Development of an Intelligent Sumo Robot based on Embedded Fuzzy Logic

Abstract

This paper presents the design and development of an intelligent sumo robot utilizing embedded fuzzy logic for real-time opponent detection and motion control. The system integrates analog infrared (IR) distance sensors and a fuzzy inference engine deployed on an Arduino Mega microcontroller to improve the robot’s responsiveness and adaptability in dynamic environments. Through sensor calibration and optimized placement, the robot accurately detects opponent positions across multiple zones. A fuzzy rule base interprets the continuous sensor inputs and generates smooth, context-aware motor responses. The system was evaluated through simulation in MATLAB and embedded implementation, with test scenarios involving five fixed opponent positions and gradually varying inputs. Comparative results show that the fuzzy controller significantly outperforms traditional if-else logic, producing smoother motion, better coverage, and more reliable decision-making, with error values between MATLAB and Arduino outputs as low as 0.22%. The embedded fuzzy logic system closely replicates simulated behavior, validating its real-time feasibility on low-cost hardware. This approach demonstrates a scalable and effective solution for intelligent mobile robotics.