INTERNET-BASED TELEOPERATION: A CASE STUDY

Toward Delay Approximation and Speed Limit Module

Shengtong Zhong, Philippe Le Parc and Jean Vareille

Laboratoire Informatique des Systèmes Complexes (LISyC), Université de Bretagne Occidentale

20, avenue Le Gorgeu, 29285 Brest Cedex, France

Keywords: Remote control, teleoperation, mobile robot, Internet delay, path error, delay approximator, speed limit.

Abstract: This paper presents the internet-based remote control of mobile robot. To face unpredictable Internet delays

and possible connection rupture, a direct teleoperation architecture with “Speed Limit Module” (SLM) and

“Delay Approximator” (DA) is proposed. This direct control architecture guarantees the path error of the

robot motion is restricted within the path error tolerance of the application. Experimental results show the

effectiveness and applicability of this direct internet control architecture in the real internet environment.

1 INTRODUCTION

Internet is not only an information highway, but also

a mean to remotely control mechanical systems, such

as robotic devices. But Internet doesn’t provide a

guaranteed Quality of Service (QoS); it entitles a

number of limitation and difficulties, such as

bandwidth constraint, transmission delays, packet

lost, connection rupture etc. The situation above

influence the performance of Internet based

telerobotics systems, which is a new field in the

recent decade.

The Mercury project (Goldberg et al., 1994) is

ne of the earliest telerobotics implementation over

the internet, then coming with the Telerobot in

Australia (Taylor and Dalton, 1997), the painting

PumaPaint Robot (Stein, 1998), and Khepera robot

(Saucy and Mondada, 2000) etc. During the past ten

years, lots of such systems have been introduced by

different researchers all over the world.

Most of these researches use a supervisory

cont

rol scheme which enables operator to issue high

level commands. As the internet time delay is

unpredictable, the design of direct control scheme

which enables user to control the motion of robot

continuously may not be easy. Such control schemes

have been proposed, but are not adequate to alleviate

e influence of Internet time delay.

This paper presents direct teleoperation

architecture

of a continuous robot motion control

which meets path error tolerance under the

unpredictable Internet time delay. Here, the path

error is guaranteed only if the path error at every

turning/stop point is restricted within a path error

tolerance which depends on application itself.

Two kinds of control strategy are introduced in

e Section 2, followed by the detail of “Speed Limit

Module” (SLM) with the quality level idea of

GEMMA-Q (Ogor, 2001) and how it works together

with the “Delay Approximator” (DA) to meet the

application requirements. During the Section 3, the

software implementation is presented with an

application over Miabot (two-wheeled robot widely

used in soccer competition organized by FIRA).

2 TELEOPERATION

ARCHITECTURE

2.1 Generic Architecture

The teleoperation over Internet lies on a generic

teleoperation architecture (Figure 1), through which

commands are exchanged between remote system

and operator (user). The user, through his Internet

navigator, addresses a request to a Web Server (step

1) and downloads an application, such as a Java

applet (step 2), on his own workstation. A

connection is then established towards the

Application Server in charge of robots and client

management (step 3). In the same time, another

connection with Multimedia Server is also

established in the form of exchanging media signals.

The user is now able to control the remote robot

upon request.

267

Zhong S., Le Parc P. and Vareille J. (2007).

INTERNET-BASED TELEOPERATION: A CASE STUDY - Toward Delay Approximation and Speed Limit Module.

In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics, pages 267-270

DOI: 10.5220/0001648202670270

 SciTePress

The generic architecture is the same in most

applications. The key problem is to alleviate the

influence of Internet time delay and towards a

continuous control within the path error requirement.

Figure 1: Generic architecture.

2.2 Control Strategies

2.2.1 “Move and Wait” Strategy

The “ Move and Wait” strategy (Sheridan, 1992),

which is typical for space robots with long distance

communication has been applied first. In the Miabot

case, five commands: “move forward” (MF), “move

backward” (MB), “turn left” (TL), “turn right” (TR)

and “stop” (ST) have been defined. These commands

are enough to perform any complex task, but the user

has to send lots of commands and change the move

or turn parameters from time to time to meet the

requirement.

