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UNIVERSITI PUTRA MALAYSIA
GENETIC ALGORITHM BASED MASS DISTRIBUTION OPTIMIZATION OF QUADRUPED LEG FOR WALKING
PERFORMANCE ENHANCEMENT
LOO SHING YAN
ITMA 2013 5
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GENETIC ALGORITHM BASED MASS DISTRIBUTION
OPTIMIZATION OF QUADRUPED LEG FOR WALKING
PERFORMANCE ENHANCEMENT
By
LOO SHING YAN
Thesis Submitted to the School of Graduate Studies, Universiti Putra
Malaysia, in Fulfilment of the Requirements for the Degree of Master of
Science
December 2013
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COPYRIGHT
All material contained within the thesis, including without limitation text, logos, icons,
photographs and all other artworks, is copyright material of Universiti Putra Malaysia
unless otherwise stated. Use may be made of any material contained within the thesis for
non-commercial purposes from the copyright holder. Commercial use of material may
only be made with the express, prior, written permission of Universiti Putra Malaysia
Copyright © Universiti Putra Malaysia
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DEDICATION
This thesis is dedicated to my parents
And my wife.
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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of
the requirement for the degree of Master of Science
GENETIC ALGORITHM BASED MASS DISTRIBUTION OPTIMIZATION OF
QUADRUPED LEG ROBOT FOR WALKING PERFORMANCE
ENHANCEMENT
By
LOO SHING YAN
December 2013
Chair: Assoc. Prof. Tang Sai Hong, PhD
Faculty: Institute of Advanced Technology
In previous research works, legged robots are typically induce stable locomotion in active
compliance and passive compliance approaches. In order to realize active compliance
locomotion, the detail studies on robot hardware and environmental factors are required.
Hence, a controller is designed to tailor for specific environment. Therefore, designing an
all-rounded controller is extremely challenging. On the contrary, passive compliance
locomotion relies on the advantage of its own body. Passive compliance mechanism that
currently adopted in legged robot such as spring-damper mechanisms, flexible links and
components, and adjustable joint stiffness are used to store and release the impact from
the environment. Therefore, stable locomotion can be acquired. However, morphological
effect on locomotion is an important issue to study.
In this thesis, the study is focused on another approach that utilize the advantage of the
robot body to achieve stable locomotion, which is mass distribution of the robot. Genetic
algorithm is used to search for the optimal mass distribution that carried out the farthest
walking distance on various terrains. In this experiment, quadruped is used to perform
repetition tests in simulated environment. In the conditions of fixed walking cycle, preset
walking pattern and limited torque generation in actuators, genetic algorithm is adopted
to optimize the walking distance of the robot by varying the masses of torso, upper limb
and lower limb, ranging from 0.01kg to 5kg. The predefined joint trajectories are
generated using Matsuoka neural oscillator network as the central pattern generator of the
quadruped. Open Dynamics Engine is adopted for legged robot simulation. The robot is
programmed to walk on flat terrain, inclined terrains of 0.1 radian and 0.15 radian, and
declined terrains of 0.1 radian and 0.15 radian with different mass distribution, in which
the value of the masses (torso, upper limb, and lower limb) are stored in the chromosomes.
Thus, it allows genetic operators to take control of the information for optimization.
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According to the experiment results, it shows that the mass distribution of the robot
substantially affect the walking distance of the robot. It also demonstrates that genetic
algorithm successfully implemented to enhance walking performance by maximizing the
walking distance in prefix conditions. It also leads to a conclusion that intelligently
manipulation of mass distribution can extend walking distance significantly.
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Abstract tesis yang dikemukakan kepada Senat Universiti Putra Malaysia
sebagai memenuhi keperluan untuk ijazah Master Sains
ALGORITMA GENETIK BERASASKAN PENGOPTIMUMAN JISIM
PENGAGIHAN ROBOT KUADRUPED UNTUK PENINGKATAN PRESTASI
PERJALANAN
Oleh
LOO SHING YAN
Disember 2013
Pengerusi: Assoc. Prof. Tang Sai Hong, PhD
Fakulti: Institut Teknologi Maju
Dalam karya-karya penyelidikan sebelumnya, robot berkaki biasanya menjanakan
pergerakan stabil dengan pematuhan aktif dan pematuhan pasif. Dalam usaha untuk
merealisasikan pergerakan pematuhan aktif, kajian terperinci mengenai perkakasan robot
dan faktor-faktor alam sekitar yang diperlukan untuk mereka bentuk pengawal yang
tertentu untuk robot berkaki terhadap alam sekitar tertentu. Oleh itu, reka bentuk pengawal
sempurna adalah amat mencabar. Sebaliknya, pematuhan pergerakan pasif bergantung
kepada kelebihan badan sendiri. Pematuhan mekanisme pasif yang kini digunakan dalam
robot berkaki seperti pegas-peredam mekanisme, rangkaian dan komponen yang fleksibel,
dan kekakuan laras sendi digunakan untuk menyimpan dan melepaskan tenaga dari
persekitaran. Oleh itu, pergerakan stabil boleh diperoleh. Walau bagaimanapun, kesan
morfologi pada pergerakan merupakan satu isu penting untuk belajar.
