope a o di ec s he obo by a se ies o clicks on he app op ia e
bu ons.
In addi ion, his mode enabled o combine pu e eleope a ion
wi h pu e ex ual p og amming, p o iding a way o o e coming
hei inhe en limi a ions. These modes o eleope a ion, o -line
p og amming and in e ac i e p og amming can be combined
and sha ed o pe o m asks mo e e icien ly. This in e ac i e
mode has opened many ways o HRI and coope a ion (Ma ion
e al., 2017; Zaa i, 2000; Zendoui e al., 2018)
Figu e 1. Teleope a ion sys em
Figu e 2. In e ac i e commands
Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
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MODERN COMMAND MODES
Mode n command modes make he e olu ion o he ask
easie and mo e e icien . Ye , hey equi e mo e complex
sys ems o be implemen ed o hey need senso s, ela i ely
as compu e s and AI echniques. They need algo i hms ha
p ocess da a, ex ac ele an ea u es and impo an
in o ma ion as humans do. In he ollowing sec ions, we
p esen speech-based command, poin ing on image-based
command, ges u e-based command, and b ain-based
command.
Speech-Based Commands
I is well known ha speech is he mos na u al way o
communica e be ween humans o he wise alking o obo s a
he ea lie age o obo ics was like a d eam. Howe e , la e
on wi h he de elopmen o AI, human speech appea s o be
an in e es ing mean o command, con ol and communica e
wi h obo s.
S ill, using human speech o command obo s equi es
speech ecogni ion echniques, which s a ed in he ea ly
1950s. O cou se, ea ly sys ems had limi ed ocabula y, bu
mode n speech ecogni ion sys ems ha e e ol ed and a e
now widely a ailable in many domains. They ha e gained
use wi h in elligen assis an s, such as Amazon's Alexa,
Apple's Si i and Mic oso 's Co ana, Google’s Google
Assis an and o he s (Te zopoulos and Sa a zemi, 2020).
These sys ems a e enabling speech in e ac ion wi h
compu e s and o he de ices. They ha e capabili ies o
in e p e wha is said h ough speech ecogni ion sys ems
and e en may espond o ques ions o commands ac oss ex -
o-speech sys ems.
In pa icula , au oma ic speech unde s anding o
gene a ing obo commands is linked o he ield o
Au oma ic Speech Recogni ion (ASR). ASR is in ended o
con e human speech in o w i en ex s. Mos Speech-based
commands and in e ac ion be ween humans and obo s ha e
been de eloped wi h he ecogni ion o isola ed wo ds
because i is easie o be used as obo commands. Examples
o sen ences ha a e used by speech sys ems o command
obo s a e: go o ini ial posi ion, ind able, mo e le , e c.
Howe e , because o he complex na u e o oice signals, ASR
s ill emains in some ci cums ances a ela i ely ha d issue o
obo s o unde s and speech commands.
The p inciple o speech commands
The p inciple used o mos wo d ecogni ion sys ems can
be illus a ed in Figu e 3 and Figu e 4. I comp ises wo phases:
he lea ning phase and he ecogni ion phase. The lea ning
phase consis s o c ea ing a lis o wo ds which a e s o ed in o
a dic iona y as e e ence wo ds. The ecogni ion phase consis s
o iden i ying any new spoken wo d o one o he e e ence
wo ds s o ed in he dic iona y.
An example o ASR we ha e implemen ed was based on
he ollowing p ocedu e: any spoken wo d which is a
con inuous acous ic signal is ansla ed by he mic ophone in o
an elec ic con inuous signal. This con inuous elec ical signal
is hen sampled by a sound ca d. Some digi al ope a ions a e
hen applied such as p e-emphasis, Fas Fou ie T ans o m
(FFT), powe spec um, il e bank in eg a ion (Mel's Fil e ),
loga i hmic comp ession, Disc ee Fou ie T ans o m. The inal
ou pu is a se o coe icien s which a e called Mel F equency
Ceps al Coe icien s (MFCC) (Muda e al., 2000). MFCC a e he
main ea u es ha cha ac e ize a speech signal. They se e o
build he dic iona y o he obo commands ( e e ences) a e a
aining phase o he use . They se e also in he ecogni ion
phase o iden i y any new unknown obo command by
compa ing i o hose s o ed in he dic iona y.
