CN111080703B - Mobile robot repositioning method based on linear matching - Google Patents
Mobile robot repositioning method based on linear matchingDownload PDFInfo
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Abstract
Description
Translated fromChinese技术领域technical field
本发明属于机器人定位技术领域，提供了一种基于直线匹配的移动机器人重定位方法。The invention belongs to the technical field of robot positioning, and provides a mobile robot repositioning method based on straight line matching.
背景技术Background technique
随着科技的发展，在自动化工厂和智能仓储物流等领域，移动机器人发挥着越来越重要的作用。在某些场合，当机器人重启或突然被“绑架”到其他位置，机器人会无法定位其位姿，此时需要人为将机器人移动到初始位置重新启动后才能工作。在现有解决机器人重定位的方案中，大多是通过在环境中贴二维码或者安装UWB等辅助设备实现机器人定位，这就限制了机器人的使用范围，增加了成本。实现移动机器人在自身位姿失效或重启等异常情况能快速准确重新定位，是目前亟需解决的问题。With the development of science and technology, mobile robots are playing an increasingly important role in the fields of automated factories and intelligent warehousing and logistics. In some occasions, when the robot restarts or is suddenly "kidnapped" to another position, the robot will not be able to locate its pose. At this time, it is necessary to manually move the robot to the initial position and restart it before it can work. In the existing solutions for robot relocation, most of the robot positioning is realized by sticking a QR code in the environment or installing auxiliary equipment such as UWB, which limits the scope of use of the robot and increases the cost. It is an urgent problem to realize that the mobile robot can quickly and accurately reposition in abnormal situations such as its own posture failure or restart.
发明内容SUMMARY OF THE INVENTION
本发明实施例提供一种直线匹配的移动机器人重定位方法，在移动机器人自身位姿失效或重启的异常情况能快速准确进行重新定位。The embodiment of the present invention provides a method for relocation of a mobile robot with linear matching, which can quickly and accurately perform relocation in the abnormal situation that the mobile robot's own posture fails or restarts.
本发明是这样实现的，一种基于直线匹配的移动机器人重定位方法，所述方法具体包括如下步骤：The present invention is implemented in this way, a method for repositioning a mobile robot based on straight line matching, the method specifically includes the following steps:
S1、加载全局地图，在全局地图中提取直线，并进行存储；S1. Load the global map, extract straight lines from the global map, and store them;
S2、在局部地图中提取直线，筛选出最佳的交叉直线对及平行直线对；S2. Extract straight lines from the local map, and screen out the best intersecting straight line pairs and parallel straight line pairs;
S3、检测局部地图中是否存在最佳交叉直线对，若检测结果为是，则执行步骤S4，若检测结果为否，则执行步骤S5；S3, detect whether there is an optimal intersecting straight line pair in the local map, if the detection result is yes, then execute step S4, if the detection result is no, then execute step S5;
S4、将局部地图中的最佳交叉直线对与全局地图中的直线对进行匹配，获取最优的旋转矩阵R及平移向量T，基于最优的旋转矩阵R及平移向量T对移动机器人进行定位；S4. Match the best intersecting line pair in the local map with the line pair in the global map, obtain the optimal rotation matrix R and translation vector T, and locate the mobile robot based on the optimal rotation matrix R and translation vector T ;
S5、将局部地图中的最佳平行直线对与全局地图中的直线对进行匹配，获取最优的旋转矩阵R及平移向量T，基于最优的旋转矩阵R及平移向量T对移动机器人进行定位。S5. Match the best parallel straight line pair in the local map with the straight line pair in the global map, obtain the optimal rotation matrix R and translation vector T, and locate the mobile robot based on the optimal rotation matrix R and translation vector T .
