Sensor based collision avoidance system for the walking machine ALDURO [Elektronische Ressource] / von Jorge Audrin Morgado de Gois

Informations

• Publié par: universitat_duisburg-essen
• Publié le: 01 janvier 2005
• Nombre de lectures: 23
• Langue: Deutsch
• Poids de l'ouvrage: 2 Mo

Extrait

Sensor-based Collision Avoidance System
for the Walking Machine ALDURO


Von der Fakultät für Ingenieurwissenschaften, Abteilung Maschinenbau der
Universität Duisburg-Essen
zur Erlangung des akademischen Grades



DOKTOR-INGENIEUR



genehmigte Dissertation



von


Jorge Audrin Morgado de Gois
aus
Rio de Janeiro - Brasilien




Referent: Prof. Dr.-Ing. habil. Dr. h.c. Manfred Hiller
Korreferenten: Prof. Dr.-Ing. Andrés Kecskeméthy
Prof. Dr.-Ing. Max Suell Dutra

Tag der mündlichen Prüfung: 26.10.2005
II

Table of Contents



1 Introduction 1
1.1 Problem Definition .................................................................................................3
1.2 Literature Review ...................................................................................................5
1.3 Goals and Organization of this Work ......................................................................9
2 Sensing Systems 12
2.1 Information Structure............................................................................................12
2.2 Sensing .................................................................................................................14
2.2.1 Virtual Sensor and Perception .......................................................................14
2.2.2 Error, Uncertainty and Imprecision................................................................16
2.3 Sensor Principles ..................................................................................................17
2.4 Sensor Systems for Distance Measurement ...........................................................19
2.4.1 Ultrasonic Sensors.........................................................................................20
2.4.2 Laser Range Finder .......................................................................................21
2.4.3 Radar ............................................................................................................21
2.5 Sensor Selection ...................................................................................................21
3 Overview on Fuzzy Logic 24
3.1 Classical Sets........................................................................................................24
3.2 Fuzzy Sets ............................................................................................................25
3.2.1 Fuzzy Set Theory versus Probability Theory .................................................26
3.2.2 Basic Definitions and Terminology ...............................................................27
3.2.3 Operation on Fuzzy Sets................................................................................27
3.2.4 Triangular Norms and Co-norms ...................................................................28
3.3 Fuzzy Relations ....................................................................................................32
3.4 Approximate Reasoning........................................................................................33
3.4.1 Inference Rules .............................................................................................34 III
4 Data Fusion 35
4.1 Single Sensor and Multiple Sensors Fusion...........................................................35
4.2 Data Fusion System ..............................................................................................38
4.2.1 Bayesian approach ........................................................................................39
4.2.2 Dempster-Shafer Approach ...........................................................................41
4.2.3 Fuzzy logic ...................................................................................................44
4.2.4 Sensor fusion by learning ..............................................................................45
4.3 Analysis aiming at ALDURO ...............................................................................46
5 The Collision Avoidance System 48
5.1 Inverse Sensor Model ...........................................................................................48
5.1.1 Measurement Uncertainty .............................................................................50
5.1.2 Fuzzification .................................................................................................52
5.1.3 Common Internal Representation ..................................................................56
5.1.4 Topographical Representation .......................................................................58
5.2 Fusion by TSK (Takagi-Sugeno-Kang System).....................................................60
5.2.1 Partitioning ...................................................................................................62
5.2.2 Optimization .................................................................................................65
5.2.3 Map Motion ..................................................................................................67
5.3 Navigation ............................................................................................................70
6 Realization 76
6.1 Selection of Ultrasonic Range Finder ....................................................................76
6.2 Interface................................................................................................................80
6.2.1 The Bus.........................................................................................................80
6.2.2 The Microcontroller ......................................................................................81
6.2.3 The Software Platform ..................................................................................83
6.3 Sensors’ Placement ...............................................................................................84
7 Tests and Results 90
7.1 Simulation Tests ...................................................................................................90
7.2 Static Tests ...........................................................................................................93
7.3 Tests with Small Mobile Robot.............................................................................98
7.4 Tests with the Leg-Test-Stand.............................................................................100 IV
8 Conclusions and Future Works 105
8.1 Conclusions ........................................................................................................105
8.2 Future Works......................................................................................................107
Appendix 109
A Technical Data of the Hardware ................................................................................109
A.1 SRF08.............................................................................................................109
A.2 I2C Bus...........................................................................................................113
B Recursive Least-Squares Method for System Identification .......................................115
References 120
Curriculum Vitae 131
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g
V

List of Symbols

In this list, the symbol # will be used as a dummy variable to indicate indexes and references
to other symbols.
μ Membership Function of set # #
T-Norm (Triangular Norm)
S-norm (Triangular Co-Norm)
c(#) Complement of set #
Therefore (first published in 1659 in the original German edition of Teusche
Algebra by Johann Rahn)
p(# | #’) Conditional probability density function of event # given the event #’
p (#|#’,#”) Joint conditional probability density function of event # given events #’ and #” joint
Occ Occupancy state Occupied
Emp Occupancy state Empty
m(#) Certainty values of proposition #
Dempster’s rule of combination
Confidence in map estimation by a neural network
Adiabatic constant for an ideal gas
Gas constant R
M Gas molecular mass
T Actual temperature a
T Calibration temperature c
I Intensity of pulse at distance # #
G Polar gain function of sensor receiver
r Range Q
e
q
b
a
a
VI
Azimuth angle
Maximal azimuth angle max
Rotation angle
d Measured distance
Range measurement error
L Maximal setup range
ˆG Approximated gain function
S Set of points in sensor workspace
S Projection of S onto XY plane xy
g(#) Approximation polynomial for the membership as function of height #
w Firing rate of rule # #
W Normalized firing rate of rule # #
f Output function of rule # #
C Cell of position (i, j) ij
Q Node of position (i, j) ij
N Number of measurements considered
P Design Matrix
Parameters Set
Parameter of output function f # #
K Reference frame #
# Relative to the grid reference system G
# Relative to the quasi-global reference system Q
# Relative to the platform fixed reference system P
M Map in reference system # #
h Maxima