thesis abstract susnea

7/29/2019 Thesis Abstract Susnea

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Embedded Microcontroller Solutions forReal-Time Control of Autonomous Mobile

Robots

A Ph.D. Dissertationpresented by Ioan Susnea, in February 2010

Under the supervision of Prof. Dr. Adrian

Filipescu

UNIVERSITY DUNAREA DE JOS OF GALATI,ROMANIA


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The Main Thesis of this Research

A distributed network of embedded

microcontrollers can solve the mostimportant problems of thenavigation control of autonomous

robots.


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Justification

Such solutions may lead to significantcost reduction for robotic systems andcan contribute to the development of

commercial Personal RoboticAssistants for the elderly and disabled.

There is an acute social need forsolutions in this field.


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Difficulties

Commonly used microcontrollers havesevere constraints in what concernscomputation power and data storage

capacity.

The tasks associated with robot control

are very complex.


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Research Strategies

In order to compensate the limitedcomputational power of microcontrollers, a

distributed multi-processor structure has

been proposed.

Appropriate control algorithms have been

selected New control algorithms, compatible with

microcontrollers have been developed.


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Main Problems Considered inthis Research

Robot navigation problems from theperspective of control theory


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General Assumptions

KINEMATIC CONTROL

DECISION

DATAACQUISITION

SENSORS

ACTUATORS

COMPUTING &COMMUNCATIONEQUIPMENT

WIRELESSLINK

AUTONOMOUS VEHICLE SMART ENVIRONMENT

DYNAMIC CONTROL

The following structure of the control system is proposed:

Each block is implemented with a distinct embedded module


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Where Am I?

The Problem of Localization in Robotic

Systems

Objective of the research:

Design of an active ultrasonic beacon able to:

- Allow the measurement of the distance

between the robot and the beacon,

-Allow the measurement of the azimuth of thebeacon relative to the robot,

- Allow the identification of the beacons.


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The principle of measuring the distancebetween the robot and the beacon

t

t

t

t

ransm

tter

ecever

Radio signal

Radio signal

Ultrasonic burst

Ultrasonicburst

tp

The distance is computed by measuring the propagation

time of the ultrasonic signal tP .


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The principle of measuring the azimuthof the beacon relative to the robot

L R

d2

d1

t1t2

a

The azimuth of the sound source is determined by

measuring the interaural time delay ITD

)arcsin( a

tc

=


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The Proposed Solution

The structure of the active beacons


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Structure of the Receiver Located on theRobot

A.M.DEMOD.

DTMFDECODER

BURSTDETECTOR

MCU

OMNIDIRECTIONALMICROPHONE

RADIOMODEM

A.M.DEMOD.

DTMFDECODER

OMNIDIRECTIONALMICROPHONE LEFT

OMNIDIRECTIONALMICROPHONE RIGHT

B.P. FILTER

B.P. FILTER

SQUAREWAVESHAPER

SQUAREWAVESHAPER

PRECEDENCEDETECTOR

UP/DOWNCOUNTER

MCU

REF. CLOCK

BEACON ID

STROBE


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Where Am I Going?The Problem of Decision in Robotic Systems

SENSORS

Internal representationof the environment

DECISION

GOALS

ACTIONS

An automated system is a decision and actionsystem.


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Objective of the Research

Development of a programming language forprogramming the decision in robotic systems

flexible enough to describe most of the situations

related to the navigation of an autonomous robotin a controlled environment, and simple enough to

be accessible to users with little or no technical

skills. We called this language RDPL - Robot Decision

Programming Language.


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The Proposed Solution

The interaction between the robot andthe environment can be described bysentences of the following type:

IF((condition1)&&(condition2)&&...&&(conditionN)) THEN MOVE_TO GOALk

IF((condition1)&&(condition2)&&...&&(con

ditionN)) THEN Activate_outputk

where (conditionj) is a logic

function of the input and output of the

system.