进一步的，全局地图中直线对的提取方法具体包括如下步骤：Further, the method for extracting line pairs in the global map specifically includes the following steps:
S11、对全局地图进行边缘检测，转化为二值化图像，利用霍夫变换检测出二值化图像中的所有直线段；S11, perform edge detection on the global map, convert it into a binarized image, and use Hough transform to detect all straight line segments in the binarized image;
S12、对全局地图提取到的所有直线段进行滤波，保留长度大于最小长度阈值且小于最大长度阈值的直线段；S12, filtering all straight line segments extracted from the global map, and retaining straight line segments whose length is greater than the minimum length threshold and less than the maximum length threshold;
S13、对滤波后的直线段进行直线拟合，拟合后的直线即为全局地图中提取到的直线。S13. Perform straight line fitting on the filtered straight line segment, and the fitted straight line is the straight line extracted from the global map.
进一步的，所述直线拟合方法具体如下：Further, the straight line fitting method is specifically as follows:
将滤波后的直线段两两组成直线对，计算各直线对间的夹角及距离，将夹角小于角度阈值一，且直线距离小于距离阈值的直线对进行直线拟合；The filtered straight line segments are formed into straight line pairs, and the included angle and distance between each straight line pair are calculated, and the straight line pair whose included angle is less than the angle threshold value 1 and the straight line distance is less than the distance threshold value is fitted with a straight line;
两直线间的距离即为两直线中点间的距离。The distance between two straight lines is the distance between the midpoints of the two straight lines.
进一步的，局部地图中的直线对的提取方法具体包括如下步骤：Further, the method for extracting straight line pairs in the local map specifically includes the following steps:
S11、对局部地图进行边缘检测，转化为二值化图像，利用霍夫变换检测出二值化图像中的所有直线段；S11, perform edge detection on the local map, convert it into a binarized image, and use Hough transform to detect all straight line segments in the binarized image;
S12、对局部地图提取到的所有直线段进行滤波，保留长度大于最小长度阈值且小于最大长度阈值的直线段；S12, filtering all straight line segments extracted from the local map, and retaining straight line segments whose length is greater than the minimum length threshold and less than the maximum length threshold;
S13、对滤波后的直线段进行直线拟合，拟合后的直线即为全局地图中提取到的直线。S13. Perform straight line fitting on the filtered straight line segment, and the fitted straight line is the straight line extracted from the global map.
进一步的，所述直线拟合方法具体如下：Further, the straight line fitting method is specifically as follows:
将滤波后的直线段两两组成直线对，计算各直线对间的夹角及距离，将夹角小于角度阈值一，且直线距离小于距离阈值的直线对进行直线拟合；The filtered straight line segments are formed into straight line pairs, and the included angle and distance between each straight line pair are calculated, and the straight line pair whose included angle is less than the angle threshold value 1 and the straight line distance is less than the distance threshold value is fitted with a straight line;
两直线间的距离即为两直线中点间的距离。The distance between two straight lines is the distance between the midpoints of the two straight lines.
进一步的，基于最佳交叉直线对的匹配过程具体包括如下步骤：Further, the matching process based on the best intersecting straight line pair specifically includes the following steps:
S41、确定最佳交叉直线对中两条直线的交点，以交点作为起点，远离交点的两直线端点为终点，生成的两条向量定义为最佳交叉矢量对；S41. Determine the intersection point of the two straight lines in the best intersecting straight line pair, take the intersection point as the starting point, and the endpoints of the two straight lines far from the intersection point as the end point, and define the two generated vectors as the best intersecting vector pair;
S42、获取全局地图中的所有交叉直线对，以交点作为起点，远离交点的两直线端点为终点，生成的两条向量定义为交叉矢量对；S42. Acquire all intersecting straight line pairs in the global map, take the intersection point as the starting point, the endpoints of the two straight lines far from the intersection point as the end point, and define the two generated vectors as intersecting vector pairs;
S42、分别计算局部地图中的最佳交叉矢量对相对于全局地图中各交叉矢量对的旋转矩阵R及平移向量T；S42, respectively calculating the rotation matrix R and translation vector T of the best cross-vector pair in the local map relative to each cross-vector pair in the global map;
S43、通过似然域模型对各组旋转矩阵R及平移向量T进行打分，打分最高的旋转矩阵R及平移向量T即为最优旋转矩阵R及平移向量T。S43. Score each group of rotation matrices R and translation vectors T by using the likelihood domain model, and the rotation matrix R and translation vector T with the highest score are the optimal rotation matrix R and translation vector T.