Dalam tesis ini, kajian ini memberi tumpuan kepada penggunaan kelebihan badan robot
untuk mencapai pergerakan stabil, iaitu pengagihan jisim robot. Algoritma genetik
digunakan untuk mencari pengagihan jisim optimum yang membenarkan jarak berjalan
kaki yang paling jauh pada pelbagai keadaan jalan. Dalam eksperimen ini, berkaki empat
digunakan untuk melakukan ujian ulangan dalam persekitaran simulasi. Dalam keadaan
persekitaran, penjanaan corak berjalan yang tetap, dan tork motor yang terhad, algoritma
genetik telah digunakan untuk mengoptimumkan jarak berjalan kaki robot dengan
pengubahan jisim tubuh, anggota atas kaki, dan anggota bawah kaki dari 0.01kg ke 5kg.
Trajektori diperoleh dari pengayun rangkaian saraf Matsuoka digunakan sebagai penjana
corak robot berkaki. Open Dynamics Engine dipakaikan untuk simulasi robot berkaki.
Robot yang diprogramkan untuk berjalan di atas kawasan yang rata, naik cerun pada sudut
0.1 radian dan 0.15 radian, dan turun cerun pada sudut 0.1 radian dan 0.15 radian dengan
pengagihan jisim yang berbeza, di mana nilai jisim-jisimnya (tubuh, anggota atas kaki,
dan anggota bawah kaki) disimpan dalam kromosom. Oleh itu, ia membolehkan operator
genetik untuk mengawal maklumat bagi process pengoptimuman.
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Menurut keputusan eksperimen, ia menunjukkan bahawa pengagihan jisim robot berkesan
untuk memanjangkan jarak berjalan kaki robot. Ia juga menunjukkan bahawa algoritma
genetik berjaya dilaksanakan untuk meningkatkan prestasi berjalan dengan
memaksimumkan jarak berjalan kaki dalam keadaan yang ditetapkan. Kesimpulannya,
mengawal pengagihan jisim secara bijak membolehkan jarak perjalanan robot
dipanjangkan dengan ketara.
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ACKNOWLEDGEMENTS
First of all, I would like to express my deepest gratitude to Assoc. Prof Dr. Tang Sai Hong.
Without his help, I would not have finished my work on time. Thanks for staying with me,
and provide me a lot of guidance during my hard times. Your advices are utmost
appreciated.
Second of all, I would like to share my gratefulness with my co-supervisor, Dr. Syamsiah
Binti Mashohor. Your artificial intelligence (AI) course are so much inspiring. It allows
me to refine my study. Therefore, without your help, the topic of research would never
come across my mind.
Millions of thanks to my lovely wife. She is willing to listen to my problems, share my
burdens, and take care of me. We are always exchanging ideas whenever I feel lost. You
are always there for me.
Lastly, thanks to my parents for the financial support and courage to further my study.
Also my friends who were helped me around. Without their help, I would not have attained
my achievements today.
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I certify that an Examination Committee has met on 23/12/2013 to conduct the final
examination of Loo Shing Yan on his Master of Science thesis entitled “GENETIC
ALGORITHM BASED MASS DISTRIBUTION OF QUADRUPED FOR WALKING
PERFORMANCE ENHANCEMENT" in accordance with the Universities and
University Colledges Act 1971 and Constitution of the Universiti Putra Malaysia [P. U.
(A) 106] 15 march 1998. The Committee recommends that the candidate be awarded the
Master of Science.
