ubiquitous rob

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Proceeding of the Second American University of Sharjah International Symposium on Mechatronics, Sharjah, U.A.E. April 19-21, 2005

UBIQUITOUS ROBOT: THE THIRD GENERATION OF ROBOTICS

Jong-Hwan Kim, Kang-Hee Lee, and Yong-Duk Kim

Robot Intelligence Technology Laboratory,Dept. of EECS, KAIST,

Guseong-dong, Yuseong-gu, Daejeon, 305-701, Republic of Korea{johkim,khlee,ydkim}@rit.kaist.ac.kr

ABSTRACT

This paper introduces ubiquitous robot (Ubibot) as a third gener-

ation of robotics, incorporating three forms of robots: software

robot (Sobot), embeded robot (Embot) and mobile robot (Mobot),

which can provide us with various services by any device through

any network, at any place anytime in a ubiquitous space. Sobot is avirtual robot, which has the ability to move to any place through a

network. Embot is embedded within the environment or in the

Mobot. Mobot provides integrated mobile services, which are

seamless, calm and context-aware. A Sobot, Rity, is introduced

to investigate the usability of the proposed concept. Rity is a 3D

synthetic character which exists in the virtual world, has a unique

IP address and interacts with human beings through an Embot im-

plemented by a face recognition system using a USB camera. To

show the possibility of realization of Ubibot by using the current

state of the art technologies, two kinds of successful demonstra-

tions are presented. Also robot genome is proposed to implement

a genetic robot, which is to investigate The Origin of Artificial

Species. To implement the robot genome, artificial chromosome

is introduced. This paper shows the personality of genetic robotsis decided by their genome.

1. INTRODUCTION

This paper is to investigate the feasibility of implementation of

ubiquitous robot (Ubibot) by using the current state of the art tech-

nology, which can be defined as a third generation of robotics.

Also it is to define genetic robot to investigate The Origin of Arti-

ficial Species. The genetic robot can be considered as an artificial

creature created by artificial chromosome.

In an ubiquitous era we will be living in a world where all

objects such as electronic appliances are networked to each other

and a robot will provide us with various services by any device

through any network, at any place anytime. This robot is definedas a ubiquitous robot, Ubibot, which incorporates three forms of

robots: software robot (Sobot), embeded robot (Embot) and mo-

bile robot (Mobot) [1, 2, 3].

The Ubibot is following the paradigm shift of computer tech-

nology. The paradigm shift of robotics is motivated by ubiquitous

computing and the evolution of computer technology in terms of

the relationship between the technology and humans [4, 5]. Con-

sidering the evolution of robot technology, the first generation was

dominated by industrial robots followed by the second generation

in which personal robots are becoming widespread these days, and

as a third generation in the near future, Ubibot will appear. Com-

paring the paradigm change between the personal robot and ubiq-

uitous robot eras, the former is based on individual robot systems

and the latter will be employing multiple robot systems using real

time broadband wireless network based on IPv6.

The Ubibot has been developed based on the robot technol-

ogy and the concept of ubiquitous computing in the Robot Intel-

ligence Technology (RIT) Lab., KAIST since 2,000. In the future

we will live in a ubiquitous world where all objects and devices are

networked. In this ubiquitous space, u-space, a Ubibot will pro-

vide us with various services anytime, at any place, by any device,

through any network. Following the general concepts of ubiqui-

tous computing, Ubibot will be seamless, calm, context-aware, and

networked.

Although this paper is to investigate the feasibility of Ubibot,

the basic concept leads us to seek the essence of what it means to

be robot in the third generation of robotics. So far most of robot

researchers have been devoted to develop and improve function-

alities of robot such as intelligence, human-robot interaction, and

mobility, without mentioning the essence of the robot as an artifi-

cial creature.

Since The Origin of Species by Charles Darwin in 1859,

the concept of evolution has been widely spread around the world.

