技术领域technical field
本发明属于无人机技术领域，尤其涉及一种运动平台上无人机自主精确着陆系统及着陆方法。The invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to an autonomous and precise landing system and landing method for unmanned aerial vehicles on a moving platform.
背景技术Background technique
如今小型旋翼无人机越来越广泛地用于各种军用、民用行业，如植保、电力巡检、航拍、灾后救援，通常的使用方法是用小汽车携带旋翼无人机到任务区域，人工控制旋翼无人机起飞，执行任务，最后降落到地面。在降落时通常需要很大一块空地，由于旋翼无人机自身定位精度较差，降落花费时间长，控制效果差，容易发生意外。如果能实现旋翼无人机自主精确降落在车顶，就能节省很多时间，也能降低对降落地点的要求。旋翼无人机上现有的传感器主要依靠GPS定位，只能实现米级精度的降落，采用差分GPS技术会大幅增加硬件成本。考虑到现有的旋翼无人机一般都会搭载云台相机，可充分利用这个云台相机，只需要再增加一台嵌入式计算机即可实现视觉辅助降落，具有成本低，精度高的优点。Nowadays, small rotor UAVs are more and more widely used in various military and civilian industries, such as plant protection, power inspection, aerial photography, and post-disaster rescue. The usual method of use is to use a car to carry the rotor UAV to the mission area. Control the rotor drone to take off, perform missions, and finally land on the ground. A large open space is usually required when landing. Due to the poor positioning accuracy of the rotor UAV, it takes a long time to land, the control effect is poor, and accidents are prone to occur. If the rotor drone can be autonomously and accurately landed on the roof of the vehicle, it will save a lot of time and reduce the requirements for the landing location. The existing sensors on the rotor UAV mainly rely on GPS positioning, which can only achieve meter-level precision landing, and the use of differential GPS technology will greatly increase the hardware cost. Considering that the existing rotor drones are generally equipped with a gimbal camera, the gimbal camera can be fully utilized, and only need to add an embedded computer to achieve visually assisted landing, which has the advantages of low cost and high precision.
用于旋翼无人机的单目视觉辅助着陆的相关研究已经有很多，但现有技术无法实现在运动平台上自主精确着陆，主要有以下几个原因：There have been a lot of researches on monocular vision-assisted landing for rotary-wing drones, but the existing technology cannot achieve autonomous and precise landing on a moving platform, mainly for the following reasons:
1、受图标尺寸限制，无人机在低处容易超出相机视野范围，在高处又看不清。1. Limited by the size of the icon, the drone is easy to exceed the camera's field of view at low places, and it is difficult to see clearly at high places.
现有的解决尺寸限制问题的方案是增加嵌套图标，但现有的嵌套图标都是由形状完全相同的不同大小的图案同心嵌套而成。由于完全相同，识别的时候计算机无法判断自己识别到的是大图标还是小图标，因此无法算出准确的位置信息，只能得到图标与画面中心的像素偏差(例如x轴偏100像素，y轴偏150像素)，使无人机的控制精度大幅降低，一般只适用于静止平台的降落，在运动平台上仅靠像素偏差无法满足精确着陆的要求。在运动平台降落实验中同心嵌套的图标还曝露出一个严重的问题：图标的可识别范围是以图标中心为顶点，向上逐渐扩大的锥体，如图3所示，飞行高度越低(或相机与图标的距离越小)，水平方向可识别的范围就越小。运动平台着陆时车速不稳定，当无人机下降到很低的位置时，一旦车速发生变化，无人机很容易脱离可识别范围，导致降落失败。The existing solution to the problem of size limitation is to add nested icons, but the existing nested icons are formed by concentrically nesting patterns of different sizes with exactly the same shape. Because they are exactly the same, the computer cannot judge whether it recognizes a large icon or a small icon during recognition, so it cannot calculate the accurate position information, and can only get the pixel deviation between the icon and the center of the screen (for example, the x-axis is offset by 100 pixels, and the y-axis is offset by 100 pixels. 150 pixels), which greatly reduces the control accuracy of the UAV. Generally, it is only suitable for landing on a stationary platform. On a moving platform, pixel deviation alone cannot meet the requirements of precise landing. In the landing experiment of the moving platform, the concentrically nested icons also exposed a serious problem: the recognizable range of the icon is the center of the icon as the vertex, and the cone gradually expands upward, as shown in Figure 3, the lower the flying height (or The smaller the distance between the camera and the icon), the smaller the recognizable range in the horizontal direction. The speed of the moving platform is unstable when landing. When the UAV descends to a very low position, once the speed changes, the UAV can easily leave the recognizable range, resulting in landing failure.
2、现有的图像识别算法无法处理倾斜的相机拍摄到的图标。现有的视觉定位所用的图标多是基于形状的，比如矩形、圆形、三角形，这种图标的识别方法是分析图标的轮廓，如果轮廓与预先设置的形状一致，则认为识别成功，如果相机倾斜，由于透视效应，拍摄到的图标不再是标准的形状，则无法识别。因此即使加上云台，当拍摄角度较大时也无法正常识别和定位，无法利用云台来扩大识别范围。2. Existing image recognition algorithms cannot handle icons captured by tilted cameras. Most of the icons used in existing visual positioning are based on shapes, such as rectangles, circles, and triangles. The recognition method of such icons is to analyze the outline of the icon. If the outline is consistent with the preset shape, the recognition is considered successful. If the camera Slanted, due to the perspective effect, the captured icon is no longer a standard shape and cannot be recognized. Therefore, even if the gimbal is added, it cannot be recognized and positioned normally when the shooting angle is large, and the gimbal cannot be used to expand the recognition range.
3、现有的图标由于形状过于简单且仅仅通过形状轮廓来判断，没有考虑对图标整个表面的识别，判断条件不够严谨，容易出现把地面上的其他物体误识别为图标的情况。3. The existing icons are too simple in shape and judged only by the outline of the shape, without considering the recognition of the entire surface of the icon, the judgment conditions are not rigorous enough, and it is easy to misidentify other objects on the ground as icons.
