Simulating unmanned aerial vehicle flight control and collision detection

Visual Computing for Industry, Biomedicine, and Art

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[1] 0000 0001 2256 9319, grid.11135.37, Peking University Shenzhen Graduate School, 518055, Shenzhen, China;0000 0001 2256 9319, grid.11135.37, Beijing Engineering Technology Research Center of Virtual Simulation and Visualization (Peking University), 100871, Beijing, China;0000 0001 2256 9319, grid.11135.37, School of EECS, Peking University, 100871, Beijing, China;

关键词: Unmanned aerial vehicle;    Proportional-integral-derivative control algorithm;    Orientation control;    Position control;    Grid;    k-dimensional tree;    Collision detection;   

DOI  :  10.1186/s42492-019-0014-9

来源: publisher

【 摘 要 】

An unmanned aerial vehicle (UAV) is a small, fast aircraft with many useful features. It is widely used in military reconnaissance, aerial photography, searches, and other fields; it also has very good practical-application and development prospects. Since the UAV’s flight orientation is easily changeable, its orientation and flight path are difficult to control, leading to its high damage rate. Therefore, UAV flight-control technology has become the focus of attention. This study focuses on simulating a UAV’s flight and orientation control, and detecting collisions between a UAV and objects in a complex virtual environment. The proportional-integral-derivative control algorithm is used to control the orientation and position of the UAV in a virtual environment. A version of the bounding-box method that combines a grid with a k-dimensional tree is adopted in this paper, to improve the system performance and accelerate the collision-detection process. This provides a practical method for future studies on UAV flight position and orientation control, collision detection, etc.

【 授权许可】

CC BY