Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field

  • Mohamed Jasim Mohamed Department of Control and Systems Engineering/ University of Technology
  • Mustaffa Waad Abbas Department of Control and Systems Engineering/ University of Technology
Keywords: Mobile Robot, Local Path Planning, Obstacles Avoidance, Potential Field

Abstract

In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint repulsive force and the off-sensors attractive force. These secondary forces and modified primary forces are merged to overcomethe drawbacks like dead ends and U shape traps. The proposed algorithm acquirs information of unknown environment by collecting the readings of five infrared sensors with detecting range of 0.8 m. The proposed algorithm is applied on two different environments also it is compared with another algorithm. The simulation and experimental results confirm that the proposed algorithm always converges to the desired target. In addition, the performance of algorithm is well and meets the requirements in terms of saved time and computational resources.

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Published
2017-12-28
How to Cite
Mohamed, M., & Abbas, M. (2017). Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field. Al-Khwarizmi Engineering Journal, 9(1), 71-82. Retrieved from http://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/160
Section
Articles