Cover
Vol. 21 No. 1 (2025)

Published: September 19, 2025

Pages: 199-209

Original Article

Mobile Robot Navigation with Obstacles Avoidance by Witch of Agnesi Algorithm with Minimum Power

Bayadir A. Issa 1 Hayder D. Almukhtar Qabeela Q. Thabit 2 Mofeed T. Rashid 3
1Electrical Engineering Techniques, Southern Technical University, Basrah, Iraq
2Basrah Education Directorate, Ministry of Education, Iraq
3Electrical Engineering Department, University of Basrah, Basrah, Iraq
History
  • Received: April 24, 2024
  • Revised: July 7, 2024
  • Accepted: July 19, 2024
  • Available Online: February 4, 2025
DOI

https://doi.org/10.37917/ijeee.21.1.20

Abstract

Obstacle avoidance in mobile robot path planning represents an exciting field of robotics systems. There are numerous algorithms available, each with its own set of features. In this paper a Witch of Agnesi curve algorithm is proposed to prevent a collision by the mobile robot’s orientation beyond the obstacles which represents an important problem in path planning, further, to achieve a minimum arrival time by following the shortest path which leads to minimizing power loss. The proposed approach considers the mobile robot’s platform equipped with the LIDAR 360o sensor to detect obstacle positions in any environment of the mobile robot. Obstacles detected in the sensing range of the mobile robot are dealt with by using the Witch of Agnesi curve algorithm, this establishes the obstacle’s apparent vertices’ virtual minimum bounding circle with minimum error. Several Scenarios are implemented and considered based on the identification of obstacles in the mobile robot environment. The proposed system has been simulated by the V-REP platform by designing several scenarios that emulate the behavior of the robot during the path planning model. The simulation and experimental results show the optimal performance of the mobile robot during navigation is obtained as compared to the other methods with minimum power loss and also with minimum error. It’s given 96.3 percent in terms of the average of the total path while the Bezier algorithm gave 94.67 percent. While in experimental results the proposed algorithm gave 93.45 and the Bezier algorithm gave 92.19 percent.

Keywords

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