基于多传感器信息融合的无人机防碰撞系统

Multi-Sensor Fusion Based UAV Collision Avoidance System

本文以四旋翼无人机(UAV)为研究对象,实现基于卡尔曼滤波器的多传感器信息融合和级联型PID位置和速度控制器对障碍目标进行检测并避免与障碍物碰撞。通过对超声波(US)和红外(IR)传感器采集的信息进行融合,以获得用于障碍物检测的可靠范围数据,然后将其馈送到碰撞回避控制器(CAC),产生回避障碍的姿态命令。结果表明,多传感器信息融合通过降低单个传感器测量中存在的噪声和误差来提供准确的距离估计。在飞行试验中,四旋翼无人机能够成功避免与在飞行期间向其引入的障碍物碰撞。

This paper presents the development of a quadrotor unmanned aerial vehicle （UAV） that is capable of detecting and avoiding collision with obstacles through the implementation of Kalman fitter-based multi-sensor fusion and cascaded PID position and velocity controllers. Sensor fusion of ultrasonic （US） and infrared （IR） sensors is performed to obtain reliable range data for obstacle detection, then fed into collision avoidance controller （CAC） for generating necessary response in terms of attitude commands. Results show that sensorfusion provides accurate range estimation by reducing noises and errors are presented inindividual sensors measurements. Flight tests performed prove the capability of UAV to avoid collisions with the obstacle that is introduced during flight successfully.