A Novel Color-Guided Navigation Framework for Autonomous Robots Using Sensor Fusion

Abstract

Reliable indoor navigation for mobile robots in industrial environments remains a challenging task due to the limitations of conventional control methods. Many existing systems depend on open-loop motor control or basic proximity sensors, which often lead to cumulative positioning errors, wheel slippage on smooth surfaces, and the inability to verify actual position against planned coordinates. To overcome these issues, this work presents a color-guided autonomous rover that integrates sensor fusion with an intelligent navigation approach to achieve accurate localization within a structured grid environment. The system is built around an ESP32 controller and incorporates an MPU6050 inertial measurement unit along with wheel encoders to enable closed-loop PID control, allowing continuous correction of motion deviations for precise linear and rotational movements. A dual I2C communication architecture is implemented to separate high-frequency motion sensing from color detection operations carried out by the TCS34725 sensor, thereby improving processing efficiency. The navigation mechanism is driven by a custom algorithm that converts grid-based target positions into directional commands and distance measures. At each designated node, the rover validates its position using predefined color markers embedded in the grid layout. Additionally, a WebSocketenabled interface supports both manual adjustment and autonomous operation, enhancing system flexibility. Experimental results indicate that the integration of inertial feedback significantly reduces drift compared to traditional approaches, demonstrating a reliable and intelligent solution for precision-oriented indoor robotic navigation.