Motivated by his discovery of evolution, the simulated evolution

has been applied to engineering problems to get an optimal so-

lution by employing the concept of chromosome representing the

solution candidate. In 1976, Richard Dawkins claimed that We

and other animals are machines created by our genes [6]. In the

third generation of robotics, genetic robot can be proposed, which

is created by artificial chromosome [7].

This paper introduces a new concept of artificial chromosome

as the essence to define the personality of a genetic robot and to

pass on its traits to the next generation, like a genetic inheritance.

It is an essential component for simulated evolution, which nec-

essarily defines The Origin of Artificial Species. If we think the

origin in terms of the essence of the artificial creatures, the essence

should be a computerized genetic code, which determines a ge-

netic robots propensity to feel happy, sad, angry, sleepy, hungry

or afraid.

The first part of this paper presents the definition and basic

concepts of Ubibot incorporating three forms of robots; Sobot,

Embot, and Mobot. A Sobot, called Rity, developed at the RIT

Lab., KAIST, is introduced to investigate the usability of the pro-

posed concept of Ubibot [8, 9]. Rity is a 3D synthetic character

which exists in the virtual world, has a unique IP address and in-

teracts with human beings through an Embot implemented by a

face recognition system using a USB camera.

Rity is an autonomous agent which behaves based on its own

internal states, and can interact with a person in real-time. It can

provide us with an entertainment or a help through various interac-

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tions in real life. To realize this, it needs an autonomous function,

artificial emotional model, learning skill, sociableness, and its own

personality [10, 11]. It can be used as a character on a game or a

movie or for the purpose of education [12, 13].

An architecture of Rity can be divided into five modules: per-

ception module, internal state module to implement motivation,homeostasis, and emotion [14, 15, 16], behavior selection module

[17, 18], interactive learning module [19], and motor module.

To show the possibility of realization of Ubibot, two kinds of

demonstrations are carried out by using the current state of the art

technologies.

In the second part, Rity is considered as an artificial creature

living in a virtual world of a PC. It is a genetic robot which has

its own genetic information. Rity is employed to test the worlds

first robotic chromosomes, which is a set of computerized DNA

(Deoxyribonucleic acid) code for creating genetic robots that can

think, feel, reason, express desire or intention, and could ulti-

mately reproduce their kind, and evolve as a distinct species.

Using this concept, a way to build artificial chromosomes is

proposed for genetic robots that would be capable of human-styleevolution. Thus, the genetic code should be designed to represent

all the traits and personality of artificial creature: a manner of re-

sponse to stimuli, the desire to avoid unpleasantness, to achieve

intimacy and control, to satisfy curiosity or greed, and to prevent

boredom, feelings of happiness, sadness, anger and fear to stimuli,

and states of fatigue, hunger, drowsiness and so on, in order to im-

bue the artificial creature with life. It can react emotionally to its

environment, learns and makes reasoned decisions, based on an in-

dividual personality. The programmed genetic code is modelled on

human DNA, though equivalent to a single strand of genetic code

rather than the complex double helix of a real chromosome. The

main functions of the genetic code are reproduction and evolution.

This paper is organized as follows. Section II presents the

definition and basic concepts of Ubibot. Section III describes theoverall architecture of the Sobot. Demonstrations of the Sobot,

Rity are provided in Section IV. Section V proposes genetic robot.

Finally, concluding remarks follow in Section VI.

2. UBIQUITOUS ROBOT: UBIBOT

Ubibot is a general term for all types of robots incorporating soft-

ware robot (Sobot), embedded robot (Embot), and mobile robot

(Mobot) which exist in a u-space. Ubibot exists in the u-space

which provides physical and virtual environments.

2.1. U-space and Ubibot

Ubiquitous space (u-space) is an environment in which ubiquitous

computing is realized and every device is networked. The world

will be composed of millions of u-spaces, each of which will be

closely connected through ubiquitous networks. A robot working

in a u-space is defined as a Ubibot and provides various services

through any network by anyone at anytime and anywhere in a u-

space.