4、现有的视觉辅助降落多采用与旋翼无人机固连的竖直向下的相机，这种方式视野范围较小且受旋翼无人机姿态影响。当无人机飞行速度较快时相机始终处在倾斜状态，使图标无法进入相机视野。4. The existing vision-assisted landing mostly uses a vertically downward camera fixedly connected to the rotor UAV. This method has a small field of view and is affected by the attitude of the rotor UAV. When the drone is flying fast, the camera is always in a tilted state, so that the icon cannot enter the camera's field of view.
发明内容Contents of the invention
为解决上述问题，本发明提供一种运动平台上无人机自主精确着陆系统及着陆方法。采用云台相机去识别由相互重叠、尺寸不同、图案不同且分布不对称的二维码组成的多层嵌套标识，提供一种精度高、可靠性好、成本低的视觉辅助旋翼无人机自主着陆系统。In order to solve the above problems, the present invention provides an autonomous and precise landing system and landing method for UAVs on a moving platform. The PTZ camera is used to identify multi-layer nested marks composed of two-dimensional codes with overlapping, different sizes, different patterns and asymmetric distribution, providing a visually assisted rotor drone with high precision, good reliability and low cost Autonomous landing system.
一种运动平台上无人机自主精确着陆系统，包括旋翼无人机1、机载云台相机2、机载计算机3、机载起落架磁性器件4、车载铁质降落坪6以及多层嵌套标识7；An autonomous and precise landing system for unmanned aerial vehicles on a moving platform, including a rotor unmanned aerial vehicle 1, an airborne pan-tilt camera 2, an on-board computer 3, an airborne landing gear magnetic device 4, a vehicle-mounted iron landing pad 6, and a multi-layer embedding Set of logos 7;
所述机载云台相机2安装在旋翼无人机1的下方，包括相机和云台；The airborne platform camera 2 is installed under the rotor UAV 1, including a camera and a platform;
所述云台被电机驱动旋转到任意给定角度；The pan-tilt is driven by a motor to rotate to any given angle;
所述机载计算机3安装在旋翼无人机1上，根据机载云台相机2拍摄的包含多层嵌套标识7的画面，向旋翼无人机1发送控制指令并引导旋翼无人机1着陆；同时机载计算机3控制云台的转动，并与旋翼无人机1的飞行控制器通信，接收旋翼无人机1的位置和速度；The on-board computer 3 is installed on the rotor UAV 1, and sends control instructions to the rotor UAV 1 and guides the rotor UAV 1 according to the picture taken by the airborne pan-tilt camera 2 that includes the multi-layer nested logo 7 Landing; at the same time, the onboard computer 3 controls the rotation of the gimbal, and communicates with the flight controller of the rotor UAV 1, and receives the position and speed of the rotor UAV 1;
所述机载起落架磁性器件4安装在旋翼无人机1起落架的下端；The airborne landing gear magnetic device 4 is installed on the lower end of the rotor UAV 1 landing gear;
所述车载铁质降落坪6固定在机动车5的顶部；The vehicle-mounted iron landing pad 6 is fixed on the top of the motor vehicle 5;
所述多层嵌套标识7附着在车载铁质降落坪6上；其中多层嵌套标识7为由相互重叠、尺寸不同、图案不同且分布不对称的二维码组成；The multi-layer nested logo 7 is attached to the vehicle-mounted iron landing pad 6; wherein the multi-layer nested logo 7 is composed of two-dimensional codes that overlap each other, have different sizes, different patterns, and are asymmetrically distributed;
其中小尺寸二维码覆盖在大尺寸二维码上；且大尺寸二维码上沿机动车5的前进方向覆盖多个小尺寸二维码，其中尺寸最大的二维码只有一个。The small-size two-dimensional code is covered on the large-size two-dimensional code; and the large-size two-dimensional code is covered with multiple small-size two-dimensional codes along the forward direction of the motor vehicle 5, and there is only one largest two-dimensional code.
一种运动平台上无人机自主精确着陆系统，所述二维码均为正方形，且正方形包括N行×N列的小正方形，其中N的取值至少为5，与机载云台相机2的分辨率有关；An autonomous and precise landing system for unmanned aerial vehicles on a moving platform, the two-dimensional codes are all squares, and the squares include small squares with N rows×N columns, where the value of N is at least 5, and the airborne pan-tilt camera 2 related to the resolution;
所述二维码只包含黑白两种颜色；位于正方形边缘的小正方形全为黑色，内部的小正方形不全为黑色，且白色小正方形和黑色小正方形分布不对称；小尺寸二维码覆盖在大尺寸二维码的黑色小正方形上。The two-dimensional code contains only two colors of black and white; the small squares located on the edge of the square are all black, and the small squares inside are not all black, and the distribution of small white squares and small black squares is asymmetrical; the small-sized two-dimensional code covers the large size QR code on the small black square.
一种运动平台上无人机自主精确着陆系统，除尺寸最大的二维码外，其他尺寸二维码的四边均设置有白边，且白边的宽度与相机分辨率有关，相机分辨率越高，所述白边越窄。An autonomous and precise landing system for unmanned aerial vehicles on a moving platform. Except for the largest two-dimensional code, the four sides of the other size two-dimensional codes are all provided with white borders, and the width of the white border is related to the resolution of the camera. Higher, the narrower the white border.
