An Intelligent Drone System to Automate the Avoidance of Collison using AI and Computer Vision Techniques


Steven Zhang1 and Yu Sun2, 1USA, 2California State Polytechnic University, USA


People love to fly drones, but unfortunately many end up crashing or losing them. As the technology of flying drones improves, more people are getting involved. With the number of users increasing, people find that flying drones with sensors is safer because it can automatically avoid problems, but such drones are expensive. This paper describes an inexpensive UAV (unmanned aerial vehicle) system that eliminates the need for sensors and uses only the camera to avoid collisions. This program helps avoid drone crashes and losses. We used the Tello Education drone as our testing drone, which is only outfitted with a camera. Using the camera feed and transmitting that data to the program, the program will then give commands to the drone to avoid collisions.


Memory leak, Resource table entry utilization, Correlation coefficient, Time Sequence monotonicity, Machine Learning.

Full Text  Volume 11, Number 14