Ubibot in a u-space consists of both software and hardware

robots. Sobot is a type of a software system whereas Embot and

Mobot are hardware systems, Figure 1. Embots are located within

the environment, human or otherwise, and are embedded in many

devices. Their role is to sense, analyze and convey information

to other Ubibots. Mobots are mobile robots. They can move

Figure 1: Ubibot in ubiquitous space

both independently and cooperatively, and provide practical ser-

vices. Each Ubibot has specific individual intelligence and roles,

and communicates information through networks. Sobot is capa-

ble of operating as an independent robot but it can also become themaster system, which controls other Sobots, Embots and Mobots

residing in other platforms as slave units. Their characteristics are

summarized in the following. For details, the reader is referred to

[2].

2.2. Software Robot: Sobot

Since Sobot is software-based, it can easily move within the net-

work and connect to other systems without any time or geograph-

ical limitation. It can be aware of situations and interact with the

user seamlessly. Sobot can be introduced into the environment

or other Mobots as a core system. It can control or, at an equal

level, cooperate with Mobots. It can operate as an individual en-tity, without any help from other Ubibots. Sobot has three main

characteristics, such as self-learning, context-aware intelligence,

and calm and seamless interaction.

2.3. Embedded Robot: Embot

EmBot is implanted in the environment or in Mobots. In coopera-

tion with various sensors, Embot can detect the location of the user

or a Mobot, authenticate them, integrate assorted sensor informa-

tion and understand the environmental situation. An Embot may

include all the objects which have both network and sensing func-

tions, and be equipped with microprocessors. Embots generally

have three major characteristics, such as calm sensing, informa-

tion processing, and communication.

2.4. Mobile robot: Mobot

Mobot is able to offer both a broad range of services for general

users and specific functions within a specific u-space. Operating

in u-space, Mobots have mobility as well as the capacity to pro-

vide general services in cooperation with Sobots and neighboring

Embots. Mobot has the characteristics of manipulability by imple-

menting arms and mobility which can be implemented in various

types, such as wheel and biped. Mobot actions provide a broad

range of services, such as personal, public, or field services.

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Behavior selector

Motivation Homeostasis Emotion

SymbolizerAttention selector Reward/penalty

signal

End signal

Sensorvalue

Preferencelearner

Sobot

Behavior

Perceptionmodule

Learningmodule

Internalstatemodule

Behaviormodule

Motormodule

Fatigue

Hunger

Drowsiness

Behavior

Virtualenvironment

Actuator

Voicelearner

Curiosity

Intimacy

Monotony

Happiness

Sadness

Anger

Symbol vector

Inherentbehaviorselector

Urgentflag

Masking

Sensors

TactileVision Sound Gyro TimerIR

Figure 2: Internal architecture of Rity

3. IMPLEMENTATION OF SOBOT

Sobot is a software robot which recognizes a situation by itself, be-

haves based on its own internal state, and can interact with a person

in real-time. Sobot should be autonomous; it must be able to selecta proper behavior according to its internal state such as motiva-

tion, homeostasis and emotion. Also, Sobot should be adaptable;

it should adapt itself to its environment. For the purpose of achiev-

ing these functions easily and efficiently, Sobot mimics an animal

which is an autonomous and adaptable agent in nature. Fig. 2

shows an internal architecture of the proposed Sobot, Rity, where

necessary modules are defined as follows: 1) Perception module,

which perceives environment through virtual and physical sensors,

2) Internal state module, which includes motivation,homeostasis

and emotion, 3) Behavior selection module, which selects a proper

behavior, 4) Learning module, which learns from the interaction

with a people, and 5) Motor module, which executes a behavior

and expresses emotion.

3.1. Perception module

The perception module includes a sensor unit, a releaser having

stimulus information provided by a symbol vector and a sensitivity

vector, and attention selector. This module can perceive and assess

the environment and send the stimulus information to the internal

state module. Sobot has several virtual sensors for light, sound,

temperature, touch, vision, gyro, and time. Sobot can perceive 47

types of stimulus information from these sensors. Based on these

information, Sobot can perform 77 different behaviors.