In o de o ecognize any spoken wo ds conside ed as
possible obo commands, ASR is using a ious me hods o
classi ica ion such as Hidden Ma ko Model (Rabine , 1989),
VQ ec o quan i ica ion (Linde e al., 1980), and lea ning
echniques as Neu al Ne wo ks (Paul and Pa ekh, 2011).
Howe e , he Mul iLaye Pe cep on (MLP) is o special
impo ance o acous ic modeling in ASR (Pin o, 2010). As an
example in one o ou implemen a ion, he ole o he classi ie
is played by he MLP (Zaa i e al., 2015). I selec s he closes
e e ence wo d wi h espec o he spoken one. The scheme o
an ASR is ep esen ed in Figu e 4.
Figu e 3. Lea ning phase
Figu e 4. Recogni ion phase
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Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
Howe e , speech-based command is in e es ing o
handicapped people using o ins ance wheelchai s id he
ope a o ’s hands canno be used o i hey a e busy wi h some
o he asks. Wi h he ecen de elopmen o pe sonal and
humanoid obo s, his mode is also gaining mo e in e es .
Ne e heless, ARS applied o obo ic domain s ill su e s
om many ba ie s. I is sensi i e o ha d noisy
en i onmen s. The esul s depend on he pe sonal
cha ac e is ic o he ope a o ha can only be imp o ed by a
long aining. E icien success can be ob ained wi h limi ed
ocabula y and canno ma ch all and new con ex s
(Oussalah and Zaa i, 2003; Zaa i e al., 2015).
Commands by Poin ing on Images (Look- hen-Mo e)
The use o ision o command and con ol obo s is a e y
impo an elemen o enhancing obo applica ions. Today,
many comme cial obo ics in eg a ing ision sys ems a e
a ailable. Bu because o he sensi i i y and complexi y o
image p ocessing, he e iciency o such sys ems is mainly
limi ed o s a ic indus ial applica ions. Fo ele obo ics,
ision-based con ol echniques, as s essed in (She idan,
1992), make a powe ul se o ools o obo in e ac ion and
con ol especially in uns uc u ed and unknown
en i onmen s. These echniques do no equi e p e-
knowledge o models abou he objec s o wo k wi h. Wi h
hese echniques, he human ope a o designa es he objec s
o loca ions o in e es om he ecei ed images; a e wa ds
he sys em ex ac s hei co esponding ea u es and heads
owa ds hem in eal space. In all hese echniques, he
supe iso ’s ole, as obse ed in (She idan, 1992) “is limi ed
o concep ion and poin ing, and he ele- obo do he es ”.
In gene al, ision-based obo command sys ems can be
di ided in wo main olds ega ding he applied con ol
sys em a chi ec u e. The ea lie echnique is named look-
and-mo e and he o he one is isual se oing.
Image-Based as Look- hen-Mo e Commands
Because eal- ime image p ocessing was ela i ely slow,
he ea lie ision-based sys ems we e p incipally designed
o applica ions o ype "look- hen-mo e" which a e usually
dedica ed o s a ic en i onmen s. They we e also e e ed
some imes as poin -and-click o image-based commands
(Kim and S a k, 1989; Oussalah and Zaa i, 2003). F om he
con ol sys em iewpoin , hei con ol a chi ec u e is an
open loop one wi hou con inuous image p ocessing
eedback.
These sys ems include s e eo ision sys ems o cap u e
images. They wo k as ollows (Figu e 5). A scene is selec ed
by he ope a o which inside which he objec o in e es
appea s in bo h s e eo ision came as. The ope a o selec s
his objec in one image by poin ing on i wi h a poin ing
de ice such as a mouse click. The s e eo ision sys em g abs
au oma ically he le and igh images. Then a s e eo ision
algo i hm p oceeds hese images in o de o ex ac he
co esponding 3D coo dina es o he selec ed objec o
in e es in he eal wo d. Once, hese 3D coo dina es a e
es ima ed, hey a e sen as a posi ion command o he obo
o heading owa ds his loca ion o his objec . In ac , he
obo execu es his command by pe o ming “blind”
mo emen s which assumes ha he en i onmen emains
s a ic a e he obo has s a ed o mo e. I is an open-loop
app oach o a ype i e and o ge (Wang, 2016) . By epea ing
his p ocess, he ope a o can di ec easily he obo o pe o m
manipula ion asks and/o na iga ion.