一种基于运动平台上无人机自主精确着陆系统的着落方法，包括以下步骤：A landing method based on a UAV autonomous precision landing system on a motion platform, comprising the following steps:
步骤1：标定机载云台相机2，得到内参数和畸变参数；并记录所有二维码的大小以及各个二维码相对多层嵌套标识7中心的位置坐标；同时分别采用N×N二维矩阵A＝[aij]N×N表征各个二维码，其中aij为二维矩阵A的第i行第j列的元素，与各个二维码第i行第j列的小正方形对应，得到表征所有二维码的二维矩阵集合∪A；其中黑色小正方形对应的矩阵元素值为0，白色小正方形对应的矩阵元素值为1；Step 1: Calibrate the airborne pan/tilt camera 2 to obtain internal parameters and distortion parameters; and record the size of all two-dimensional codes and the position coordinates of each two-dimensional code relative to the center of the multi-layer nested logo 7; Dimensional matrix A=[aij ]N×N characterizes each two-dimensional code, where aij is the element in row i, column j of two-dimensional matrix A, corresponding to the small square in row i, column j of each two-dimensional code , to obtain the two-dimensional matrix set ∪A representing all two-dimensional codes; the matrix element value corresponding to the black small square is 0, and the matrix element value corresponding to the white small square is 1;
步骤2：机载计算机3控制机载云台相机2转动，并识别来自机载云台相机2拍摄的图像，判断是否找到二维码；具体识别步骤如下：Step 2: The on-board computer 3 controls the rotation of the on-board pan-tilt camera 2, and recognizes the image taken by the on-board pan-tilt camera 2, and determines whether a two-dimensional code is found; the specific identification steps are as follows:
步骤21：将机载云台相机2读取到的画面依次进行灰度化、二值化和降噪处理，得到0/1二值图，其中0代表黑色像素，1代表白色像素；Step 21: Grayscale, binarize, and denoise the image read by the on-board pan/tilt camera 2 in order to obtain a 0/1 binary image, where 0 represents a black pixel and 1 represents a white pixel;
步骤22：利用边界跟踪算法从0/1二值图中提取画面所拍摄到的所有物体的轮廓，选取凸四边形轮廓，得到物体对应的凸四边形图像；Step 22: Use the boundary tracking algorithm to extract the outlines of all objects captured in the picture from the 0/1 binary image, select the outline of a convex quadrilateral, and obtain the corresponding convex quadrilateral image of the object;
步骤23：通过仿射变换，将所述凸四边形图像变为正方形图像；Step 23: changing the convex quadrilateral image into a square image through affine transformation;
步骤24：将正方形图像等分为N行N列的小正方形，计算每个小正方形中1的个数；其中，如果小正方形中1的个数超过像素总数的一半，则判定该小正方形为白色，否则为黑色；Step 24: Divide the square image into small squares with N rows and N columns, and calculate the number of 1s in each small square; where, if the number of 1s in the small square exceeds half of the total number of pixels, then determine that the small square is white, otherwise black;
步骤25：采用N×N二维矩阵B＝[bij]N×N表征步骤23中的正方形图像，其中bij为二维矩阵B第i行第j列的元素，与第i行第j列小正方形对应；其中，如果小正方形为黑色，则其对应二维矩阵的元素值为0；如果小正方形为白色，则其对应二维矩阵的元素值为1；Step 25: Use N×N two-dimensional matrix B=[bij ]N×N to characterize the square image in step 23, where bij is the element in row i, column j of two-dimensional matrix B, and Columns of small squares correspond; where, if the small square is black, the element value corresponding to the two-dimensional matrix is 0; if the small square is white, the element value corresponding to the two-dimensional matrix is 1;
步骤26：将正方形图像对应的二维矩阵B与二维码对应的集合∪A中的二维矩阵进行对比；其中：Step 26: Compare the two-dimensional matrix B corresponding to the square image with the two-dimensional matrix in the set ∪A corresponding to the two-dimensional code; where:
如果二维矩阵B与集合∪A中的任意二维矩阵A完全相同，则机载云台相机2成功识别多层嵌套标识7中的二维码，并进入步骤3；If the two-dimensional matrix B is exactly the same as any two-dimensional matrix A in the set ∪A, then the airborne pan-tilt camera 2 successfully recognizes the two-dimensional code in the multi-layer nesting mark 7, and enters step 3;
如果二维矩阵B与二维矩阵A不相同，则重复步骤21-25；If the two-dimensional matrix B is different from the two-dimensional matrix A, then repeat steps 21-25;
步骤3：利用机载云台相机2的内参数和畸变参数、各个二维码相对多层嵌套标识7中心的位置坐标、二维码在机载云台相机2所拍摄画面上的像素坐标以及机载云台相机2相对于旋翼无人机1的姿态角，通过梯度法寻优计算机载云台相机2相对于多层嵌套标识7的位置和姿态角；其中，机载云台相机2相对于旋翼无人机1的姿态角为云台被电机驱动旋转的角度；Step 3: using the internal parameters and distortion parameters of the airborne PTZ camera 2, the position coordinates of each two-dimensional code relative to the center of the multi-layer nested logo 7, and the pixel coordinates of the two-dimensional code on the screen captured by the airborne PTZ camera 2 And the attitude angle of the airborne pan-tilt camera 2 relative to the rotor UAV 1, the position and attitude angle of the computer-borne pan-tilt camera 2 relative to the multi-layer nested logo 7 are optimized by gradient method; wherein, the airborne pan-tilt camera 2 The attitude angle relative to the rotor UAV 1 is the angle at which the gimbal is driven by the motor to rotate;
步骤4：机载计算机3根据机载云台相机2拍摄的画面和机载云台相机2相对于多层嵌套标识7的位置和姿态角，计算旋翼无人机1当前相对于多层嵌套标识7的姿态角和位置信息，从而生成控制指令控制旋翼无人机1缩小相对于多层嵌套标识7中心位置的偏差，沿水平方向与多层嵌套标识7中心位置对齐，再沿竖直方向降低高度；Step 4: The onboard computer 3 calculates the position and attitude angle of the rotor UAV 1 relative to the multi-layer embedding mark 7 according to the picture taken by the on-board PTZ camera 2 and the position and attitude angle of the airborne PTZ camera 2 relative to the multi-layer embedding mark 7. Set the attitude angle and position information of the logo 7, so as to generate control instructions to control the rotor UAV 1 to reduce the deviation relative to the center position of the multi-layer nest logo 7, align with the center position of the multi-layer nest logo 7 along the horizontal direction, and then move along the reduce height vertically;
步骤5：当旋翼无人机1接近车载铁质降落坪6时，机载起落架磁性器件4与车载铁质降落坪6互相吸引，使旋翼无人机1稳定落在车载铁质降落坪6上，完成着落。Step 5: When the rotor UAV 1 approaches the vehicle-mounted iron landing pad 6, the magnetic device 4 of the airborne landing gear and the vehicle-mounted iron landing pad 6 attract each other, so that the rotor UAV 1 stably lands on the vehicle-mounted iron landing pad 6 On, complete landing.