3.2. Internal state module

The internal state module defines the internal state with the mo-

tivation unit, the homeostasis unit and the emotion unit. Motiva-

tion (M) is composed of six states: curiosity, intimacy, monotony,avoidance, greed, and the desire to control. Homeostasis (H) in-cludes three states: fatigue, hunger, and drowsiness. Emotion (E)includes five states: happiness, sadness, anger, fear, and neutral.

According to the internal state, a proper behavior is selected.

3.3. Behavior selection module

Behavior selection module is used to choose a proper behavior,

based on Sobots internal state as well as stimulus information.

When there is no command input from a user, various behaviors

can be selected probabilistically by introducing a voting mecha-

nism, where each behavior has its own voting value. The algorithm

is described as follows: 1) Determine temporal voting vector, Vtusing M and H, 2) Calculate voting vector Vby masking Vt withattention command and emotion masks, 3) Calculate a behavior

selection probability, p(b), using V, 4) Select a proper behavior bby p(b) among various behaviors.

Initially, the temporal voting vector is calculated from the mo-

tivation and homeostasis as follows:

VTt =

M

TDM +H

TDH

=[vt1, vt2, , vtn]

(1)

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DM =

dM11 dM12 dM1n

dM21 dM22...

.

...

. .dMx1 dMxn

DH =

dH11 dH12 dH1n

dH21 dH22...

.

... . .

dHy1 dHyn

(2)

where n, x and y are the numbers of behaviors, motivations, andhomeostases. vtk, k = 1, , n, is the temporal voting value,DM and DH are weights connecting the motivation and home-ostasis to behaviors, respectively.

As a next step, various maskings to the temporal voting vector,

Vt are implemented considering emotion and external sensor infor-mation. Here, three kinds of masking are implemented to the tem-poral voting vector. These three kinds of maskings are masking

for attention, masking for command, and masking for emotion.

The masking process is to select a more appropriate behavior such

that it prevents Sobot from carrying out unusual behaviors. For

example, a behavior when it recognizes a ball should be different

from that when it recognizes a person. When Sobot does not see

the ball, masking for attention to the ball is carried out such that

behaviors related to the ball are masked out and are not activated.

An attention masking matrixQa(Sa(t)) is obtained by the at-tention symbol, Sa(t). Each attention symbol has its own maskingvalue and the matrix is defined as follows:

Qa(Sa(t)) =

qa1(Sa(t)) 0 0

0 qa2 (Sa(t))...

.... . .

0 qan(Sa(t))

(3)

where n is a number of behaviors, qa() is a masking value, and0 qa() 1. Similarly, command and emotion masking matri-ces are defined.

From these three masking matrices and the temporal voting

vector, the behavior selector obtains a final voting vector as fol-

lows:

VT =VTtempQ

a(a)Qv(c)Qe(e)

=[v1, v2, , vn](4)

where vk, k = 1, 2, , n, is the kth behaviors voting value.Finally, the selection probability p(bi) of a behavior, bi, i =

1, 2, , n, is calculated from the voting values as follows:

p(bi) =vi

nk=1

(vk). (5)

By using the probability-based selection mechanism, the be-

havior selector can show diverse behaviors.

Even if a behavior is selected by both internal state and sensor

information, there are still some limits on providing Sobot with

natural behaviors. Inherent behavior selector makes up for the

weak points in the behavior selector. It imitates an animals in-

stinct. For instance, as soon as an obstacle like a wall or a cliff is

found, it makes Sobot react to this situation immediately. Since ituses only sensory information directly, its decision making speed

is faster than that of the behavior selector. The deterministic in-

herent behavior selector and the probabilistic behavior selector are

complementary to each other for realizing a natural behavior. This

means that it can help Sobot do right thing while carrying out var-

ious behaviors.

3.4. Motor module

The motor module incorporates an actuator to execute behaviors

and present emotions subject to the situation.

3.5. Learning module

Learning module consists of preference learner and command learner.

The former is to teach Sobot likes and dislikes for an object. If

Sobot gets a reward or a penalty, the connected weights from the

symbol to internal states are changed. On the other hand, the latter

is to teach Sobot to do an appropriate behavior which a user wants

Sobot to do.

