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Using Genetic Algorithm to Learn Gaits for an Eight-Legged Robot.

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Title: Using Genetic Algorithm to Learn Gaits for an Eight-Legged Robot.
Authors: H. Khayoun, Fatima1 fatimaahameed98@gmail.com, A. Aldair, Ammar1, A. Issa, Ali2
Source: Iraqi Journal for Electrical & Electronic Engineering. Jun2026, Vol. 22 Issue 1, p68-76. 9p.
Subjects: Genetic algorithms, PID controllers, Dynamic stability, Robots, Robot control systems, Simulation software, MatLab (Computer software)
Abstract (English): Legged robots offer several benefits over standard wheeled vehicles when operating in tough and unstructured terrain. These benefits include increased speed, improved fuel efficiency, increased mobility, improved isolation from uneven terrain, and reduced environmental harm. This paper presents the modeling of an eight-legged robot that was simulated using Simscape Multibody toolbox in MATLAB, where the robot consists of eight legs, and each leg contains three links, and each link contains a PID controller, meaning it contains a total of 24 controllers. This controller was used to control the robot’s gait and make it more stable. To obtain the optimal and most stable gait for the robot and to travel a longer distance, an optimization algorithm should be used, so that in this paper the genetic algorithm (GA) is used to obtain those points. To test the robustness of the proposed controllers, different weights are added (1 kg and 3 kg) as a load to the body of the legged robot, the obtained results show the efficiency of the proposed controllers. [ABSTRACT FROM AUTHOR]
Abstract (Arabic): تركز هذه المقالة على استخدام خوارزمية جينية (GA) لتحسين نمط مشي روبوت ذو ثمانية أرجل، تم تصميمه ومحاكاته باستخدام صندوق أدوات Simscape Multibody في برنامج MATLAB. يمتلك الروبوت ثمانية أرجل، كل منها يحتوي على ثلاثة مفاصل يتم التحكم بها بواسطة متحكمات تناسبية-تكاملية-تفاضلية (PID)، ليصل مجموع المتحكمات إلى 24 متحكمًا. تُستخدم الخوارزمية الجينية لإيجاد نمط المشي الأكثر ثباتًا وكفاءة من خلال تحسين نقاط المسار للمفاصل، بهدف تعظيم المسافة المقطوعة مع الحفاظ على الاستقرار. تختبر الدراسة متانة نمط المشي المحسن بإضافة أوزان قدرها 1 كيلوجرام و3 كيلوجرامات إلى جذع الروبوت، مما يوضح أن المتحكم المحسن بواسطة الخوارزمية الجينية يحافظ على الاستقرار والحركة الفعالة تحت هذه الاضطرابات. تسهم هذه الدراسة في تطوير روبوتات ذات أرجل قادرة على التنقل في تضاريس معقدة مع تحسين الاستقرار والكفاءة. [Extracted from the article]
Copyright of Iraqi Journal for Electrical & Electronic Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Using Genetic Algorithm to Learn Gaits for an Eight-Legged Robot.
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  Data: <searchLink fieldCode="AR" term="%22H%2E+Khayoun%2C+Fatima%22">H. Khayoun, Fatima</searchLink><relatesTo>1</relatesTo><i> fatimaahameed98@gmail.com</i><br /><searchLink fieldCode="AR" term="%22A%2E+Aldair%2C+Ammar%22">A. Aldair, Ammar</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22A%2E+Issa%2C+Ali%22">A. Issa, Ali</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Iraqi+Journal+for+Electrical+%26+Electronic+Engineering%22">Iraqi Journal for Electrical & Electronic Engineering</searchLink>. Jun2026, Vol. 22 Issue 1, p68-76. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22PID+controllers%22">PID controllers</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+stability%22">Dynamic stability</searchLink><br /><searchLink fieldCode="DE" term="%22Robots%22">Robots</searchLink><br /><searchLink fieldCode="DE" term="%22Robot+control+systems%22">Robot control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+software%22">Simulation software</searchLink><br /><searchLink fieldCode="DE" term="%22MatLab+%28Computer+software%29%22">MatLab (Computer software)</searchLink>
– Name: Abstract
  Label: Abstract (English)
  Group: Ab
  Data: Legged robots offer several benefits over standard wheeled vehicles when operating in tough and unstructured terrain. These benefits include increased speed, improved fuel efficiency, increased mobility, improved isolation from uneven terrain, and reduced environmental harm. This paper presents the modeling of an eight-legged robot that was simulated using Simscape Multibody toolbox in MATLAB, where the robot consists of eight legs, and each leg contains three links, and each link contains a PID controller, meaning it contains a total of 24 controllers. This controller was used to control the robot’s gait and make it more stable. To obtain the optimal and most stable gait for the robot and to travel a longer distance, an optimization algorithm should be used, so that in this paper the genetic algorithm (GA) is used to obtain those points. To test the robustness of the proposed controllers, different weights are added (1 kg and 3 kg) as a load to the body of the legged robot, the obtained results show the efficiency of the proposed controllers. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label: Abstract (Arabic)
  Group: Ab
  Data: تركز هذه المقالة على استخدام خوارزمية جينية (GA) لتحسين نمط مشي روبوت ذو ثمانية أرجل، تم تصميمه ومحاكاته باستخدام صندوق أدوات Simscape Multibody في برنامج MATLAB. يمتلك الروبوت ثمانية أرجل، كل منها يحتوي على ثلاثة مفاصل يتم التحكم بها بواسطة متحكمات تناسبية-تكاملية-تفاضلية (PID)، ليصل مجموع المتحكمات إلى 24 متحكمًا. تُستخدم الخوارزمية الجينية لإيجاد نمط المشي الأكثر ثباتًا وكفاءة من خلال تحسين نقاط المسار للمفاصل، بهدف تعظيم المسافة المقطوعة مع الحفاظ على الاستقرار. تختبر الدراسة متانة نمط المشي المحسن بإضافة أوزان قدرها 1 كيلوجرام و3 كيلوجرامات إلى جذع الروبوت، مما يوضح أن المتحكم المحسن بواسطة الخوارزمية الجينية يحافظ على الاستقرار والحركة الفعالة تحت هذه الاضطرابات. تسهم هذه الدراسة في تطوير روبوتات ذات أرجل قادرة على التنقل في تضاريس معقدة مع تحسين الاستقرار والكفاءة. [Extracted from the article]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Iraqi Journal for Electrical & Electronic Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.37917/ijeee.22.1.7
    Languages:
      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 68
    Subjects:
      – SubjectFull: Genetic algorithms
        Type: general
      – SubjectFull: PID controllers
        Type: general
      – SubjectFull: Dynamic stability
        Type: general
      – SubjectFull: Robots
        Type: general
      – SubjectFull: Robot control systems
        Type: general
      – SubjectFull: Simulation software
        Type: general
      – SubjectFull: MatLab (Computer software)
        Type: general
    Titles:
      – TitleFull: Using Genetic Algorithm to Learn Gaits for an Eight-Legged Robot.
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            NameFull: H. Khayoun, Fatima
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            NameFull: A. Aldair, Ammar
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            NameFull: A. Issa, Ali
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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