四旋翼飞行器的障碍检测方法研究
发布时间：2018-10-11 18:47
【摘要】：为实现四旋翼飞行器在煤矿环境中自主飞行,其关键技术之一是要实现四旋翼飞行器对障碍物之间的距离检测。本文主要对四旋翼飞行器的障碍检测方法进行研究。障碍检测硬件系统主要包括STM32F767处理器为核心的控制芯片模块,以6组超声波传感器模块和姿态传感器模块(包括加速度计,陀螺仪,磁力计)以及无线通信模块。软件系统主要包括MATLAB平台的上位机模块以及基于ARM的单片机软件模块。障碍检测系统通过传感器采集数据,再通过无线通信模块,把数据发送至上位机。四旋翼飞行器障碍检测功能实质是指四旋翼在地面坐标系中的方位估算。因此,该系统的核心算法是卡尔曼滤波算法。首先在静止状态下,提出静态模型卡尔曼滤波算法以实现障碍检测。然后在运动状态情况下,其障碍检测的算法修正为:以超声波模块采集的数据作为卡尔曼方程的观察量,用姿态传感器数据为飞行器的运动模型提供参考依据,再通过动态系统最优估计算法解算出障碍物离飞行器的最优估计距离值。接着分别从超声波模块遇到干扰的情况,飞行器偏航的情况以及系统处于不平衡的情况下,提出修正以超声波模块数据为基础的卡尔曼方程观察量方法,其中包括有同侧比较算法,方向余弦法。最后通过实验数据,验证该算法符合设计指标。
[Abstract]:In order to realize the autonomous flight of the four-rotor aircraft in the coal mine environment, one of the key technologies is to realize the distance detection between the obstacles of the four-rotor aircraft. In this paper, the obstacle detection method of four-rotor aircraft is studied. The hardware system of obstacle detection mainly includes the control chip module with STM32F767 processor as the core, six groups of ultrasonic sensor module and attitude sensor module (including accelerometer, gyroscope, magnetometer) and wireless communication module. The software system mainly includes upper computer module of MATLAB platform and MCU software module based on ARM. The obstacle detection system collects the data through the sensor and sends the data to the upper computer through the wireless communication module. The obstacle detection function of the four-rotor aircraft is essentially the azimuth estimation of the four-rotor in the ground coordinate system. Therefore, the core algorithm of the system is Kalman filter algorithm. At first, a static model Kalman filter algorithm is proposed to detect obstacles in static state. Then in the case of motion, the algorithm of obstacle detection is revised as follows: the data collected by ultrasonic module is taken as the observation quantity of Kalman equation, and the attitude sensor data is used to provide reference basis for the motion model of aircraft. Then the optimal estimated distance of the obstacle from the vehicle is calculated by the optimal estimation algorithm of the dynamic system. Then, the Kalman equation observation method based on ultrasonic module data is proposed, which is based on the ultrasonic module interference, the aircraft yaw and the unbalanced system. These include the same side comparison algorithm, directional cosine method. Finally, the experimental data show that the algorithm accords with the design index.
【学位授予单位】：西安科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD76
本文编号：2264866
[Abstract]:In order to realize the autonomous flight of the four-rotor aircraft in the coal mine environment, one of the key technologies is to realize the distance detection between the obstacles of the four-rotor aircraft. In this paper, the obstacle detection method of four-rotor aircraft is studied. The hardware system of obstacle detection mainly includes the control chip module with STM32F767 processor as the core, six groups of ultrasonic sensor module and attitude sensor module (including accelerometer, gyroscope, magnetometer) and wireless communication module. The software system mainly includes upper computer module of MATLAB platform and MCU software module based on ARM. The obstacle detection system collects the data through the sensor and sends the data to the upper computer through the wireless communication module. The obstacle detection function of the four-rotor aircraft is essentially the azimuth estimation of the four-rotor in the ground coordinate system. Therefore, the core algorithm of the system is Kalman filter algorithm. At first, a static model Kalman filter algorithm is proposed to detect obstacles in static state. Then in the case of motion, the algorithm of obstacle detection is revised as follows: the data collected by ultrasonic module is taken as the observation quantity of Kalman equation, and the attitude sensor data is used to provide reference basis for the motion model of aircraft. Then the optimal estimated distance of the obstacle from the vehicle is calculated by the optimal estimation algorithm of the dynamic system. Then, the Kalman equation observation method based on ultrasonic module data is proposed, which is based on the ultrasonic module interference, the aircraft yaw and the unbalanced system. These include the same side comparison algorithm, directional cosine method. Finally, the experimental data show that the algorithm accords with the design index.
【学位授予单位】：西安科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD76
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