Howe e , while his echnique is simple, i enables high
le el commands. I ep esen s an e icien way o gene a e
look- hen-mo e obo commands o s a ic en i onmen s.
A success ul implemen a ion o an au oma ic image-based
(look- hen-mo e) commands named click-and-mo e, has been
de eloped o six DOF manipula o s. I has been desc ibed in
(Oussalah and Zaa i, 2003; Zaa i and Van B ussel, 1997). I has
also been ex ended o mobile manipula o s (Zaa i, 2000) and
o pa allel cable-based obo s (Bouchemal and Zaa i, 2014). All
ou expe imen s ha e p o en ha i is a e y powe ul
echnique o a ious ypes o obo s in he ange whe e
calib a ion o he came as has been pe o med.
Visual Se oing Con ol
Wi h he inc easing powe o image p ocessing, i becomes
possible o apply machine ision o dynamic sys ems ac ing o
mo ing in a non-s a ic en i onmen and capable o acking
mo ing a ge s. This echnique, known as ision-based con ol
o isual se oing appea ed in 1979 (Co ke, 1994; Hans, 2018).
Visual se oing is dis inguished om look- hen-mo e since i
enables o con ol he obo 's mo ion using eal- ime eedback
based on ision senso s (Vah enkamp e al., 2008).
Ges u al-based Commands
Ges u e-based obo command is a echnique ha uses he
mo emen o some body pa s in o de o in e ac and
command obo s. Ges u es can be o any ype o body
mo emen s: head mo emen , hand ges u e, anybody
mo emen and e en acial exp essions. Also, ools mo ed by a
human ope a o such as pencils, lags, s icks, e c. can be used
o in e ac and command obo s.
As he many mode n modes o obo command, ges u e-
based command has been s udied, designed and implemen ed
by many au ho s. A su ey conce ning ges u e-based
in e ac ion is p esen ed in (Gal án-Ruiz e al., 2020; S. Mi a
and T. Acha ya, 2007). Technically, in mos applica ions,
ges u e-based in e ac ion equi es de ec ion and iden i ica ion
o ges u es as in ended obo commands. Ac ually, de ec ion
and iden i ica ion o ges u es a e mainly based on objec
ecogni ion and acking app oaches in ol ing CCD came a
senso s. As o isual se oing, se e al image p ocessing
me hods a e used o image ecogni ion such as ea u es-based,
appea ance-based, g adien -based, lea ning me hods, e c.
(Bake and Ma hews, 2004; Bonci e al., 2021; Lucas and
Kanade, 1981; Nea chou, 2011).
P inciple o Ges u e-Based commands
The p inciple o ges u e-based in e ac ion sys ems is
simple. I equi es senso s ha cap u e sequences o images
du ing he mo emen o a human body pa o o any ool
mo ed by he ope a o . These sequences o images a e hen
analyzed by an image p ocessing so wa e in o de o ack he
mo ion o some de ec ed elemen s o in e es . Once a signi ican

Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
6 / 11
mo emen is de ec ed and acked; he inal con igu a ion o
he ges u e is iden i ied. I is in e p e ed wi h espec o a
code ha links de ec ed mo emen s wi h co esponding
obo commands. This iden i ica ion o he ges u e is inally
sen as a co esponding obo command. Las ly, he obo
pe o ms he in ended ac ion o ask. Figu e 6 summa izes
he p inciple o ges u e-based obo command showing he
sequence o he designed and implemen ed main ope a ions
(Zaa i, 2021).
Applica ions o ges u e-based obo command a e
nume ous and can be adap ed and ex ended acco ding o
many needs and con ex s. Ges u e exp essions can be
employed in egions whe e he speech is useless. This can
happen, o ins ance, in noisy places, in unde wa e a eas,
and in emp y space whe e he medium canno con oy he
oice wa es as wi h as onau s (Liu e al., 2016). I can be also
used o lea ning by demons a ion and o imi a ion as
ep oducing ope a ions in medical ca e o ele-su ge y
(S aub e al., 2011). This command mode is also in e es ing in
some mili a y ac i i y o communica e and di ec emo e
eams, au onomous and unmanned sys ems (Ellio e al.,
2016). Mo eo e , i can be used in assis i e obo ics o
supe ising dea people, o su eillance o disabled people,
e c. (Bouchemal and Zaa i, 2013).
