This paper presents the development of a quadrotor unmanned aerial vehicle (UAV) that is capable of detecting and avoiding collision with obstacles through the implementation of Kalman filter-based multi-sensor fusion and cascaded PID position and velocity controllers. Sensor fusion of ultrasonic (US) and infrared (IR) sensors is performed to obtain a reliable range data for obstacle detection which then fed into collision avoidance controller (CAC) for generating necessary response in terms of attitude commands. Results showed that sensor fusion provided accurate range estimation by reducing noises and errors that were present in individual sensors measurements. Flight tests performed proved the capability of UAV to avoid collisions with the obstacle that was introduced to it during flight successfully.