Members of the Thesis Examination Committee were as follows:
Abd. Rahman bin Ramli, PhD
Associate Professor
Faculty of Engineering
Universiti Putra Malaysia
(Chairman)
Mohd Khairol Anuar bin Mohd Ariffin, PhD
Associate Professor
Faculty of Engineering
Universiti Putra Malaysia
(Internal Examiner)
Suhaidi bin Shafie, PhD
Faculty of Engineering
Universiti Putra Malaysia
(Internal Examiner)
Shamsudin Hj Mohd Amin, PhD
Professor
Faculty of Electrical Engineering
Universiti Teknologi Malaysia
(External Examiner)
________________________________
Zulkarnain Zainal, PhD
Deputy Dean
School of Graduate Studies
Universiti Putra Malaysia
Date:
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This thesis was submitted to the Senate of Universiti Putra Malaysia and has been accepted
as fulfilment of the requirement for the degree of Master of Science. The members of the
Supervisory Committee were as follows:
Tang Sai Hong, PhD
Associate Professor
Faculty of Engineering
University Putra Malaysia
(Chairman)
Syamsiah Binti Mashohor, PhD
Senior Lecturer
Faculty of Engineering
University Putra Malaysia
(Member)
BUJANG BIN KIM HUAT, PhD
Dean
School of Graduate Studies
Universiti Putra Malaysia
Date:
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DECLARATION
Declaration by graduate student
I hereby confirm that:
This thesis is my original work; Quotation, illustrations and citations have been duly referenced; This tesis has not been submitted previously or concurrently fot any other degree at
any other institutions;
Intellectual property from the thsis and copyright of thesis are fully-owned by Universiti Putra Malaysia, as according to the Universiti Putra Malaysia (Research)
Rules 2012;
Written permission must be obtained from supervisor and office of Deputy Vice-Chancellor (Research and Innovation) before thesis is published (in the form of
written, printed or in electronic form) including book, journals, modules, proceedings,
popular writings, seminar papers, manuscripts, posters, reports, lecture notes, learning
modules or any other materials as stated in the Universiti Putra Malaysia (Research)
Rules 2012;
There is no plagiarism or data falsification/fabrication in the thesis, and scholarly integrity is upheld as according to the Universiti Putra Malaysia (Graduate Studies)
Rules 2003 (Revision 2012-2013) and the Universiti Putra Malaysia (Research) Rules
2012. The thesis has undergone plagiarism detection software.
Signature: _________________________________ Date: 23 December 2013
Name and Matric No.: _____________________________________________________
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Declaration by members of Supervisory Committee
This is to confirm that:
The research conducted and the writing of the thesis was under our supervision; Supervision responsibilities as stated in the Universiti Putra Malaysia (Graduate
Studies) Rules 2003 (Revision 2012-2013) are adhered to.
Signature: __________________ Signature: __________________
Name of Name of
Chairman of Member of
Supervisory Supervisory
Committee: __________________ Committee: __________________
Signature: __________________ Signature: __________________
Name of Name of
Member of Member of
Supervisory Supervisory
Committee: __________________ Committee: __________________
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TABLE OF CONTENTS
Page ABSTRACT iii
ABSTRAK v
ACKNOWLEDGEMENTS vii
APPROVAL viii
DECLARATION x
TABLE OF CONTENT xi
LIST OF TABLES xiv
LIST OF FIGURES xvi
LIST OF ABBREVIATIONS xviii
CHAPTERS
1 INTRODUCTION 1 1.1 Preface 1 1.2 Problem statement 2 1.3 Research objectives 2 1.4 Scope of the study 3 1.5 Organization of the chapters 3
2 LITERATURE REVIEW 5 2.1 Introduction 5 2.2 Active compliance and passive compliance mechanisms 6
2.2.1 Active compliance mechanism 6 2.2.2 Passive compliance mechanism 7
2.3 Morphological effect on walking performance 9 2.4 Artificial intelligence as optimization tool 10
2.4.1 Optimization of controller 11 2.4.2 Optimization of morphology 12
2.5 Basic motion generators 13 2.6 Simulator engine 17
2.6.1 Physical experiment against simulated experiment 17 2.6.2 Types of simulator engine 18
2.7 Summary 19
3 METHODOLOGY 21 3.1 Introduction 21 3.2 Experimental setup 25
3.2.1 Matsuoka neural oscillator network settings 25 3.2.2 Terrain setup 27 3.2.3 Genetic algorithm setup 30 3.2.4 Legged robot specification 32 3.2.5 Open Dynamics Engine as legged robot simulator 33
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4 RESULTS AND DISCUSSION 35 4.1 Introduction 35 4.2 Results 36
4.2.1 Reference joint trajectories generated using 36 Matsuoka neural oscillator network
4.2.2 Preliminary results 37 4.2.3 Optimized mass distribution and walking results 37
using GA on flat terrain
4.2.4 Optimized mass distribution and walking results 39 using GA on sloping terrains
4.3 Discussion 47 4.3.1 Obtained results 48 4.3.2 Comparison with previously done experiments 51
5 CONCLUSION 55 5.1 Conclusion 55 5.2 Major contribution 55 5.3 Limitation 56 5.4 Future work 56
REFERENCES 58
APPENDICES 64
BIODATA OF STUDENT 94
LIST OF PUBLICATIONS 95
GENETIC ALGORITHM BASED MASS DISTRIBUTIONOPTIMIZATION OF QUADRUPED LEG FOR WALKINGPERFORMANCE ENHANCEMENTAbstractTABLE OF CONTENTSREFERENCESAPPENDICES