一种运动平台上无人机自主精确着陆系统的着落方法，所述步骤26中如果识别到多个二维码，则优先使用尺寸最大的二维码；如果识别的二维码都是同样大小的二维码，则优先使用靠近多层嵌套标识7中心的二维码。A landing method for an autonomous and precise landing system of an unmanned aerial vehicle on a motion platform, if multiple two-dimensional codes are recognized in the step 26, the two-dimensional code with the largest size is preferentially used; if the two-dimensional codes recognized are all the same size QR codes, the QR codes close to the center of the multi-layer nested logo 7 are preferred.
一种运动平台上无人机自主精确着陆系统的着落方法，所述步骤4中机载计算机3生成控制指令控制旋翼无人机1的过程中，如果机动车5车速突然变化，机载计算机3将发送控制指令以控制云台转动，使离相机最近的二维码始终处于机载云台相机2的视野中心。A landing method for an autonomous and precise landing system of an unmanned aerial vehicle on a motion platform. In the process of generating control commands to control the rotor unmanned aerial vehicle 1 in the step 4, if the speed of the motor vehicle 5 changes suddenly, the onboard computer 3 A control command will be sent to control the rotation of the gimbal, so that the QR code closest to the camera is always in the center of the field of view of the onboard gimbal camera 2.
一种运动平台上无人机自主精确着陆系统，所述多层嵌套标识7表面材质粗糙。An autonomous and precise landing system for unmanned aerial vehicles on a moving platform, the surface material of the multi-layer nested logo 7 is rough.
一种运动平台上无人机自主精确着陆系统，所述机载计算机3为高性能Arm架构或x86架构计算模块，通过串口与旋翼无人机1的飞行控制器通信，通过USB接口或专用视频输入口读取相机画面；机载计算机3接收来自机载云台相机2记录的画面和姿态角，旋翼无人机1的位置、速度和姿态角，并向旋翼无人机1发送控制指令。An autonomous and precise landing system for unmanned aerial vehicles on a motion platform, the onboard computer 3 is a high-performance Arm architecture or x86 architecture computing module, communicates with the flight controller of the rotor UAV 1 through a serial port, and communicates with the flight controller of the rotor UAV 1 through a USB interface or a dedicated video The input port reads the camera picture; the onboard computer 3 receives the picture and attitude angle recorded by the onboard pan-tilt camera 2, the position, speed and attitude angle of the rotor UAV 1, and sends control instructions to the rotor UAV 1.
一种运动平台上无人机自主精确着陆系统，所述机载起落架磁性器件4为钕铁硼磁铁。An autonomous and precise landing system for an unmanned aerial vehicle on a moving platform, the magnetic device 4 of the airborne landing gear is a neodymium-iron-boron magnet.
有益效果：Beneficial effect:
1、本发明使用相互重叠、尺寸不同且分布不对称的二维码组成多层嵌套标识，利用旋翼无人机搭载的云台相机，提供一种精度高、可靠性好、成本低的视觉辅助旋翼无人机自主着陆系统，特别适用于在运动机动车顶端的着陆。图标设计上把小尺寸二维码覆盖在大尺寸二维码上，将同心嵌套改为分布不对称的混合式嵌套，与同心嵌套的图标相比，本设计显著增加水平方向的可识别范围，如附图3所示。无人机飞行高度很低时，由于大尺寸二维码上沿机动车的前进方向覆盖多个小尺寸二维码，即使车速突然变化，无人机也能从一个小尺寸二维码切换到另一个小尺寸二维码，减小脱离多层嵌套识别范围的可能性。1. The present invention uses overlapping two-dimensional codes with different sizes and asymmetric distribution to form multi-layer nested marks, and uses the pan-tilt camera carried by the rotor drone to provide a visual image with high precision, good reliability and low cost. Auxiliary rotorcraft autonomous landing system, especially suitable for landing on top of sports vehicles. In the icon design, the small-size QR code is covered on the large-size QR code, and the concentric nesting is changed to a mixed nesting with asymmetric distribution. Compared with the concentric nesting icon, this design significantly increases the horizontal direction. The identification range is shown in Figure 3. When the flying height of the drone is very low, since the large-size QR code covers multiple small-size QR codes along the forward direction of the motor vehicle, even if the vehicle speed changes suddenly, the drone can switch from a small-size QR code to Another small-size QR code reduces the possibility of leaving the recognition range of multi-layer nesting.
2、本发明通过为每个小图标设置不同的二维码，并且分别采用不同的二维矩阵表征各个二维码，使得计算机可以区分每个图标，在姿态解算时可以得到全部姿态角和实际偏差，而不仅仅是像素偏差。2. The present invention sets different two-dimensional codes for each small icon, and uses different two-dimensional matrices to characterize each two-dimensional code, so that the computer can distinguish each icon, and can obtain all attitude angles and Actual deviation, not just pixel deviation.