The learning can be considered as adjusting weighting param-

eters between commands and behaviors; if Sobot does a proper

behavior for a given command, the weight between the command

and the behavior is strengthened, and others are weakened. How-

ever, there are usually tens of behaviors. Thus, the learning process

requires lot of time. Also it may be difficult to expect a desired

behavior for an ordered command. To solve these problems, anal-

ogous behaviors are grouped into a subset before learning. For in-

stance, the set SIT is composed of behaviors such as sit, crouch,

and lie, and so on, as similar behaviors to sit. If a proper behavior

is carried out for a certain command, all the corresponding weights

of the subset are strengthened and vice versa. The update law is as

follows:

Wij(t + 1) = Wij(t) + Ri (6)

Ri =

+Cr on reward

Cp on penalty

where Wij is a weight between the ith command and the jth be-havior subset, is an emotion parameter, Ri is for a weight changefor reward or penalty, and Cr and Cp are positive constants. When

Sobot receivesa patting (hitting) through a tactile sensor or a praise(a scolding) through a sound sensor, the perception module trans-

lates it as a reward (penalty). Weight is increased on reward, and

decreased on penalty as shown in (6). It should be noted that an

emotion parameter, is employed to consider the fact that learningrate depends on internal states. That is, learning speed is fast when

happiness value is high and vice versa.

Although the learning has been done on a behavior subset

level, considering the direct contribution of the selected behavior

the command masking values are assigned differently as follows:

qvm(ci) = Wij

qv(ci) = Wij

(7)

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with > > 0where qvm(ci) is a masking value of a behavior, bm carried out justnow by the command, Ci and q

v(ci) indicates masking values ofother behaviors in the same subset, Bi and and are positiveconstants. The command masking matrix is updated in proportion

to weight values. A behavior activated just now and other behav-iors in the same subset influence different weight changes by and . Since is bigger than , the activated behavior gets alarger weight value than others in the same subset.

4. DEMONSTRATIONS FOR UBIBOT

To demonstrate the usability of Rity for Ubibot, a Sobot, Rity is

developed in a 3D virtual world. The following two demonstra-

tions show seamless and omni-presence properties of Sobot.

4.1. Seamless integration of real and virtual worlds

This section will demonstrate how, in a virtual environment, Rity

will continuously cooperate with the real world with the help of a

USB camera. The face recognition system stored in a PC watches

the neighboring environment through the USB camera and, when a

human is detected, analyzes, recognizes and authenticates the face.

The result is to be sent to Rity through the network. Sobot will then

react to the vision input information as it would normally react us-

ing the virtual sensing information. If the human is Ritys master,

Rity will tend to stare at the master and happily greet him/her.

Fig. 3, 4 and 5 are photographs of computer screens show-

ing the virtual pet, Rity, in a virtual 3D environment. The small

window at the bottom right of Fig. 3 shows the visual information

in the form of a recognized face. A PCA method[20], which has

been enhanced based on the evolutionary algorithm, was used for

face detection. The window at the top right shows the graphical

representation of the internal states of Rity.

Voice command Emotion

Rity

Masters face recognition

Ritys internal state

Voice command Emotion

Rity

Masters face recognition

Ritys internal state

Figure 3: Seamless integration of real and virtual worlds

Fig. 4 shows an example, in which Rity recognizes its master.

Rity then shows a happy look and welcomes him, with an increase

of such internal states as curiosity, intimacy, and happiness.

In Fig. 5, when a human who is not the master appears, Rity

ignores him/her. In this case, for example, the internal state keeps

as it has been.

Figure 4: When Rity recognizes its master

Figure 5: When Rity detects a stranger

4.2. Omni-present Sobot

This section discusses how Sobot can be connected and transmit-

ted any time and at any place. Fig. 6 shows the interaction between

Sobot A, owned by User A and Sobot B, owned by User B.

