Simulating unmanned aerial vehicle flight control and collision detection

Abstract

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.

Construction of a virtual reality platform for computer-aided navigation Lingnan bone setting technique

“…At present, the collision detection algorithms for the two models can be roughly divided into two categories: space decomposition method and hierarchical bounding box method [ 11 , 12 ]. The space decomposition method divides the entire virtual space into small cells of equal volume.…”