Analysis and Evaluation of Electronic System Architectures in Intelligent Robotics

Abstract

The architecture of electronic systems in intelligent robotics plays a fundamental role in improving accuracy, processing speed, reliability, and autonomous decision-making. In this study, five common architectures—centralized, distributed, hybrid, modular, and layered—are analyzed from the perspectives of complexity, reliability, response time, fault tolerance, energy consumption, and scalability. Data were extracted using comparative methods, graphical modeling, and performance criteria analysis. The results indicate that the centralized architecture has a simpler structure and lower cost but is more vulnerable to system failure. In contrast, distributed and layered architectures offer higher reliability and scalability, enabling parallel processing and big data management. The layered architecture, due to its combination of reactive and hierarchical features, provides a suitable balance between response speed and decision-making accuracy. Findings show that while more advanced architectures entail greater design complexity, they deliver superior performance in industrial applications, mobile robots, and autonomous systems. The results of this study can assist researchers and designers in selecting the most appropriate architecture for intelligent robotic systems.