进一步的，基于最佳平行直线对的匹配过程具体包括如下步骤：Further, the matching process based on the best parallel line pair specifically includes the following steps:
S51、定义局部地图中最佳平行直线对的方向，并赋予全局地图中各组平行直线对相同方向；S51. Define the direction of the best parallel straight line pair in the local map, and assign the same direction to each group of parallel straight line pairs in the global map;
S52、获取各组平行直线对的最高似然得分及其对应的旋转矩阵R及平移向量T；S52, obtain the highest likelihood score of each group of parallel straight line pairs and its corresponding rotation matrix R and translation vector T;
S53、获取各组平行直线对的最高似然得分的最大值及其对应的旋转矩阵R及平移向量T，该旋转矩阵R及平移向量T即为最优旋转矩阵R及平移向量T。S53: Obtain the maximum value of the highest likelihood score of each group of parallel straight line pairs and the corresponding rotation matrix R and translation vector T, where the rotation matrix R and translation vector T are the optimal rotation matrix R and translation vector T.
进一步的，所述平行直线对的最高似然得分的获取方法具体如下：Further, the method for obtaining the highest likelihood score of the pair of parallel lines is as follows:
S521、计算局部地图中的最佳平行直线对相对于全局地图中平行直线对的旋转矩阵R；S521, calculate the rotation matrix R of the best parallel line pair in the local map relative to the parallel line pair in the global map;
S522、提取最佳平行直线对中一条直线的起始点，提取全局地图中平行直线对中的一条直线，从该直线的起始点开始，依次遍历该直线上的每个像素点，计算出每个像素点相对于起始点的平移向量T；S522: Extract the starting point of a straight line in the best parallel straight line pair, extract a straight line in the parallel straight line pair in the global map, start from the starting point of the straight line, traverse each pixel point on the straight line in turn, and calculate each pixel point on the straight line. The translation vector T of the pixel point relative to the starting point;
S523、通过似然域对各组旋转矩阵R及平移向量T进行打分，最高打分即为对应平行直线对的最高似然得分。S523. Score each group of rotation matrices R and translation vectors T through the likelihood domain, and the highest score is the highest likelihood score corresponding to the pair of parallel straight lines.
本发明提供的基于直线匹配的移动机器人重定位方法在移动机器人出现“绑架”或重启等异常情况后，能够快速进行重定位。The mobile robot relocation method based on straight line matching provided by the present invention can quickly perform relocation after abnormal situations such as "kidnapping" or restarting of the mobile robot.
附图说明Description of drawings
图1为本发明实施例提供的基于直线匹配的移动机器人重定位方法流程图。FIG. 1 is a flowchart of a method for relocation of a mobile robot based on line matching provided by an embodiment of the present invention.
具体实施方式Detailed ways
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.
图1为本发明实施例提供的基于直线匹配的移动机器人重定位方法流程图，该方法具体包括如下步骤：1 is a flowchart of a method for relocation of a mobile robot based on line matching provided by an embodiment of the present invention, and the method specifically includes the following steps:
S1、加载全局地图，在全局地图中提取直线端，并进行存储至直线集合，之后的匹配操作无需重复进行全局地图中的直线提取操作，只需从直线集合中直接读取即可。S1. Load the global map, extract the straight line ends in the global map, and store them in the straight line set. The subsequent matching operation does not need to repeat the straight line extraction operation in the global map, but only needs to read directly from the straight line set.