3、本发明对二维码进行识别，不是靠图形轮廓来判断，而是分析了轮廓内部的所有像素，降低了把其他物体误识别为图标的概率，不依赖形状轮廓使得相机无需保持竖直向下，从任意角度拍到图标均可识别，增大了识别角度的同时保证了识别的精度。并可根据预先设计好的小二维码在大二维码上的相对位置计算出无人机相对于多层嵌套标识中心的实际偏差，为混合式嵌套的实现提供了基础。3. The invention recognizes the two-dimensional code, not by the graphic outline, but by analyzing all the pixels inside the outline, which reduces the probability of misidentifying other objects as icons, and does not rely on the shape outline so that the camera does not need to be kept vertical Downward, the icon can be recognized from any angle, which increases the recognition angle and ensures the recognition accuracy. And according to the relative position of the pre-designed small two-dimensional code on the large two-dimensional code, the actual deviation of the drone relative to the center of the multi-layer nesting mark can be calculated, which provides a basis for the realization of hybrid nesting.
4、本发明把与无人机固连的传统的单目相机升级为云台相机，增大了画面拍摄范围，且画面稳定，不易受飞机姿态影响；同时通过对云台的控制使得相机能更好地锁定图标，减少脱离识别范围的可能性。4. The present invention upgrades the traditional monocular camera fixedly connected with the UAV to a pan-tilt camera, which increases the shooting range of the picture, and the picture is stable, and is not easily affected by the attitude of the aircraft; at the same time, the camera can be controlled by the pan-tilt. Better locking of icons, less chance of getting out of recognition range.
5、本发明采用的多层嵌套标识表面材质粗糙，既能有效减少反光，又能在旋翼无人机着陆后提供较大的摩擦力。5. The surface material of the multi-layer nested logo adopted in the present invention is rough, which can not only effectively reduce reflection, but also provide greater friction after the rotor drone lands.
附图说明Description of drawings
图1为本发明的一种运动平台上无人机自主精确着陆系统示意图；Fig. 1 is a schematic diagram of an autonomous and precise landing system for an unmanned aerial vehicle on a motion platform of the present invention;
图2为本发明的多层嵌套标识具体实现形式；Fig. 2 is the specific implementation form of the multi-layer nested identification of the present invention;
图3为本发明的机载云台相机在识别范围上与现有技术的对比示意图；Fig. 3 is a schematic diagram of comparison between the airborne pan-tilt camera of the present invention and the prior art in the recognition range;
图4为本发明识别多层嵌套标识中二维码的流程图；Fig. 4 is the flowchart of identifying the two-dimensional code in the multi-layer nested mark of the present invention;
1-旋翼无人机，2-机载云台相机，3-机载计算机，4-机载起落架磁性器件，5-机动车，6-车载铁质降落坪，7-多层嵌套标识。1-Rotor UAV, 2-Airborne PTZ camera, 3-Airborne computer, 4-Airborne landing gear magnetic device, 5-Motor vehicle, 6-Vehicle iron landing pad, 7-Multi-layer nested logo .
具体实施方式detailed description
下面结合附图和实施例对本发明进行详细的描述。The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.
本发明设计一种特别设计的多层嵌套二维码标识，利用旋翼无人机现有的云台相机，提供一种精度高、可靠性好、成本低的视觉辅助旋翼无人机自主着陆系统，特别适用于在运动车辆顶端的着陆。其系统组成如图1所示，包括旋翼无人机1、机载云台相机2、机载计算机3、机载起落架磁性器件4、车载铁质降落坪6以及多层嵌套标识7；The present invention designs a specially designed multi-layer nested two-dimensional code identification, and uses the existing pan-tilt camera of the rotor UAV to provide a vision-assisted autonomous landing of the rotor UAV with high precision, good reliability and low cost system, especially for landing on top of moving vehicles. Its system composition is shown in Figure 1, including rotor UAV 1, airborne pan-tilt camera 2, airborne computer 3, airborne landing gear magnetic device 4, vehicle-mounted iron landing pad 6 and multi-layer nested logo 7;
所述旋翼无人机1指一套完整的无人机系统，包括无人机、遥控器(或地面站)，无人机由机架、螺旋桨电机、电调、传感器、飞行控制器；其中传感器包括加速度计、陀螺仪、磁罗盘、GPS、气压计；The rotor UAV 1 refers to a complete UAV system, including a UAV, a remote controller (or a ground station), and the UAV consists of a frame, a propeller motor, an electric regulator, a sensor, and a flight controller; wherein Sensors include accelerometer, gyroscope, magnetic compass, GPS, barometer;
所述机载云台相机2安装在旋翼无人机1的下方，包括相机和云台；The airborne platform camera 2 is installed under the rotor UAV 1, including a camera and a platform;
所述云台被电机驱动旋转到任意给定角度，并记录相机当前相对于旋翼无人机1的姿态角或记录相机在地面坐标系下的姿态角；云台既可以保证相机画面稳定不受无人机运动的影响，又使相机可以从更大的角度拍摄到多层嵌套标识7；云台按照机载计算机3的命令转动，并把相机画面直接传输到机载计算机3，同时将相机姿态角直接传输到机载计算机3或通过飞行控制器间接传输到机载计算机3。The pan/tilt is driven by the motor to rotate to any given angle, and records the current attitude angle of the camera relative to the rotor UAV 1 or records the attitude angle of the camera in the ground coordinate system; the pan/tilt can ensure that the camera picture is stable without being affected The impact of the movement of the UAV enables the camera to take pictures of the multi-layer nested logo 7 from a larger angle; The camera attitude angle is directly transmitted to the onboard computer 3 or indirectly transmitted to the onboard computer 3 through the flight controller.
