Intelligent Obstacle Avoidance Controller for QBot2

This paper describes the design process and the steps involved in the implementation of a fuzzy logic-based controller for autonomous navigation of an educational robot called Qbot2. The differential-driven robot is equipped with three ultrasonic sensors (SRF-04) mounted on the front bumper and DC motors with built-in encoders and current sensors. The controller takes the inputs from three ultrasonic sensors and generates the speed commands to avoid any obstacle in its path. PCB is designed to process all the data from the sensors and direct the signal to the motors via motor driver circuits. The low-level implementation of the hurdle avoidance controller is implemented using an inexpensive Arduino UNO in real-time. The controller performance is validated through an experimental run. The designed platform can be used to implement various fuzzy inference systems in real-time and hence can be utilized as laboratory work for testing soft computing algorithms on mobile robotics.