在本发发明实施例中，全局地图中的直线段提取方法具体包括如下步骤：In the embodiment of the present invention, the method for extracting straight line segments in the global map specifically includes the following steps:
S11、对全局地图进行边缘检测，转化为二值化图像，利用霍夫变换检测出二值化图像中的所有直线段，每条直线段采用四个元素(x1,y1,x2,y2)表示，其中(x1,y1)和(x2,y2)分别表示直线段的起始点和结束点；S11. Perform edge detection on the global map, convert it into a binarized image, use Hough transform to detect all straight line segments in the binarized image, and each straight line segment adopts four elements (x1 , y1 , x2 , y2 ), where (x1 , y1 ) and (x2 , y2 ) represent the starting point and the ending point of the straight line segment, respectively;
S12、对全局地图提取到的所有直线段进行滤波，即保留长度大于最小长度阈值且小于最大长度阈值的直线段；S12, filtering all straight line segments extracted from the global map, that is, retaining straight line segments whose length is greater than the minimum length threshold and less than the maximum length threshold;
S13、对滤波后的直线段进行直线拟合，拟合后的直线即为全局地图中的直线段，其拟合方法具体如下：S13. Perform straight line fitting on the filtered straight line segment. The fitted straight line is the straight line segment in the global map. The fitting method is as follows:
将滤波后的直线段两两组成直线对，计算各直线对间的夹角及距离，将夹角小于角度阈值一，且直线距离小于距离阈值的直线对进行直线拟合；两直线间的距离即为两直线中点间的距离。Combine the filtered straight line segments into straight line pairs, calculate the included angle and distance between the straight line pairs, and perform straight line fitting on the straight line pairs whose included angle is less than the angle threshold value 1 and the straight line distance is less than the distance threshold value; the distance between the two straight lines is the distance between the midpoints of the two straight lines.
S2、在局部地图中提取直线，筛选出最佳交叉直线对及最佳平行直线对；S2. Extract straight lines from the local map, and filter out the best intersecting straight line pair and the best parallel straight line pair;
在本发明实施例中，利用激光传感器获取当前帧数据并转换为局部图像，确定激光传感器当前位置为图像的中心位置，局部地图中的直线提取方法具体包括如下步骤：In the embodiment of the present invention, the current frame data is obtained by using a laser sensor and converted into a local image, and the current position of the laser sensor is determined as the center position of the image. The method for extracting a straight line in the local map specifically includes the following steps:
S21、对局部地图进行边缘检测，转化为二值化图像，利用霍夫变换检测出二值化图像中的所有直线段，每条直线段采用四个元素(x1,y1,x2,y2)表示，其中(x1,y1)和(x2,y2)分别表示直线段的起始点和结束点；S21. Perform edge detection on the local map, convert it into a binarized image, and use Hough transform to detect all straight line segments in the binarized image. Each straight line segment uses four elements (x1 , y1 , x2 , y2 ), where (x1 , y1 ) and (x2 , y2 ) represent the starting point and the ending point of the straight line segment, respectively;
S22、对局部地图提取到的所有直线段进行滤波，即保留长度大于最小长度阈值且小于最大长度阈值的直线段；S22, filtering all straight line segments extracted from the local map, that is, retaining straight line segments whose length is greater than the minimum length threshold and less than the maximum length threshold;
S23、对滤波后的直线段进行直线拟合，拟合后的直线即为局部地图中的直线，其拟合方法具体如下：S23. Perform straight line fitting on the filtered straight line segment. The fitted straight line is the straight line in the local map. The fitting method is as follows:
将滤波后的直线段两两组成直线对，计算各直线对间的夹角及距离，将夹角小于角度阈值一，且直线距离小于距离阈值的直线对进行直线拟合；两直线间的距离即为两直线中点间的距离。Combine the filtered straight line segments into straight line pairs, calculate the included angle and distance between the straight line pairs, and perform straight line fitting on the straight line pairs whose included angle is less than the angle threshold value 1 and the straight line distance is less than the distance threshold value; the distance between the two straight lines is the distance between the midpoints of the two straight lines.
