Autonomous drone control system for object tracking: Flexible system design with implementation example

Abstract

This paper contains presentation of the flexible control system for an autonomous UAV (unmanned air vehicle). The complete description of hardware and software solutions used to realize autonomous flight are presented in this work. Main objective of the research was to develop software which provides ease of adjustment and extendibility to drone system with different equipment. Presented system is utilizable on various hardware platforms and is capable of realizing different missions with minimal adjustments. Described concept significantly simplifies designing complex system by introducing modular architecture. Presented method of dividing software components into modules with single functionality minimizes amount of work necessary to adjust system in case of changes in hardware. Presented general concept of system architecture is backed up with real life working model designed for tracking and landing on moving target. This paper contains detailed description of algorithms used in the project. Landing area detection is accomplished with vision system. Canny's edge detection algorithm with contour shape analysis algorithm is used for marker detection. Lucas-Kanade optical flow algorithm is applied for tracking detected pattern. Mission planning is realized as dedicated state machine developed for this particular task. System design is built with use of ROS (Robot Operating System) and is utilizing its subscriber-publisher method of data exchange between separated software units. Especially designed frame is used as hardware platform. Exemplary system is realized with Raspberry Pi 3 as onboard computer and Pixhawk flight controller. This concept and the exemplary system is a result of preparation for Mohamed Bin Zayed International Robotic Challenge 2017 in Abu Dhabi. Results from experiments performed as trials for the competition and future prospects are presented in this paper.