In addi ion, he ges u e-based in e ac ion can be designed
wi h con ac o wi hou con ac . Examples o ges u e
in e ac ion wi h con ac a e used o eaching on blackboa ds,
ables and o he suppo s. In hese si ua ions, ma ke s and
colou s can be employed o acili a e he acking o elemen s
o in e es (Bouchemal and Zaa i, 2013; Nea chou, 2011;
Sigalas e al., 2010). Mo eo e , wi h he e en o Co id-19
pandemic, ges u e-based con ol wi hou con ac is gaining a
special impo ance by a oiding ouch and con ac wi h
con amina ed people and objec s like doo handles,
machines, e c.
This command mode o e s he ad an age o eeing he
ope a o om he con ac wi h he compu e . Ne e heless,
some di icul ies which a e ela ed o image p ocessing and
en i onmen al issues can limi he capabili ies and
pe o mances o his command mode.
BRAIN-BASED INTERACTION AND
COMMANDS
Beside he a ie y o exis ing human-machine in e ac ion and
command echniques, hese las decades, biological ones ha e
opened new unp eceden ed pe spec i es owa ds e y
in e es ing and p omising inno a i e esea ches. Indeed, bio-
mechanical ac ions, myo-elec ic and bio-cybe ne ic echniques
can be used o in e ac ion, command and con ol o dynamical
sys ems such as obo s, wheelchai s, and e en pa alyzed body
pa s o human (Be na-Ma inez, 2011; Ma inek e al., 2021;
Rechy-Rami ez and Hu, 2015).
In his con ex , he mas e ing o he b ain ac i i y o human
beings o in e ac ing and commanding sys ems e eals o be a
e y a ac i e opic. Indeed, b ain ac i i y is he p ime sou ce
o gene a ing command signals. In he pas , unde s anding
mind hough s and de ec ing in en ions we e conside ed as a
kind o elepa hic capabili y which only exis s in science ic ion.
Howe e , wi h ecen ad ances in neu o-sensing echnologies,
his belie is inally u ning in o eali y (Nam e al., 2018). As a
esul , he ield o human- obo in e ac ion has been signi ican ly
en iched by he b ain-based in e ac ion and command
echniques. I is ac ually possible o a subjec , by means o B ain
Compu e In e aces (BCI), o de ec o gene a e commands ha
can be used o manipula e i ual o eal sys ems acco ding o
in en ions h ough he b ain ac i i y (Nicolas-Alonso and
Gomez-Gil, 2012).
Figu e 5. Look hen mo e commands
Figu e 6. Look hen mo e commands
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Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
P inciple o B ain-Compu e In e aces
C ow I is well es ablished ha human b ain ac i i y
consis s o emi ing wa es wi h ce ain pa e ns as a esul o
ex e nal s imuli o men al s a es (Buzsaki, 2006; Doelling and
Assaneo, 2021). BCIs a e speci ic de ices which a e capable
o cap u ing and measu ing b ain ac i i y, hen ex ac ing
in e es ing ea u es, and inally con e ing hese ea u es in o
ou pu s o in e ac wi h and command dynamic sys ems.
Thus, BCIs enable use s o in e ac wi h compu e s and o he
de ices by means o b ain ac i i y only (A onso e al., 2014;
A onso, 2013; Yonck, 2002). They p o ide a unique way o
communica ion be ween a human and a machine (o de ice)
wi hou any neu omuscula in e en ion (Abi i e al., 2017;
Wolpaw e al., 2002). Mo e gene ally, B ain–Machine
In e aces (BMIs) a e de ices ha ansla e neu onal
in o ma ion in o commands capable o con olling ex e nal
so wa e o ha dwa e such as compu e s, wheelchai s,
p os hesis, and obo s. Figu e 7 shows a scheme o a BCI
in e acing and con e ing b ain ac i i y o a use in o
command signals wi h possible eedback (do ed lines) o he
use .
The design p inciple o BCIs is simila o mos o he
in e aces such as speech-based, image-based, ges u e-based
ones. I consis s o con e ing basic signals in o commands
by means o a se o p ocessing ope a ions: de ec ing he
p ima y use 's signals, p ocessing i in o de o ex ac
ele an ea u es, classi ying he ob ained ea u es in o de o
decide o which p ede ined command i is supposed o ha e
been issued; hen his command is sen o execu ion (see
Figu e 8).
