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