在本发明实施例中，对局部地图中进行直线提取操作后，提取到若干条直线，将若干条直线两两进行组合，形成若干组直线对，计算直线对间的夹角，若夹角大于角度预设值，则判定该直线对为交叉直线对，若夹角小于或等于角度预设值，则判定该直线对为平行直线对；In the embodiment of the present invention, after performing a straight line extraction operation on the local map, several straight lines are extracted, and several straight lines are combined in pairs to form several sets of straight line pairs, and the included angle between the straight line pairs is calculated. If the included angle is greater than If the angle preset value is set, the straight line pair is determined to be a cross straight line pair, and if the included angle is less than or equal to the angle preset value, the straight line pair is determined to be a parallel straight line pair;
针对交叉直线对：提取夹角大于角度阈值二的交叉直线对，检测该交叉直线对中短直线段的距离，将距离最长的短直线段所在的交叉直线对作为最佳交叉直线对；For the intersecting straight line pair: extract the intersecting straight line pair whose included angle is greater than the angle threshold 2, detect the distance of the short straight line segment in the intersecting straight line pair, and take the intersecting straight line pair where the short straight line segment with the longest distance is located as the best intersecting straight line pair;
针对平行直线对：将角度最小的平行直线对作为最佳平行直线对。For parallel line pairs: The parallel line pair with the smallest angle is regarded as the best parallel line pair.
S3、检测局部地图中是否存在最佳交叉直线对，若检测结果为是，则执行步骤S4，若检测结果为否，则执行步骤S5；S3, detect whether there is an optimal intersecting straight line pair in the local map, if the detection result is yes, then execute step S4, if the detection result is no, then execute step S5;
S4、将局部地图中的最佳交叉直线对与全局地图中的直线对进行匹配，获取最优的旋转矩阵R及平移向量T，基于最优的旋转矩阵R及平移向量T对移动机器人进行定位；S4. Match the best intersecting line pair in the local map with the line pair in the global map, obtain the optimal rotation matrix R and translation vector T, and locate the mobile robot based on the optimal rotation matrix R and translation vector T ;
在本发明实施例中，全局地图中的直线对是指全局地图中两两直线组合而成的，基于最佳交叉直线对的匹配过程具体包括如下步骤：In the embodiment of the present invention, the straight line pair in the global map refers to a combination of two straight lines in the global map, and the matching process based on the best intersecting straight line pair specifically includes the following steps:
S41、确定最佳交叉直线对中两条直线的交点，以交点作为起点，远离交点的两直线端点为终点，生成的两条向量定义为最佳交叉矢量对；S41. Determine the intersection point of the two straight lines in the best intersecting straight line pair, take the intersection point as the starting point, and the endpoints of the two straight lines far from the intersection point as the end point, and define the two generated vectors as the best intersecting vector pair;
S42、获取全局地图中的所有交叉直线对，以交点作为起点，远离交点的两直线端点为终点，生成的两条向量定义为交叉矢量对；S42. Acquire all intersecting straight line pairs in the global map, take the intersection point as the starting point, and the endpoints of the two straight lines far from the intersection point as the end point, and define the two generated vectors as intersecting vector pairs;
S42、分别计算局部地图中的最佳交叉矢量对相对于全局地图中各交叉矢量对的旋转矩阵R及平移向量T；S42, respectively calculating the rotation matrix R and translation vector T of the best cross-vector pair in the local map relative to each cross-vector pair in the global map;
S43、通过似然域对各组旋转矩阵R及平移向量T进行打分，打分最高的旋转矩阵R及平移向量T即为最优的旋转矩阵R及平移向量T。S43. Score each group of rotation matrices R and translation vectors T through the likelihood domain, and the rotation matrix R and translation vector T with the highest scores are the optimal rotation matrix R and translation vector T.