BCI echniques
Di e en echniques a e used o measu e b ain ac i i y
o BCIs. Mos BCIs use elec ical signals which a e de ec ed
using senso s placed in asi ely o non-in asi ely. The e a e
se e al echniques o nonin asi e BCI, such as EEG
(elec oencephalog aphy), MEG (magne oencephalog aphy),
o MRT ( unc ional magne ic esonance imaging:
omog aphy) (Fe ei a e al., 2008). Elec oencephalog aphy
(EEG) is a physiological me hod o eco d he elec ical ac i i y
gene a ed by he b ain ia elec odes placed on he scalp
su ace. The signal ampli ude is usually unde 100 μV and he
equency band o no mal EEG signals is usually abo e DC up
o 50 Hz (Ma inek e al., 2021).
In in asi e echniques, special de ices a e inse ed di ec ly
in o he human b ain by su ge y. In Semi-in asi e, de ices a e
inse ed in o he skull on he op o he human b ain, o di ec ly
on he co ex (called Elec oco icog aphy – ECoG); he su ace
o he b ain (signal ha ing abou 1- 2 mV o ampli ude (Fe ei a
e al., 2008). In gene al, non-in asi e echniques a e conside ed
as sa es , o low-cos ype o de ices and hen easies o
s udies. Howe e , he cap u ed a human b ain signals a e
weake compa ed o in asi e echniques which a e in di ec
con ac s wi h neu al cells (Fe ei a e al., 2008; S ey l e al.,
2016).
Applica ions and Pe spec i es o BCIs
F om he beginning, mos applica ions o he biological and
physiological con ol echniques we e o ien ed owa ds he
assis ance o handicapped and disabled people. The p og ess in
de eloping BCIs is p o iding a lo o hope o his communi y,
especially o hose wi hou muscula capabili y. Wha is
ema kable conce ning he BCIs is ha mos applica ions
dedica ed o medical applica ions can in ol e he use a he
same ime as a commande and as a subjec .
A e a aining pe iod, he use can lea n how o gene a e
commands by hough s, o con ol and ac i a e p os hesis
membe s o his own body pa s such as pa alyzed membe s
(Baniqued e al., 2021; Mane e al., 2020). Figu e 9 p esen an
ope a o wea ing a BCI o con olling a mechanical sys em.
Figu e 7. BCI in e acing b ain ac i i y o sys ems
Figu e 8. Global o ganiza ion o BCIs
Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
8 / 11
Figu e 9. Ope a ion wi h BCI commanding a mechanical
sys em
BRIEF SUMMARY ABOUT AI AND HRI
Since he eme gence o he i s heo ies and app oaches o
AI, he e was a hope o in use hese echniques in pa icula o
obo s o imp o ing hei adap i i y and sma ness. The low
o echniques p o ided by AI such as symbolic compu a ions,
gene ic algo i hms, neu al ne s, uzzy logic, and machine
lea ning, has se ed and s ill se es o a emp ing o sol e and
o e come many issues ha limi obo ic applica ions. Ac ually,
AI has ed obo s by nume ous capabili ies wi h mo e o less
sa is ying success. Some ema kable ields a e speech
unde s anding, objec ecogni ion based on ision,
au onomous na iga ion, manipula ion asks, in e ac ions wi h
humans and o he en i ies, coope a ion, and so on (Pe ez e al.,
2018; Seme a o e al., 2021).
Bu ollowing he inc easing complexi y o obo ic sys ems
designed o au onomously pe o m asks and missions in
a ious en i onmen s; speci ic con ol a chi ec u es o
in elligen sys ems equi ing high le el lexibili y and
adap i i y was p oposed and implemen ed. One popula
example o such a chi ec u e is he h ee laye ed one which
combines e lexi e and eac i e beha io s as well as
delibe a i e capabili ies (A kin, 1998, p. 199; R. B ooks, 1986; S.
Ga cıa e al., 2018).
Howe e , conce ning he con ibu ion o AI o he
pa icula domain o HRI, some au ho s ha e analyzed and
discussed many ele an applica ions, challenging issues and
po en ial p omising pe spec i es (Feil-Sei e and Ma a ic, 2009;
Lemaignan e al., 2017; Seme a o e al., 2021; She idan, 2016).
In ac , he mos challenging goal o AI ela ed o HRI is s ill
how o design obo s ha can unde s and and in e p e human
beha io s and in en ions in dynamic and possibly unp edic ed
si ua ions in o de o ake app op ia e decisions?