For example, Sobot A is implemented at a local site, connects

to the network and then invites Sobot B, located at a remote site,

into its local space. Both Sobots (A and B) should have their own

individual IP addresses. The User B will type in the ID and pass-

word and the IP address of Sobot B in order to access the remote

site. Once access is approved, Sobot B, carrying its native charac-

teristics and behavior patterns, can enter the local environment of

User A.In Fig. 7, there are two Sobots in the local space. They look

the same but have different characteristics. If the user gives the

same stimulus to the two Sobots, for example, clicks once to pat

or twice to hit, each Sobot will react differently because of their

different characteristics. Fig. 7 shows the results of the experi-

mentation after applying 10 instances of patting, or clicking, on

both Sobots A and B. The figure shows the changes in internal

states, facial expression and their behavior. As the amount of cu-

riosity, intimacy and happiness increases, Sobot A starts moving

around with a happy face, Fig. 7(a). On the other hand, in the case

of Sobot B, the drowsiness increases making it sad and eventually

sleepy. Fig. 7(b) and7(c) shows a comparison of the internal states

of Sobot A and B.

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(a) (b)

Figure 6: Omni-present Sobot (a) connection with another Sobot

in a remote site (b) IP address of a Sobot in a remote site, username

and password for certification

Sobot can be downloaded and sent regardless of whether the

site is local or remote. This is made possible by defining a common

platform of the 3D graphic environment along with sensors andbehaviors.

5. ROBOT GENOME

This section presents a way to build an artificial creature that would

be capable of human-style evolution. As is well known, there are

no one gene - one trait relationships in naturally evolved systems

because of the pleiotypic and polygenic nature of the genotype,

where pleiotypic nature has the effect that a single gene affects

multiple phenotypic characters and polygenic nature has the effect

that a single phenotypic character is affected by multiple genes. It

means a single genetic change can affect every phenotypic charac-

teristic.

To reflect this nature, unlike previously devised methods thatassociated stimuli with responses, Ritys chromosomal coding con-

tains a sophisticated weighting system provided in the internal ar-

chitecture (Figure 2). Internal relationships created by the weight-

ing system allow Rity to be an individual capable of more than

purely mechanistic response. Also it has a kind of programmed

favoritism for one subtle shade of emotional or rational response,

over another.

Rity has fourteen artificial chromosomes by which its traits

can be passed on to its offspring. It perceives 47 different types

of stimuli and can respond with 77 different behaviors as its re-

sponses. Figure 8 shows its 14 chromosomes, where chromosomes

C1-C6 are related to motivation,C7-C9 to homeostasis, andC10-

C14 to emotion. Also, motivation is composed of six states (chro-

mosomes): curiosity (C1), intimacy (C2), monotony (C3), avoid-ance (C4), greed (C5), and desire to control (C6). Homeosta-

sis includes three states (chromosomes): fatigue (C7), drowsiness

(C8), and hunger (C9). Emotion includes five states (chromo-

somes): happiness (C10), sadness (C11), anger (C12), fear (C13),

and neutral (C14).

Each chromosome Ck, k = 1, 2, , 14, consists of threekinds of genes: F-genes xFk, I-genes x

Ik, and B-genes x

Rk, de-

fined as

Ck =

xFkxIkxBk

(8)

(a)

(b) (c)

Figure 7: Omni-presence (a) Sobot A in a local site and Sobot B

downloaded from a remote site (b) Internal state of Sobot A (c)

Internal state of Sobot B

with

xF

k =

xF1xF2

...

xFp

,xIk =

xI1xI2

...

xIq

,xBk =

xB1xB2

...

xBn

(9)

where p, q, and n are total numbers of F-genes, I-genes, andB-genes in a chromosome. In Rity, p = 5 , q = 47, and n = 77 .

Consequently, a robot genome G, which means a chromoso-

mal set with genetic codes determining Ritys personality, is de-

fined as

G = C1 C2 C14 . (10)F-genes represents fundamental characteristics of Rity, includ-

ing genetic information such as volatility, initial and mean value of

each internal state, some intrinsic parameters, etc. Volatility means

whether the internal state is volatile or non-volatile since operating

point in time. F-genes can also include sex, life span, color and so

on to define its fundamental nature.