2.2.2 “Speed Control” Strategy

To reduce user’s workload and towards a fluent

process during the complex task, a “Speed control”

strategy, similar to real driving, is introduced. “No-

stop move forward” (NSMF), “no-stop move

backward” (NSMB), “turn left” (TL), “turn right”

(TR) and “stop” (ST) commands are defined in this

strategy. When the robot executes a turning

command, it stops running first, perform the entire

turning next, and then runs in previous speed again.

The user may choose different running speed as well

as turning degree.

The user’s operation reduce is significant. The

robot is running with speed

during the whole task

even though there is a turning/stop point. When the

user sends a turning/stop command to robot, the

command reaches the robot with a discrete time

delay due to Internet time delay. The robot may

run an extra distance before it performs the

turning/stop.

tΔ

dΔ

tvd Δ×=Δ

Where

indicates the current speed of the robot,

the current Internet time delay between sending the

command from the user and executing the command

by robot.

As Internet doesn’t provide a guaranteed Quality

of Service (QoS), the time delay is unpredictable.

Figure 2 is an execution result of the task A E

with “Speed control” strategy. The path error is

accumulative, and path deviation is significant which

may result in the failure of the task.

→

Figure 2: A path result with “Speed Control”.

2.3 Speed Limit Module and Delay

Approximator

2.3.1 Speed Limit Module (SLM)

The GEMMA-Q (Ogar, 2001) methodology derived

from GEMMA (ADEPA, 1981) has been proposed.

The basic idea is to define the quality of

communication as a discrete value. Following the

value, the automated system has to follow different

rules to ensure the security (path error). According to

the type of quality, these rules might be different. If

the user has a slightly deteriorated communication

quality, the user might keep the control and the

automated system has to work in deteriorated mode.

The GEMMA-Q has been used in the application

over robot arm and prototype machine (Le Parc et al.,

2001). In this paper, which aims to control a simple

robot, use only the quality level idea of GEMMA-Q

to design SLM.

communication quality levels are

introduced which corresponds Internet time delay

zone (Time D.). Each time delay zone has its own

sub path error tolerance

(Sub T.) and Max

Speed as shown in the Table 1.

ICINCO 2007 - International Conference on Informatics in Control, Automation and Robotics

268

Table 1: Quality levels in SLM.

Qual. Time D. Sub T. Max Speed

~0 t

000

/tv

Δ=

~ tt

)/(

0111

ttv

−

Δ=

~ tt

)/(

1222

ttv

−

Δ=

~ tt

)/(

2333

ttv

−

Δ=

...

1−n

tt ~

1−

)/(

111 −−−

−

Δ=

nnnn

ttv

t≥

⎪

⎩

⎪

⎨

⎧

−∈≤

≤Δ

∑

)1,1,0(

njvv

δδ

When the quality level changes, the Application

Server evaluates the Current Robot Speed (CRS) and

the Max Speed of this quality level (MSoT). If

CRS MSoT, no command is sent to robot; else the

Application Server sends MSoT command to robot

(change CRS to MSoT).

≤

MSoT is calculated by the time delay zone and

sub tolerance which are defined by user according to

application. In order to meet the path error tolerance

at the turning/stop point, the following constraints

are used when designing SLM:

The above constraint guarantees the path error at

the turning/stop point is restricted within

in any

Internet time delay situation.

is the best quality

level, its Max Speed

is the fastest running speed

of the robot.

is the disconnection situation, and

the robot stops running immediately . The

proof of how the constraint works are shown below.

)0( =

There are two kinds of situation when the robot

runs under the speed limit rules.

1. Stable network delay

It means the robot is running in the same time

delay quality level

between two continuous

actual Internet time delay (from the real clock

time of receiving previous actual Internet time

delay to the real clock time of receiving next

actual Internet time delay). Then

2. Unstable network delay

The robot is running in the different time

delay quality levels between two continuous

actual Internet time delays. The worst case is

from to :

≤

Δ=

Δ+

∑

The path error

is within the restriction of

path error tolerance

in both situations. Then the

path error at every turning/stop point in the task is

guaranteed and the successfully continuous control

of the robot is achieved.