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RDPL - Robot DecisionProgramming Language

The proposed language can be classified amongrobot programming languages developed as

extensions of existing programming languages. It isderived from the standard IEC61131-3, intended for

programming the PLCs. RDPL is a compiled language, based on a reduced

set of primitives, with the following general syntax:

FNAMEdest, op1, op2, op3, op4


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Distinctive Features of RDPL

Inputs and outputs are distributed, being associatedwith sensors and actuators located (mainly) in the

smart environment.

A limited set of inputs is associated with a set of

voice commands, such as STOP, MOVE, LEFT,RIGHT. In this approach, the recognition of a voicecommand generates a transition of the associated

digital input. A special category of outputs is represented by the

motion commands:MOVE TRIGGER, GOAL_X,GOAL_Y, GOAL_HEADING, EDGE


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Structure of the Distributed Input-OutputSystem

RADIO MODEM

InputOutputModule(s)

Voice command

Sensor

Actuator

PROTOCOL

CONVERTER

RS-485 BUS

RS-232


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The Implementation of RDPL

SCAN INPUT

FETCH

EVALUATE

FUNCTION

INCREMENT PC

UPDATE

OUTPUT

RESET PC

LAST

FUNCTION?

NO

YES

PC - PROGRAM COUNTER


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How Should I Get There?

Controlling the motion of the robot tothe goal

It is assumed that the robots move in a fullyknown environment. Moreover, this

environment is manipulated by placing

special sensors and actuators intended forthe interaction with the robots.

Therefore, this research does not cover theproblems of map building and path

planning. It is limited to finding solutions

for defining and following paths.


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Following a path defined as a trail ofVirtual Pheromones

Any attempt to model the natural pheromonesshould address the following problems:

- Diffusion - is a process that creates spatial

gradients of the intensity of pheromones,detectable by the sensors.

- Evaporation decreases the intensity of the

pheromone source with the time.- Aggregation comes from the superposition of

the effects of multiple pheromone sources.


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The model of artificialpheromones]1,0[: +Rp

=

0

1)( 0

xp

xp Difusion

=

tptp 1)( 0 Evaporation

=

=

tdpP

N

k

kkR 11

1

0Aggregation


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Additional assumptions:

S1

S2

3

S4

Snd1

d2

dn

p1

p2

pn

P

Directive

sensitivity

=

=

N

k

kkR

dpP1

0 1

Time invariance

Differential sensing with two antennas


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Defining the path

a

(x ,y )R R

The map that embeds the information on the spatial

distribution of pheromones is stored in the memory of

a pheromone server, located in the environment.


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Computing the pheromone intensityfor a given posture of the robot

2

0

2

0 )()( yyxxdi ii +=

=

i

i

d

pp 10

=

i

ii

d

xx 0arcsin

+

=

==

2

1

2

1

sincosN

i

ii

N

i

iiR ppP


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Path following - The bio-mimeticapproach

IfPL and PR are the pheromone intensities detected by two antennas L(Left) and R (Right), the reference speeds for the drive wheels are:

=

||

|)|1(

RL

RL

L

PPK

PPKv

=

|)|1(

||

RL

RL

R

PPK

PPKv

for P >PL R

for P =PL R

for P


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Path Following - The FuzzyApproach

)()()( tPtPte RL =

)()()(' 1= kkk tetete

The FLC simultaneously generates references

for vL and vR, the speeds of the differential drive

wheels.


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Experiments with real robots

http://www.youtube.com/watch?v=0LJQmJS5ZdY

http://www.youtube.com/watch?v=GHBOP8HfJcI

http://www.youtube.com/watch?v=xUdYQMwD83s

http://www.youtube.com/watch?v=6UqSDp0GEzU


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Avoiding Obstacles

Objective of the research

Development of a reactive obstacle

avoidance algorithm compatible with lowcost sensors and with the limitations of

microcontrollers.


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The Bubble ReboundAlgorithm

A

B

Currentheading

-90o

+90o

0o

sonar_readings

12

3

4

-1-2

-3

-4

Defining the sensitivity bubbleand polar representation of the

information provided by sensors.


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The Bubble ReboundAlgorithm

START

ADJUST HEADING

TO GOAL

OBSTACLE?

OBSTACLE?

MOVE STRAIGHT

TO GOAL

GOAL

REACHED?