I-genes includes genetic codes representing its internal prefer-

ence by setting the weights between the stimulus and internal state.

Theses genes shape variety of the internal state affected by stimuli

and have information of whether the stimulus satisfies, amplifies,

or has nothing to do with the internal state. After the birth, the

preference can be trained on-line by adapting the weights like pet

training.

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C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14

F-GENES

I-GENES

B-GENES

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14

F-GENES

I-GENES

B-GENES

Figure 8: Artificial chromosomes of Rity

B-genes includes genetic codes related to output behavior by

setting the weights between the internal state and voting vector.

These genes are in charge of behavior selection, its frequency, and

its activation level based on the internal state. They also include

masking information which prevents Rity from doing unnecessary

emotional expression and behaviors.

Genetic robot can be defined as a robot which has its own ge-

netic codes. This section verifies the concept of genetic robot byimplanting the artificial chromosomes into Ritys. The genes in

Figure 8 are originally represented by real numbers; values of F-

genes range from 1 to 500, I-genes from 0 to 5000, and B-genes

from 1 to 1000. Like a DNA analysis, these genes are normalized

to brightness values from 0 to 255, which are expressed to black-

and-white rectangles. The darker the color is, the higher its value

is.

Figure 9 shows two different chromosome set of Ritys. As

per their genetic codes, no two Ritys react the same way to their

surroundings as shown in Figure 10. One was bored; the other was

panted and expressed happiness at the sight of their human han-

dlers because they had a different personality. It totally depends

on their genes.

Current version is equivalent to a single strand of genetic codeof real numbers rather than the complex double helix of a real chro-

mosome. One of future works is on the equivalent of X and Y

chromosomes that would confer sexual characteristics. Thus, if

male and female like each other, they could have their own chil-

dren. Also the software chromosomes will be implanted in a mo-

bile robot so that they will imbue the robot with life. Consider-

ing the concept of ubiquitous robot and ubiquitous computing en-

vironment, however, a key future work should be that the robot

genome is to be sent via the Internet to other computers or pieces

of hardware, becoming a sort of wirelessly transmissible soul

that would invisibly control the actions and desires of future inter-

connected appliances, from devices in a smart home or office, to

cellphones or security cameras including ubibots.

(a) (b)

Figure 9: Two different chromosome set of Ritys: (a) chromo-

some set of Rity A and (b) chromosome set of Rity B

(a)

(b) (c)

Figure 10: Rity A and Rity B in a virtual space: (a) Rity A and

Rity B, (b) Internal state of Rity A, and (c) Internal state of Rity B

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6. CONCLUDING REMARKS

This paper introduced a ubiquitous robot, Ubibot, as a third gen-

eration of robotics, which integrates three forms of robots: Sobot,

Embot and Mobot. Rity, a Sobot or an artificial creature living in

a virtual 3D world of a PC, was implemented using two scenariosto demonstrate the possibility of realizing Ubibot. The first sce-

nario illustrated how Rity, with the support of Embot, could recog-

nize its master and reacted properly. This was to show the seam-

less integration of real and virtual worlds. The second scenario

demonstrated how Sobots could be transmitted through networks

and be transposed into different locations. This was to demonstrate

the omni-presence capability by using Sobot. This paper also pro-

posed a new concept of robot genome to investigate The Origin of

Artificial Species, such as genetic robot. The robot genome was

implanted into Rity to test a feasibility that genetic robots could

have their own personality. The artificial chromosomes will lead

the genetic robot to reproduction and evolution.

In the new ubiquitous era, our future world will be composed

of millions of u-spaces, each of which will be closely connectedthrough ubiquitous networks. In this u-space we can expect that

Ubibot will help us whenever we click as Genie of the Magic Lamp

did for Aladdin.

Acknowledgments

This work was supported by the Ministry of information & Com-

munications, Korea, under the Information Technology Research

Center (ITRC) Support Program.

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