Optic Flow-Based Reactive Collision Prevention for MAVs Using the Fictitious Obstacle Hypothesis

Optical flow sensors and optical flow divergence (OFD) have offered partial solutions for obstacle avoidance, landing, and perching with micro aerial vehicles. Theoretically, OFD can indicate the risk of collision, providing that the sensors' field of view is bounded within a single flat surface on the obstacle. However, in the real world, directly measuring the risk of collision with OFD generates false alarms due to rapidly changing speeds and irregular surroundings. In this letter, we present a new obstacle detection strategy based on an extended Kalman filter (EKF) combining the OFD with inertial sensing. The introduction of a fictitious obstacle hypothesis and the use of the EKF estimates enable us to differentiate the surrounding-generated OFD from the OFD caused by the actual obstacle. An embedded constant zero-OFD controller is then used for post-detection emergency deceleration. The ultra-light OFD estimation and control system, with a mass of 20 g, estimates OFD at 160 Hz. The system was validated on a 158 g mini quadrotor in both laboratory and field tests. Experimental results illustrate that the presented system can achieve accurate obstacle detection, near-obstacle distance estimation, and controlled deceleration to prevent collisions. 1 Video attachment: https://youtu.be/yIyYHYN0jOw.