所述机载计算机3安装在旋翼无人机1的上方；机载计算机3与旋翼无人机1的飞行控制器通信，接收来自机载云台相机2拍摄的画面和姿态角、来自旋翼无人机1的的位置、速度和姿态角，并向旋翼无人机1发送控制指令；Described onboard computer 3 is installed on the top of rotor drone 1; The position, velocity and attitude angle of the human-machine 1, and send control instructions to the rotor UAV 1;
所述机载计算机3为高性能Arm架构或x86架构计算模块，通过串口与旋翼无人机1的飞行控制器通信，通过USB接口或专用视频输入口读取相机画面；The onboard computer 3 is a high-performance Arm architecture or an x86 architecture computing module, communicates with the flight controller of the rotor UAV 1 through a serial port, and reads the camera picture through a USB interface or a dedicated video input port;
所述机载起落架磁性器件4安装在旋翼无人机1起落架的下端；所述机载起落架磁性器件4为小型钕铁硼磁铁，具有重量轻，磁性强的优点；The airborne landing gear magnetic device 4 is installed on the lower end of the rotor UAV 1 landing gear; the airborne landing gear magnetic device 4 is a small neodymium-iron-boron magnet, which has the advantages of light weight and strong magnetism;
所述车载铁质降落坪6固定在机动车5的顶部；其中机载起落架磁性器件4对车载铁质降落坪6有吸引作用；The vehicle-mounted iron landing pad 6 is fixed on the top of the motor vehicle 5; wherein the airborne landing gear magnetic device 4 has an attractive effect on the vehicle-mounted iron landing pad 6;
所述多层嵌套标识7附着在车载铁质降落坪6上；其中多层嵌套标识7为由相互重叠的二维码组成。其中多层嵌套标识7为印有二维码的粗糙布料，粗糙布料既能有效减少反光，又能在旋翼无人机着陆后提供较大的摩擦力。The multi-layer nesting logo 7 is attached to the vehicle-mounted iron landing pad 6; wherein the multi-layer nesting logo 7 is composed of overlapping two-dimensional codes. Among them, the multi-layer nested logo 7 is a rough cloth printed with a two-dimensional code. The rough cloth can not only effectively reduce reflection, but also provide greater friction after the rotor drone lands.
所述多层嵌套标识7由相互重叠、尺寸不同、图案不同的二维码组成，其中尺寸最大的二维码只有一个；The multi-layer nested logo 7 is composed of overlapping two-dimensional codes with different sizes and different patterns, wherein there is only one two-dimensional code with the largest size;
所述二维码均为正方形，且正方形按行列等分成5行5列的小正方形；The two-dimensional codes are all squares, and the squares are equally divided into small squares with 5 rows and 5 columns according to rows and columns;
所述二维码只包含黑白两种颜色，并以黑色为主；位于正方形边缘的小正方形为黑色，内部的小正方形不全为黑色，且白色小正方形和黑色小正方形分布不对称，保证整个图案不对称；小二维码覆盖在大二维码的黑色小正方形上；分别采用5×5二维矩阵A＝[aij]5×5表征各个二维码，其中aij为二维矩阵A第i行第j列个元素，与各个二维码第i行第j列小正方形对应，得到表征所有二维码的二维矩阵集合∪A；其中黑色小正方形对应的矩阵元素值为0，白色小正方形对应的矩阵元素值为1；The two-dimensional code only contains two colors of black and white, and black is the main color; the small squares on the edge of the square are black, and the small squares inside are not all black, and the distribution of small white squares and small black squares is asymmetrical, ensuring that the entire pattern Asymmetric; the small two-dimensional code is covered on the small black square of the large two-dimensional code; each two-dimensional code is represented by a 5×5 two-dimensional matrix A=[aij ]5×5 , where aij is the two-dimensional matrix A The element in the i-th row and j-column corresponds to the small square in the i-th row and j-column of each two-dimensional code, and the two-dimensional matrix set ∪A representing all two-dimensional codes is obtained; the matrix element value corresponding to the black small square is 0, The matrix element value corresponding to the small white square is 1;
如图2所示，大二维码边长为100厘米，中二维码边长为20厘米，小二维码边长为8厘米。所述小二维码与大二维码邻接的四边设置有白边，白边的宽度与相机分辨率有关，相机分辨率越高，所述白边越窄；图2中小二维码的四周白边宽度为1厘米。同时由于相机的感光元件过于灵敏，导致黑白边界处失真，因此小二维码的白色部分可用灰色代替。旋翼无人机1飞行高度越低，相机水平方向能识别二维码的范围就越小，而汽车和无人机不可能总是匀速运动，出现速度差不可避免，因此降落过程中沿汽车前进的方向旋翼无人机1极易脱离识别范围，为了解决这个问题，在大二维码上沿汽车前进方向覆盖5个小二维码。As shown in Figure 2, the side length of the large QR code is 100 cm, the side length of the medium QR code is 20 cm, and the side length of the small QR code is 8 cm. The four sides adjacent to the small two-dimensional code and the large two-dimensional code are provided with white borders, and the width of the white border is related to the resolution of the camera. The higher the resolution of the camera, the narrower the white borders; around the small two-dimensional code in Fig. 2 The width of the white border is 1 cm. At the same time, because the photosensitive element of the camera is too sensitive, the black and white boundary is distorted, so the white part of the small QR code can be replaced by gray. The lower the flying height of the rotor UAV 1, the smaller the range that the camera can recognize the two-dimensional code in the horizontal direction, and the car and the UAV cannot always move at a constant speed, and the speed difference is inevitable, so move forward along the car during the landing process The direction of the rotor UAV 1 is very easy to get out of the recognition range. In order to solve this problem, five small QR codes are covered on the big QR code along the direction of the car.
一种运动平台无人机自主精确着陆系统的着落方法，包括以下步骤：A landing method for an autonomous and precise landing system of a motion platform unmanned aerial vehicle, comprising the following steps:
步骤1：旋翼无人机1飞行前用张正友法标定机载云台相机2，得到内参数和畸变参数；并对所有二维码进行编号，以便在识别时加以区分，记录所有二维码的大小和各个二维码相对多层嵌套标识7中心的位置坐标；Step 1: Calibrate the airborne gimbal camera 2 with the Zhang Zhengyou method before the flight of the rotor UAV 1 to obtain the internal parameters and distortion parameters; and number all the two-dimensional codes to distinguish them during identification, and record the parameters of all two-dimensional codes The size and position coordinates of each two-dimensional code relative to the center of the multi-layer nested logo 7;
所述张正友法为针对摄像机径向畸变问题，提出的求解摄像机内外参数的方法，同一个相机只需要标定一次。该方法模板制作容易，使用方便，成本低，鲁棒性好，准确率高，具有广泛的应用。The Zhang Zhengyou method is a method proposed to solve the internal and external parameters of the camera for the radial distortion problem of the camera. The same camera only needs to be calibrated once. The template of the method is easy to make, convenient to use, low in cost, good in robustness, high in accuracy, and has wide applications.