STOP

COMPUTE

NEW HEADING

ADJUST

MOTION

GOAL

VISIBLE?

KEEP MOVING

YES

YES

YES

YES

NO

NO

NO

NO

O1

S

H

V


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Computing the Rebound Angle

N

=

0

=

2,2

0

NNi

ii

=

=

=

2

2

2

2

N

Ni

i

N

Ni

ii

R

D

D

0 - angular pace of the distribution of sensors on

the circumference

Di - Distance reported by sensor i


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Experiments with real robots

Start Goal

Pioneer avoiding an obstacle


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Published Works Related to thisDissertation [1] Susnea I. Mitescu M. Microcontrollers in practiceISBN:

3540253017, Springer Verlag, 2005

[2] Susnea I. Vasiliu G. Filipescu A. Radaschin A., VirtualPheromones for Real-Time Control of Autonomous MobileRobots, in Studies of Informatics and Control, Vol 18, issue 3,

2009. [3] Susnea I . Vasiliu G, Filipescu A, Coman G., On the

Implementation of a Robotic Assistant for the Elderly. A NovelApproach, 7th WSEAS Int. Conf. on Computational, Iintelligence

Man-machine Systems and Cybernatics (CIMMACS '08), Cairo,Egipt, December 29-31, 2008, pp.215-220


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Published Works Related to thisDissertation [4] Susnea I, Filipescu A, Vasiliu G., Filipescu S., Path

Following, Real-time, Embedded Fuzzy Control of a MobilePlatform Wheeled Mobile Robot, IEEE International Conferenceon Automation and Logistics, ICAL 2008, 1-3 Sep., Qingdao,China, IEEE ICAL 2008 CD Proceedings, pp.91-96

[5] Susnea I, Vasiliu G, Filipescu A, Real-Time, EmbeddedFuzzy Control of the Pioneer3-DX Robot for Path Following, The12th WSEAS International Conference on SYSTEMS, Heraklion,Greece, July 22-24, 2008, pp.334-338


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Published Works Related to thisDissertation [6] Susnea I . Vasiliu G, Filipescu A, RFID Digital Pheromones

for Generating Stigmergic Behaviour to Autonomous MobileRobots, 4th WSEAS Int. Conf. on Dynamic Systems and Control(Control '08), CORFU ISLAND, GREECE, October 26-28, 2008,pp.20-24

[7] Susnea I., Vasiliu G., Filipescu A., Coman G., Radaschin A.,Real-Time Control of Autonomous Mobile Robots Using VirtualPheromones, The 7th ASCC Conference, Hong Kong 2009

[8] Susnea I., Vasiliu G., Filipescu A., Serbencu A., Radaschin

A., Virtual Pheromones to Control Mobile Robots. A NeuralNetwork Approach, The IEEE International Conference onAutomation and Logistics, ICAL 2009, Shenyang, China.


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Published Works Related to thisDissertation [9] Filipescu A, Susnea I, Stancu Al, Stamatescu G, Path

following, real-time, embedded fuzzy control of a mobileplatform pioneer 3-dx, 8th WSEAS International Conference onSystems Theory and Scientific Computation (ISTASC08),Rhodes (Rodos) Island, Greece, August 20-22, 2008, pp.334-335

[10] Filipescu A., Susnea I., Filipescu A., Stamatescu G.Distributed System of Mobile Platform Obstacle Avoidance andControl As Robotic Assistant for Disabled and Elderly, To bepresented at the 7th IEEE International Conference on Control &

Automation ICCA09, Christchurch, New Zealand, Dec. 2009 [11] Filipescu A., Susnea I., Filipescu S., Stamatescu G.,

Wheeled Mobile Robot Control Using Virtual Pheromones andNeural Networks, To be presented at the 7th IEEE International

Conference on Control & Automation ICCA09, Christchurch,New Zealand, Dec. 2009


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Conclusions

Some of the major fields of robot navigation:localization, decision, path following, andobstacle avoidance, have been addressed froman interdisciplinary perspective.

The proposed solutions have practicalapplications and may contribute to the evolutionof knowledge in the respective fields.

Some new research directions have beensuggested.

thesis abstract susnea

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