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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.