步骤2：旋翼无人机1的任务结束后，利用旋翼无人机1现有的返航和跟随系统，使旋翼无人机1跟随机动车5飞行，此时由于GPS精度限制，跟随的精度大约为2米左右；同时机载计算机3控制机载云台相机2绕俯仰轴在下半圆匀速转动，并对来自云台相机的图像进行识别，判断是否找到二维码；如图4所示，为本发明识别多层嵌套标识中二维码的流程图，其中具体识别步骤如下:Step 2: After the task of the rotor UAV 1 is over, use the existing return and follow system of the rotor UAV 1 to make the rotor UAV 1 follow the motor vehicle 5 to fly. At this time, due to the limitation of GPS accuracy, the following accuracy is about is about 2 meters; at the same time, the on-board computer 3 controls the on-board pan-tilt camera 2 to rotate at a constant speed in the lower semicircle around the pitch axis, and recognizes the image from the pan-tilt camera to determine whether a two-dimensional code is found; as shown in Figure 4, it is The present invention recognizes the flow chart of the two-dimensional code in the multi-layer nested mark, and wherein concrete recognition steps are as follows:
步骤21：RGB彩色图像预处理，将机载云台相机2读取到的画面进行灰度化、二值化、降噪处理，得到0/1二值图，其中0代表黑色像素，1代表白色像素；Step 21: RGB color image preprocessing, grayscale, binarize, and denoise the image read by the airborne pan/tilt camera 2 to obtain a 0/1 binary image, where 0 represents black pixels and 1 represents white pixels;
步骤22：由于正方形从不同角度拍摄时，在相机画面中的形状不同，但都属于凸四边形；因此利用边界跟踪算法从0/二值图中提取画面所拍摄到的所有物体的轮廓，选取凸四边形轮廓，得到物体对应的凸四边形图像；所述凸四边形图像即为二维码的外边界；Step 22: Since the squares have different shapes in the camera screen when they are shot from different angles, they all belong to convex quadrilaterals; therefore, use the boundary tracking algorithm to extract the outlines of all objects captured in the screen from the 0/binary image, and select the convex The quadrilateral outline obtains the convex quadrilateral image corresponding to the object; the convex quadrilateral image is the outer boundary of the two-dimensional code;
所述边界跟踪算法是轮廓搜索的常用方法，其基本思想是由一个边缘点出发，依次搜索并连接相邻边缘点从而逐步检测出边界；The boundary tracking algorithm is a common method for contour search, and its basic idea is to start from an edge point, search and connect adjacent edge points in turn to gradually detect the boundary;
步骤23：通过仿射变换，将所述凸四边形图像变为正方形图像；Step 23: changing the convex quadrilateral image into a square image through affine transformation;
步骤24：将正方形图像等分为5行5列的小正方形，计算每个小正方形中1的个数；其中，如果小正方形中1的个数超过像素总数的一半，则判定该小正方形为白色，否则为黑色；Step 24: Divide the square image into small squares with 5 rows and 5 columns, and calculate the number of 1s in each small square; where, if the number of 1s in the small square exceeds half of the total number of pixels, then determine that the small square is white, otherwise black;
步骤25：采用5×5二维矩阵B＝[bij]5×5表征步骤23中的正方形图像，其中bij为二维矩阵B第i行第j列个元素，与第i行第j列小正方形对应；其中，如果小正方形为白色，则其对应二维矩阵的元素值为1；如果小正方形为黑色，则其对应二维矩阵的元素值为0；Step 25: Use a 5×5 two-dimensional matrix B=[bij ]5×5 to characterize the square image in step 23, where bij is the element of the i-th row, j-th column of the two-dimensional matrix B, and the i-th row, j-th element Columns of small squares correspond; where, if the small square is white, the element value corresponding to the two-dimensional matrix is 1; if the small square is black, the element value corresponding to the two-dimensional matrix is 0;
步骤26：将正方形图像对应的二维矩阵B与二维码对应的集合∪A中的二维矩阵进行对比；其中：Step 26: Compare the two-dimensional matrix B corresponding to the square image with the two-dimensional matrix in the set ∪A corresponding to the two-dimensional code; where:
如果二维矩阵B与集合∪A中的任意二维矩阵A完全相同，则机载云台相机2成功识别多层嵌套标识7中的二维码，并进入步骤3；其中如果识别到多个二维码，则优先使用尺寸最大大二维码；如果识别的二维码都是同样大小的二维码，则优先使用靠近多层嵌套标识7中心的二维码；如图3所示为本发明的机载云台相机2在识别范围上与现有技术的对比示意图；If the two-dimensional matrix B is exactly the same as any two-dimensional matrix A in the set ∪A, then the airborne pan-tilt camera 2 successfully recognizes the two-dimensional code in the multi-layer nested logo 7, and enters step 3; wherein if multiple If two QR codes are used, the QR code with the largest size will be used preferentially; if the recognized QR codes are all QR codes of the same size, the QR code close to the center of the multi-layer nested logo 7 will be used first; as shown in Figure 3 Shown as the comparison schematic diagram of the airborne pan-tilt camera 2 of the present invention and the prior art in the recognition range;
如果二维矩阵B与二维矩阵A不相同，则重复步骤21-25；If the two-dimensional matrix B is different from the two-dimensional matrix A, then repeat steps 21-25;
步骤3：利用机载云台相机2的内参数和畸变参数、已知的多层嵌套标识7中二维码大小和位置、二维码在机载云台相机2拍摄画面上的像素坐标以及机载云台相机2相对于旋翼无人机1的姿态角，通过梯度法寻优计算机载云台相机2相对于多层嵌套标识7的位置和姿态角；Step 3: Utilize the internal parameters and distortion parameters of the airborne PTZ camera 2, the size and position of the two-dimensional code in the known multi-layer nested logo 7, and the pixel coordinates of the two-dimensional code on the image captured by the airborne PTZ camera 2 And the attitude angle of the airborne pan-tilt camera 2 relative to the rotor UAV 1, the position and attitude angle of the computer-borne pan-tilt camera 2 relative to the multi-layer nested logo 7 are optimized by gradient method;
