阅读说明：本技术 一种适用于输电巡检工作的末端路径导航方法 (Tail end path navigation method suitable for power transmission inspection work ) 是由 李平 李从林 张勇 吴召军 任延明 米军平 葛扬 布天文 任勇超 呼延庆 唐宏 于 2019-03-21 设计创作，主要内容包括：本发明公开了一种适用于输电巡检工作的末端路径导航方法,主要解决了最后一段(末端)路径的导航问题,提高了日常运行检修和巡视的工作效率,避免了防止走错路、耗时耗力等问题,达到了对工作和人员的可控管理。其实现步骤为：(1)利用多传感器对局部未知环境进行探测并构建局部环境模型；(2)采用自适应栅格方法构建全局地图；(3)基于改进的BFS算法实现路径导航。本发明可以实现移动巡检终端在局部未知环境下的快速路径导航功能,帮助巡检工作人员准确、快速、安全地到达目的地,并且把学习到的末端路径规划路线记录下来传回给控制台,方便下次巡检任务的执行。(The invention discloses a tail end path navigation method suitable for power transmission inspection work, which mainly solves the navigation problem of the last section (tail end) path, improves the working efficiency of daily operation maintenance and inspection, avoids the problems of preventing walking by mistake, consuming time and labor and the like, and achieves the controllable management of work and personnel. The method comprises the following implementation steps: (1) detecting a local unknown environment by using a plurality of sensors and constructing a local environment model; (2) constructing a global map by adopting a self-adaptive grid method; (3) and realizing path navigation based on the improved BFS algorithm. The invention can realize the rapid path navigation function of the mobile inspection terminal under the local unknown environment, help the inspection staff to accurately, rapidly and safely reach the destination, and return the learned tail end path planning route to the console, thereby facilitating the execution of the next inspection task.)

1. A tail end path navigation method suitable for power transmission inspection work comprises the following steps:

(1) detecting a local unknown environment by using multiple sensors and constructing a local environment model:

(1a) at the position of an inspection worker or a mobile inspection terminal, the camera and the laser sensor are kept at fixed positions and angles to detect the front environment. Smoothing the frame image obtained by the camera by adopting an improved median filtering method;

(1b) on the basis of obtaining the image, an improved canny algorithm is applied to finish the image edge detection to obtain an image containing the object edge;

(1c) setting a threshold pixel, introducing threshold processing to reduce noise of a result image, and returning the approximate position coordinates of the obstacle and the angle relative to the robot according to the result image;

(1d) and measuring distance information within a certain range of the angle in front by the laser sensor, judging whether an obstacle exists or not by combining the obstacle, and converting the measured distance value d of the laser sensor into position information relative to the mobile inspection terminal through coordinate conversion if the obstacle exists. Wherein, the coordinate conversion formula is as follows:

wherein, (x1, y1) is the position of the obstacle in the world coordinate system; (x, y) and alpha respectively represent the position and the course angle of the central point of the mobile inspection terminal in a world coordinate system; d and beta are respectively the distance of the obstacle detected by the laser sensor and the included angle between the right front of the mobile inspection terminal and the fed back laser beam;

(1e) and constructing a three-dimensional local environment model by adopting an extended modeling idea. And (3) setting up a three-dimensional model in a real environment by using an adjacent rectangular frame and adopting a simple plane extension method, wherein the complete information of the obstacle is gradually detected along with the continuous update of the current position.

(2) Constructing a local map by adopting a self-adaptive grid method:

(2a) projecting the three-dimensional local environment model obtained in the step (1) to the xoy plane (ground) to obtain a two-dimensional local map;

(2b) and (3) performing grid division on the projection drawing obtained in the previous step, wherein 1 represents an obstacle grid, and 0 represents a free grid. The adaptive grid division method based on the quadtree is adopted, namely, the grid size is dynamically adjusted according to the distribution situation of the obstacles in the environment to perform map creation. In the area with fewer obstacles, the storage space is reduced and the calculation efficiency is improved by increasing the size of the grid; in areas where obstacles are concentrated, the grid size is smaller to improve the accuracy of the map model and calculations.

(3) Realizing path navigation based on an improved BFS algorithm:

(3a) in the obtained grid map, setting a distance threshold value by taking the grid where the current position is located as the center, and selecting one grid within the distance threshold value range as a next moving target;

(3b) a grid is selected using a modified breadth search first (BFS) algorithm. The original BFS algorithm selects the grid closest to the current location (grid), and in the improved BFS algorithm herein, the selection criteria of this target grid are: taking score as d1 (distance of grid to final target) + d2 (distance of current position to grid) which is the smallest and can reach (can cross obstacle);

(3c) and (4) updating the current position to be the position of the grid obtained in the last step, and repeating the steps (3-1) and (3-2) until the destination point is reached.

