Vision systems in drones, specifically Unmanned Aerial Vehicles (UAV) are currently used for retrieving real-time video of the area to fly over, nevertheless commercially there are no identification nor control applications for this type of aircrafts. Some existing technologies for trajectory generation are based on cubic polynomials and Bezier curves [5] but this paper presents the implementation of an optical flow algorithm that assures to track and control the trajectory in a quadrotor drone in real time, determining the distance between the drone and a certain objective as well as the speed calculation and its displacement direction by the means of the implementation of the Lucas-Kanade (LK) algorithm. The core purpose of this paper is to achieve a low-cost and faster (due to the UAV's dynamics) solution besides the implementation of a Global Positioning System (GPS) using an Inertial Navigation System (INS) to generate an aerial trajectory, therefore it can be generated in real time converting the UAV into a semi-autonomous aircraft. The aerial robot's dynamic model was obtained by the Euler-Lagrange method, the image processing is based on the pin-hole model of a camera and optical flow. The main advantages and results obtained through the experimentation was first to correctly detect the line, and by LK implementation on OpenCV the line was correctly tracked by the drone achieving this with a low computational cost and with the possibility of indoor use covering the applications where the GPS is not able to work.
Real-Time Drone (UAV) Trajectory Generation and Tracking by Optical Flow
2018-11-01
440480 byte
Conference paper
Electronic Resource
English
Drone Trajectory Segmentation for Real-Time and Adaptive Time-Of-Flight Prediction
DOAJ | 2021
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