【摘要】：為實(shí)現(xiàn)四旋翼飛行器在煤礦環(huán)境中自主飛行,其關(guān)鍵技術(shù)之一是要實(shí)現(xiàn)四旋翼飛行器對(duì)障礙物之間的距離檢測(cè)。本文主要對(duì)四旋翼飛行器的障礙檢測(cè)方法進(jìn)行研究。障礙檢測(cè)硬件系統(tǒng)主要包括STM32F767處理器為核心的控制芯片模塊,以6組超聲波傳感器模塊和姿態(tài)傳感器模塊(包括加速度計(jì),陀螺儀,磁力計(jì))以及無線通信模塊。軟件系統(tǒng)主要包括MATLAB平臺(tái)的上位機(jī)模塊以及基于ARM的單片機(jī)軟件模塊。障礙檢測(cè)系統(tǒng)通過傳感器采集數(shù)據(jù),再通過無線通信模塊,把數(shù)據(jù)發(fā)送至上位機(jī)。四旋翼飛行器障礙檢測(cè)功能實(shí)質(zhì)是指四旋翼在地面坐標(biāo)系中的方位估算。因此,該系統(tǒng)的核心算法是卡爾曼濾波算法。首先在靜止?fàn)顟B(tài)下,提出靜態(tài)模型卡爾曼濾波算法以實(shí)現(xiàn)障礙檢測(cè)。然后在運(yùn)動(dòng)狀態(tài)情況下,其障礙檢測(cè)的算法修正為:以超聲波模塊采集的數(shù)據(jù)作為卡爾曼方程的觀察量,用姿態(tài)傳感器數(shù)據(jù)為飛行器的運(yùn)動(dòng)模型提供參考依據(jù),再通過動(dòng)態(tài)系統(tǒng)最優(yōu)估計(jì)算法解算出障礙物離飛行器的最優(yōu)估計(jì)距離值。接著分別從超聲波模塊遇到干擾的情況,飛行器偏航的情況以及系統(tǒng)處于不平衡的情況下,提出修正以超聲波模塊數(shù)據(jù)為基礎(chǔ)的卡爾曼方程觀察量方法,其中包括有同側(cè)比較算法,方向余弦法。最后通過實(shí)驗(yàn)數(shù)據(jù),驗(yàn)證該算法符合設(shè)計(jì)指標(biāo)。
[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.
【學(xué)位授予單位】：西安科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TD76

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本文編號(hào)：2264866