To his end, con inuous e o s a e spen on esea ching
echniques and designing join cogni i e a chi ec u es o
imp o e HRI by ying o allow obo s gaining mo e
knowledge and au onomous de elopmen as human beings
do. E o s a e o ien ed o de eloping obo mechanisms o
enable de elopmen al lea ning and capabili y o acqui ing
skills (Lemaignan e al., 2017; Nicolescu and Ma a ic, 2005;
Seme a o e al., 2021). Beside supe ised and unsupe ised
lea ning, ein o cemen lea ning, deep lea ning;
de elopmen al au onomous lea ning is a e y impo an and
challenging app oach. I is a kind o a sel -lea ning compe ence
whe e he obo a emp o acqui e knowledge and skills by
con inuous obse a ion and imi a ion o people and o he
in elligen sys ems. As wi h humans, i equi es obse ing e en s
and si ua ions, classi ying and o ganizing hem, ex ac ing
ele an ea u es and in e ing ules and unde s anding
si ua ions and pa ne 's in en ions (A en s and G ei ans, 2022;
Nicolescu and Ma a ic, 2005).
Among he issues and pe spec i es is he need o make mo e
na u al he in e ac ion and he unde s anding be ween humans
and obo s as be ween humans hemsel es. This eques
cons i u es also one main objec i e o he 4 h indus ial
gene a ion which in ends o es ablish na u al coope a ion and
collabo a ion be ween humans and sma obo s named
some imes "cobo s" in o de o achie e common asks and
missions (A en s and G ei ans, 2022; Chak abo i e al., 2017;
Ja aid and Khan, 2021; Zamalloa e al., 2017).
Mo eo e , he ac ual and u u is de elopmen o di e en
kind o in elligen obo s and hei a ious possible in e ac ions
wi h humans is p essing owa ds a homogeneous ep esen a ion
o Human-Robo con ol a chi ec u es. The e is a se ious need o
de elop a uni ied con ol a chi ec u e o HRIS ha ele a es he
cogni i e compe encies o he obo s o app oxima e he le el o
humans and elimina es he e o e he dis inc ion be ween
humans and a i icial in elligen sys ems when wo king oge he
as eam membe s (Ha io and Adams, 2013; K äme e al., 2012;
Zaa i, 2021).
CONCLUSION
This pape has b ie ly desc ibed he mos command modes
in ol ed in HRIS. This includes he adi ional in e ac ion and
command modes which a e namely ele-manipula ion, o -line
obo compu e p og amming and lea ning by demons a ion
(lead- h ough and each pendan ). I hen in oduces he modes
which ha e been os e ed la e on by he conjunc ion o obo ics
wi h he eme gence o a i icial in elligence echniques and he
p o ision o powe ul compu ing machines. The ollowing
modes we e conside ed: in e ac i e commands based on GUI,
oice-based commands, poin ing on image-based commands,
ges u e-based commands, and inally b ain-based commands. In
addi ion, some ele an and challenging issues co esponding o
some command modes ha e been b ie ly discussed.
One can no ice ha he gene a ion o obo commands
ollows almos he same p ocess: de ec ing he in ended
command signal gene a ed by he ope a o by means o speci ic
senso s; hen analyzing and iden i ying his command w. . a
dic iona y; and inally o de ing he obo o execu ing his
command. The cons i u ion o he dic iona y ha con ains he
e e ences a e usually cons i u ed h ough a lea ning p ocess.
I s pe spec i es on he sho and mean e ms, he e is a need
o imp o e he command modes o make hem mo e lexible and
use iendly. These modes can also be combined unde a
mul imodal ope a o in e ace o p o ide mo e lexible
in e ac ion and con ol o obo s. The e is also a need o use
echniques o a i icial in elligence o enable a human- obo
coope a ion and coo dina ion as pa ne s. On he o he hand,
9 / 11
Abdelouahab Zaa i / J INFORM SYSTEMS ENG, 7(2), 14039
BCI is aking mo e a en ion o he capabili y i o e s o
con olling i ual as well as eal dynamic sys ems. P obably,
he mos impo an domain in he nea u u e is he
applica ions o BCI in o de o help handicapped and disabled
people using hei pa alyzed limbs, wheelchai s, p os hesis,
and se ice obo s.
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