2. The method for navigating the tail end path suitable for the power transmission inspection work according to claim 1, wherein the improved median filtering algorithm in the step (1) comprises the following steps: on the basis of 3-by-3 windows, the correlation with the adjacent pixels is increased in the horizontal direction and the vertical direction.

3. The method for navigating the tail end path suitable for the power transmission inspection work according to claim 1, wherein the step of performing the edge detection by adopting a canny algorithm in the step (1) comprises the following steps:

(1) carrying out image smoothing processing;

(2) calculating the amplitude and the direction of the gradient by adopting a first-order partial derivative finite difference method;

(3) non-maxima suppression;

(4) thresholding is connected to the edge.

4. The method for navigating the tail end path suitable for the transmission inspection work according to claim 1, wherein the step (2) of the self-adaptive grid division comprises the following steps:

(1) equally dividing the grid map into four parts, and checking the grid attribute block by block (0/1);

(2) if all grids of the respective regions have the same value or differ within a specified threshold, the sub-region is not partitioned, otherwise, the partitioning of the sub-region is continued until each sub-block contains only the same attribute value.

Technical Field

The invention designs a tail end path navigation method suitable for an unknown environment, which adopts a multi-sensor view fusion method to improve the detection precision of the environment, realizes the function of planning the path of a local unknown environment on the basis, can be used for exploring a new path in unknown environments such as rural roads, mountain roads and the like in the inspection work of a power transmission line, and improves the working efficiency of daily operation, maintenance and inspection.

Background

The power transmission operation inspection and patrol positioning management system has a vital practical value for the daily operation and maintenance work of power transmission. When the inspection working group receives the emergency repair task, the inspection working group can drive to a high-speed roadside or a provincial highway roadside close to the task by a conventional method, but the next road is not a navigation path or even has no path at all, and how to solve the navigation of the last section (tail end) is the most practical problem. Meanwhile, due to the lack of support of the mobile terminal, the inspection personnel cannot safely transmit information and return on-site photos in real time, and the condition that the inspection personnel cannot work on time, comprehensively and accurately can not be caused, so that the management personnel cannot timely, accurately and comprehensively know the inspection positioning and track conditions of the inspection personnel, and cannot make reasonable decisions in time.

At present, the operation and maintenance technology and the device of some transmission lines in the power system are more or less related to real-time navigation in practice, and particularly, some online power operation and maintenance systems and GPS emergency repair positioning systems. While these systems serve some purpose, they have not been fully satisfactory. The general problems are as follows: the information which can be remotely inquired is less; the positioning and track conditions of the inspection personnel are difficult to be managed accurately; lack of detailed geographic information, etc.

In view of the above, the invention realizes the terminal path navigation function of the power transmission inspection mobile terminal based on the related technologies such as environment modeling and path planning, can effectively improve the working efficiency of daily operation maintenance and inspection, solves the problems of preventing walking by mistake, consuming time and labor and the like, achieves the controllable management of work and personnel, and has very important significance for the daily work management of power transmission inspection.

Disclosure of Invention

The invention provides a tail end path navigation method suitable for power transmission inspection work, aiming at the defects of the existing power transmission inspection and positioning management system in the aspect of work efficiency. The invention realizes the function of terminal path navigation of the power transmission mobile inspection terminal, and the specific flow is shown in figure 1.

The method comprises the following implementation steps:

(1) detecting local unknown environment by utilizing multiple sensors and constructing local environment model

Aiming at the current surrounding environment of the inspection staff or the mobile terminal, a method of combining a visual sensor and a laser sensor is adopted for detection. The general position of the obstacle is determined by the information of the vision sensor, the obstacle distance is detected by the laser sensor, the obstacle coordinate is determined by combining the vision sensor and the laser sensor, and a local environment model is constructed on the basis.

(2) And constructing a local map by adopting a self-adaptive grid method.

Aiming at the processing result of the last step, the self-adaptive grid modeling method is adopted to perform grid division on the global map, the area with few obstacles is represented by a large grid, and the area with complex obstacles is divided by a small grid.

(3) And realizing path navigation based on the improved BFS algorithm.

In the obtained grid map, taking the grid in which the current position is located as the center, selecting the next grid to be moved according to a certain rule, and repeating the steps until the final destination is reached.

