Cover
Vol. 22 No. 1 (2026)

Published: June 15, 2026

Pages: 68-76

Original Article

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

Fatima H. Khayoun 1 Ammar A. Aldair 1 Ali A. Issa 2
1 Electrical Engineering Department, University of Basrah, Iraq
2 Medical Device Engineering, National University of Science and Technology, Dhi-Qar, Iraq
History
  • Received: February 2, 2024
  • Revised: March 25, 2024
  • Accepted: March 27, 2024
  • Available Online: June 15, 2026
DOI

https://doi.org/10.37917/ijeee.22.1.7

Abstract

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.

Keywords

References

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