With the constraints, the different quality levels

with its respective time delay zone value, sub

tolerance and max speed are defined according to

different application. e.g.: the normal quality level of

Internet time delay is

in the application, its sub

tolerance

should take a larger percentage of

. It means the robot is preferred to have larger sub

tolerance in the normal quality level; in the same

time, speed limit rules guarantees

≤Δd

in any

situation.

Figure 3: A path result using “Speed Control” with SLM.

In Figure 3, the path deviation at every turning/stop

point is restricted within

. Then a successful task

is achieved using “Speed control” with SLM. The

above describes the detail SLM with the quality level

idea, next part emphasize on how the gets the quality

level information of current time delay from DA.

2.3.2 Delay Approximator (DA) Principals

δδδ

≤

Δ=

Δ++Δ+Δ=

−++−×+×≤

×=Δ

∑

−

iii

ttvttvtv

tvd

101100

)()(

In the generic architecture, Pinger-Ponger is the

mechanism to provide the Internet time delay

information to DA. The next actual Internet time

delay

is calculated as follows:

pnn

TTt −

Where

is the real clock time of receiving previous

actual Internet time delay from Pinger-Ponger;

the real clock time when Pinger-Ponger sends the

next Internet time delay to DA.With above feature,

INTERNET-BASED TELEOPERATION: A CASE STUDY - Toward Delay Approximation and Speed Limit Module

269

the current (up-to-now) time delay from is

formed as:

tΔ

is the time delay zone in SLM.

is the

watchdog and is the automatic counter initialized

with 0.

is only activated when there is quality

level change, and this quality level change is used as

tΔ

current time delay change information.

Pinger-Ponger only provides the Internet time

delay when it gets one. The Internet time delay is

unpredictable, so there is no idea when Pinger-

Ponger gets new information.

There is no idea about the future, but the current

situation is supervised by DA as following principals:

1. DA receives information from Pinger-Ponger.

Pinger-Ponger informs DA of receiving the

next actual Internet time delay, and then DA

forwards the quality level of calculated

SLM. Meanwhile the previous parameters are set

to be the current ones: the value of

is set

, the quality level of previous actual

Internet time is changed to the quality level of

, reset the watchdog .

2. No information from Pinger-Ponger and

tΔ )(

tΔ

is activated to a quality level change.

is the previous actual Internet time delay.

There are two kinds of situations:

tΔ

•

The quality level of current time delay is

no worse than that of previous actual time

delay; there is no action and DA keeps

supervising.

tt Δ≤Δ

•

The quality level of current time delay

situation is worse than that of previous actual

tt Δ>Δ

Internet time delay. When

is activated, it

indicates a change of quality level and “DA”

forwards the new quality level to SLM. DA

keeps supervising.

tΔ

DA keeps supervising the Internet delay situation

all the time. It provides the real Internet time delay

or current time delay to SLM.

3 EXPERIMENT

The remote control system server has been built in

UBO, France. Some users (mainly from France,

Sweden, and China) are invited to test the feasibility

of effectiveness of the system. The average Internet

time delay varies a lot between European users and

Asian users. It’s not easy to find a uniform SLM for

all the users, but certain SLM works fine for some

users. The test is still on-going currently. The

average Internet time delay of the user is able to

observe during the test, so next step consideration is

to build SLM for respective user group

(distinguished by average Internet time delay. e.g.:

Asia, Europe, etc.) and the system can choose

different SLM automatically due to the user group.

⎩

⎨

⎧

∈−=Δ

==Δ

−

),2,1(

njttt

jtt

jjc

4 CONCLUSION

In this paper, the SLM and DA based architecture is

proposed to face the unpredictable Internet delay in

Internet-based robot control. This approach

guarantees the path error of the continuous robot

motion. Here, the path error is guaranteed only if the

path error at every turning/stop point is within a path

error tolerance

which depends on application

itself.

In this architecture, the current time delay is

supervised by DA; and SLM applies different speed

limit rules according to the current time delay

situation. Then the robot is always running in a

proper speed which meets the path error restriction.

Finally, a continuous control of the internet-based

robot is achieved successfully.

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Meng Wang, and James N.K. Liu, 2005. Interactive

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