在本发明实施例中，旋转矩阵R及平移向量T的计算公式具体如下：In the embodiment of the present invention, the calculation formulas of the rotation matrix R and the translation vector T are as follows:
其中，VL表示局部地图中直线组成的向量，VW表示全局地图直线组成的向量，PL表示局部地图直线上的点坐标，PW表示全局地图直线上的点坐标。Among them,VL represents the vector composed of straight lines in the local map, VW represents the vector composed of the global map lines,PL represents the point coordinates on the local map line, andPW represents the point coordinates on the global map line.
S5、将局部地图中的最佳平行直线对与全局地图中的直线对进行匹配，获取最优的旋转矩阵R及平移向量T，基于最优的旋转矩阵R及平移向量T对移动机器人进行定位；S5. Match the best parallel straight line pair in the local map with the straight line pair in the global map, obtain the optimal rotation matrix R and translation vector T, and locate the mobile robot based on the optimal rotation matrix R and translation vector T ;
在本发明实施例中，基于最佳平行直线的匹配过程具体包括如下步骤：In the embodiment of the present invention, the matching process based on the best parallel line specifically includes the following steps:
S51、定义局部地图中最佳平行直线对的方向，并赋予全局地图中各组平行直线对相同方向；S51. Define the direction of the best parallel straight line pair in the local map, and assign the same direction to each group of parallel straight line pairs in the global map;
S52、获取各组平行直线的最高似然得分及其对应的旋转矩阵R及平移向量T，最高似然得分是指通过似然模型计算出的各组平行直线的最高得分，其获取方法具体如下：S52. Obtain the highest likelihood score of each group of parallel lines and the corresponding rotation matrix R and translation vector T. The highest likelihood score refers to the highest score of each group of parallel lines calculated by the likelihood model, and the acquisition method is as follows :
S521、计算局部地图中的最佳平行直线对相对于全局地图中平行直线对的旋转矩阵R，利用VL＝R·VW求解旋转矩阵R，VL表示局部地图直线组成的向量，VW表示全局地图直线组成的向量；S521. Calculate the rotation matrix R of the best parallel line pair in the local map relative to the parallel line pair in the global map, and useVL =R·VW to solve the rotation matrix R, whereVL represents a vector composed of local map lines, andVW Represents a vector composed of straight lines on the global map;
S522、提取局部地图中一条直线的起始点，提取全局地图中平行直线对中的一条直线，从该直线的起始点开始，依次遍历该直线上的每个像素点，计算出每个像素点相对于起始点的平移向量T，利用公式T＝PL-R·PW，得到每个像素点对应的平移向量T。S522, extracting the starting point of a straight line in the local map, extracting a straight line in the pair of parallel straight lines in the global map, starting from the starting point of the straight line, traversing each pixel point on the straight line in turn, and calculating the relative relative value of each pixel point From the translation vector T at the starting point, the translation vector T corresponding to each pixel is obtained by using the formula T=PL -R·PW .
S523、通过似然域对各组旋转矩阵R及平移向量T进行打分最高打分即为对应平行直线对的最高似然得分。S523 , scoring each group of rotation matrices R and translation vectors T through the likelihood domain. The highest score is the highest likelihood score of the corresponding pair of parallel straight lines.
S53、获取各组平行直线对最高得分的最高值及其对应的旋转矩阵R及平移向量T，将该旋转矩阵R及平移向量T作为最优旋转矩阵R及平移向量T。S53 , obtain the highest value of the highest score of each group of parallel straight line pairs and the corresponding rotation matrix R and translation vector T, and use the rotation matrix R and translation vector T as the optimal rotation matrix R and translation vector T.
本发明提供的基于直线匹配的移动机器人重定位方法在移动机器人出现“绑架”或重启等异常情况后，能够快速进行重定位。The mobile robot relocation method based on straight line matching provided by the present invention can quickly perform relocation after abnormal situations such as "kidnapping" or restarting of the mobile robot.
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本发明的保护范围之内。The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention shall be included in the protection of the present invention. within the range.
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