An Extensible Intelligent Simulation System for Robot Path Planning in Wireless Sensor Networks

Abdulaziz Shehsb; Abdelhady Naguib; Abdelaziz Abohamama; Ahmed Elashry

doi:10.48161/qaj.v6n1a2235

Authors

Abdulaziz Shehab Department of Information Systems, College of Computer and Information Sciences, Jouf University, Sakaka 72388, Saudi Arabia; Department of Information Systems, Mansoura University, Mansoura 35516, Egypt; https://orcid.org/0000-0001-8610-7172
Abdelhady Naguib Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72388, Saudi Arabia; Department of Systems and Computers Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11884, Egypt; https://orcid.org/0000-0001-5220-6789
A. S. Abohamama Department of Computer Science, Mansoura University, Mansoura 35516, Egypt; Department of Computer Science, Arab East Colleges, Riyadh 53354, Saudi Arabia; https://orcid.org/0000-0002-8658-8428
Ahmed Elashry Faculty of Computer Studies, Arab Open University, Riyadh 13311, Saudi Arabia; Information Systems Department, computers and information Faculty, Kafr El-Sheikh University, Kafr El-Sheikh 33516, Egypt. https://orcid.org/0000-0001-6618-0479

DOI:

https://doi.org/10.48161/qaj.v6n1a2235

Keywords:

Bézier curves, genetic algorithm (GA), graphical user interface (GUI), robot path planning, trajectory simulation, scenario generation, WSN localization.

Abstract

Optimizing robot trajectories in dynamic and complex environments remains a significant challenge, particularly within wireless sensor networks (WSNs), where many existing simulation tools rely on predefined and inflexible scenarios. This paper presents an extensible graphical user interface (GUI)–based simulation system that integrates robot animation and scenario generation within a unified framework. The proposed system adopts a modular, plugin-based architecture that enables the seamless incorporation of diverse path-planning and trajectory optimization models without modifying the core infrastructure. In addition, an intelligent path-planning approach based on a Genetic Algorithm enhanced with Bézier curve modeling is integrated to support smooth and collision-free robot navigation in dynamic environments. Experimental evaluation demonstrates that the proposed framework provides an effective, scalable, and adaptable platform for conducting reproducible robot trajectory simulations in both research-oriented and practical applications. Overall, the proposed GUI-based and modular simulation framework provides a flexible, extensible, and reproducible platform for evaluating intelligent robot trajectory planning in dynamic WSN environments.

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