所述梯度法为数值计算求取最优解的常用方法；The gradient method is a common method for numerical calculation to obtain an optimal solution;
步骤4：机载计算机3根据机载云台相机2拍摄的画面和机载云台相机2相对于多层嵌套标识7的位置和姿态角，计算旋翼无人机1当前相对于多层嵌套标识7的姿态角和位置信息，从而生成控制指令控制旋翼无人机1缩小相对于多层嵌套标识7中心位置的偏差，并逐渐下降；Step 4: The onboard computer 3 calculates the position and attitude angle of the rotor UAV 1 relative to the multi-layer embedding mark 7 according to the picture taken by the on-board PTZ camera 2 and the position and attitude angle of the airborne PTZ camera 2 relative to the multi-layer embedding mark 7. Set the attitude angle and position information of the logo 7, thereby generating control instructions to control the rotor UAV 1 to reduce the deviation relative to the center position of the multi-layer nested logo 7, and gradually descend;
其中下降过程分为高处和低处两个阶段，当旋翼无人机1起落架下端距离车载铁质降落坪6超过30厘米时，旋翼无人机1沿水平方向对齐多层嵌套标识7，向多层嵌套标识7中心靠近；当旋翼无人机1与多层嵌套标识7的中心在水平方向上的偏差小于10厘米时，旋翼无人机1开始沿竖直方向缓慢下降；当旋翼无人机1起落架下端距离车载铁质降落坪6小于30厘米时，机载计算机3锁定机载云台相机2竖直向下，旋翼无人机1竖直方向快速下降；此时如果仍然能识别到二维码，则旋翼无人机1在水平方向继续对齐二维码，进一步提高降落精度。The descent process is divided into two stages: high and low. When the lower end of the landing gear of the rotor UAV 1 is more than 30 cm away from the vehicle-mounted iron landing pad 6, the rotor UAV 1 is aligned with the multi-layer nested mark 7 in the horizontal direction. , close to the center of the multi-layer nesting logo 7; when the center of the rotor UAV 1 and the multi-layer nesting logo 7 deviates less than 10 centimeters in the horizontal direction, the rotor UAV 1 begins to slowly descend in the vertical direction; When the lower end of the landing gear of the rotor UAV 1 is less than 30 centimeters from the vehicle-mounted iron landing pad 6, the onboard computer 3 locks the airborne pan-tilt camera 2 vertically downward, and the rotor UAV 1 vertically descends rapidly; at this time If the two-dimensional code can still be recognized, the rotor drone 1 continues to align the two-dimensional code in the horizontal direction to further improve the landing accuracy.
如果机动车5车速突然变化，多层嵌套标识7上的所有二维码将靠近机载云台相机2画面边缘，使机载云台相机2无法识别二维码；此时机载计算机3将发送控制指令以控制云台转动，使离相机最近的二维码始终处于机载云台相机2的视野中心，提高跟随的可靠性；If the speed of motor vehicle 5 changes suddenly, all the two-dimensional codes on the multi-layer nesting mark 7 will be close to the edge of the screen of the airborne pan-tilt camera 2, so that the airborne pan-tilt camera 2 cannot recognize the two-dimensional code; The control command will be sent to control the rotation of the gimbal, so that the QR code closest to the camera is always in the center of the field of view of the on-board gimbal camera 2, improving the reliability of following;
步骤5：当旋翼无人机1接近车载铁质降落坪6时，机载起落架磁性器件4与车载铁质降落坪6互相吸引，使旋翼无人机1稳定落在车载铁质降落坪6上，完成着陆。Step 5: When the rotor UAV 1 approaches the vehicle-mounted iron landing pad 6, the magnetic device 4 of the airborne landing gear and the vehicle-mounted iron landing pad 6 attract each other, so that the rotor UAV 1 stably lands on the vehicle-mounted iron landing pad 6 on, complete the landing.
当然，本发明还可有其他多种实施例，在不背离本发明精神及其实质的情况下，熟悉本领域的技术人员当可根据本发明作出各种相应的改变和变形，但这些相应的改变和变形都应属于本发明所附的权利要求的保护范围。Of course, the present invention can also have other various embodiments, and those skilled in the art can make various corresponding changes and deformations according to the present invention without departing from the spirit and essence of the present invention, but these corresponding Changes and deformations should belong to the scope of protection of the appended claims of the present invention.
| Application Number | Priority Date | Filing Date | Title |
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| CN201611204761.4ACN106527487A (en) | 2016-12-23 | 2016-12-23 | Autonomous precision landing system of unmanned aerial vehicle on motion platform and landing method |
| Application Number | Priority Date | Filing Date | Title |
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| CN201611204761.4ACN106527487A (en) | 2016-12-23 | 2016-12-23 | Autonomous precision landing system of unmanned aerial vehicle on motion platform and landing method |
| Publication Number | Publication Date |
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| CN106527487Atrue CN106527487A (en) | 2017-03-22 |
| Application Number | Title | Priority Date | Filing Date |
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| CN201611204761.4APendingCN106527487A (en) | 2016-12-23 | 2016-12-23 | Autonomous precision landing system of unmanned aerial vehicle on motion platform and landing method |
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| RJ01 | Rejection of invention patent application after publication | Application publication date:20170322 |