The invention can realize the rapid path navigation function of the mobile inspection terminal under the local unknown environment, help the inspection staff to accurately, rapidly and safely reach the destination, and return the learned tail end path planning route to the console, thereby facilitating the execution of the next inspection task.

Drawings

FIG. 1 is a flow chart of an implementation of the present invention

FIG. 2 is a flow chart of the modified canny algorithm

FIG. 3 is an improved median filter window template

FIG. 4 is a simulation diagram of the end path navigation result

Detailed Description

The invention is further described below with reference to the accompanying drawings.

Referring to fig. 1, the present invention is embodied as follows.

Step 1, detecting a local unknown environment by using multiple sensors and constructing a local environment model.

(1-1) at the position where the inspection worker or the mobile inspection terminal is located, the camera and the laser sensor keep fixed positions and angles to detect the front environment. Smoothing the frame image obtained by the camera by adopting an improved median filtering method;

(1-2) on the basis of the obtained image, completing image edge detection by applying an improved canny algorithm to obtain an image containing the edge of the object;

(1-3) setting a threshold pixel, introducing threshold processing to reduce noise of a result image, and returning the approximate position coordinates of the obstacle and the angle relative to the robot according to the result image;

and (1-4) measuring distance information within a certain range of the angle in front by the laser sensor, judging whether obstacles exist or not by combining obstacles, and converting the measured distance value d of the laser sensor into position information relative to the mobile inspection terminal through coordinate conversion if the obstacles exist. Wherein, the coordinate conversion formula is as follows:

wherein, (x1, y1) is the position of the obstacle in the world coordinate system; (x, y) and alpha respectively represent the position and the course angle of the central point of the mobile inspection terminal in a world coordinate system; d and beta are respectively the distance of the obstacle detected by the laser sensor and the included angle between the right front of the mobile inspection terminal and the fed back laser beam;

and (1-5) constructing a three-dimensional local environment model by adopting an extended modeling idea. And (3) setting up a three-dimensional model in a real environment by using an adjacent rectangular frame and adopting a simple plane extension method, wherein the complete information of the obstacle is gradually detected along with the continuous update of the current position.

And 2, constructing a local map by adopting a self-adaptive grid method.

(2-1) projecting the three-dimensional local environment model obtained in the step (1) to the xoy plane (ground) to obtain a two-dimensional local map;

and (2-2) performing grid division on the projection drawing obtained in the previous step, wherein 1 represents an obstacle grid, and 0 represents a free grid. The adaptive grid division method based on the quadtree is adopted, namely, the grid size is dynamically adjusted according to the distribution situation of the obstacles in the environment to perform map creation. In the area with fewer obstacles, the storage space is reduced and the calculation efficiency is improved by increasing the size of the grid; in areas where obstacles are concentrated, the grid size is smaller to improve the accuracy of the map model and calculations. The method comprises the following specific steps: (a) equally dividing the grid map into four parts, and checking the grid attribute block by block (0/1); (b) if all grids of the respective regions have the same value or differ within a specified threshold, the sub-region is not partitioned, otherwise, the partitioning of the sub-region is continued until each sub-block contains only the same attribute value.

And 3, realizing path navigation based on the improved BFS algorithm.

And (3-1) in the obtained grid map, setting a distance threshold value by taking the grid in which the current position is positioned as the center, and selecting one grid within the distance threshold value range as a next moving target.

And (3-2) selecting the grids by adopting a modified breadth search first (BFS) algorithm. The original BFS algorithm selects the grid closest to the current location (grid), and in the improved BFS algorithm herein, the selection criteria of this target grid are: taking score as d1 (distance of grid to final target) + d2 (distance of current position to grid) which is the smallest and can reach (can cross obstacle);

and (3-3) updating the current position to be the position of the grid obtained in the last step, and repeating the steps (3-1) and (3-2) until the destination point is reached.

Description of the embodiments

FIG. 4 is a simulation diagram of the algorithm of the present invention. Dividing a two-dimensional projection graph of the local environment model by using an adaptive grid method, selecting a grid center within a threshold value (an optimal threshold value can be selected through experimental tests) from a current position as a candidate of a next moving position, and selecting a grid center with the minimum score (the distance from a grid to a final target and the distance from the current position to the grid). As shown in fig. 4, the positions pointed by the arrows represent all the candidate moving objects, wherein the positions pointed by the solid arrows represent the optimally selected moving objects. And after the range of the current local environment is finished, updating the current position, reestablishing the local environment model, and carrying out next selection.