Positioning method and device, equipment, storage medium and product

Abstract

The invention discloses a positioning method and device, equipment, a storage medium and a product, and relates to the technical field of data processing, and the positioning method comprises the steps: collecting the current environment information, and determining the current local map information according to the current environment information; matching the local map information with a preset global map to obtain a matching result; determining a rough position based on the matching result, and determining relative position information according to the rough position and the current environment information; and positioning according to the relative position information and the preset global map to obtain a positioning result. The rough position is determined according to the matching of the local map and the global map, then the relative position information is determined according to the rough position and the current environment information, and positioning is carried out according to the relative position information and the preset global map. According to the method, accurate positioning can be carried out when the GPS signal is weak.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to positioning methods, devices, equipment, storage media and products. Background Art

[0002] Robot inspection has a wide range of application scenarios, covering inspections in high and low voltage distribution rooms, industrial parks, and automated inspections in various industrial fields. For example, in industrial park inspections, industrial park inspection robots have brought many conveniences and benefits to industrial park management. These robots can effectively replace security personnel for routine inspections. For mountain inspections, inspection robots can accurately identify abnormal situations such as fires. At the same time, they can also monitor smoke concentrations in real time, and when the smoke concentration exceeds the specified threshold, they can take real-time photos of the scene and transmit them back to the terminal, and sound an alarm.

[0003] In conventional open park inspections, the inspection robot can be positioned through GPS and other positioning methods. However, at some project sites, the area where the robot needs to inspect is a mountainous area with tall and lush trees on both sides of the road. The sky above the driving road is particularly severely blocked by branches. The GPS signal is sometimes available and sometimes not. The inertial navigation equipment on board cannot stably provide high-precision geographic coordinate information, causing the position of the inspection robot to keep jumping. Therefore, how to accurately position the inspection robot in the scenario of weak GPS signals has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The main purpose of this application is to provide a positioning method, device, equipment, storage medium and product, aiming to solve the technical problem of low positioning efficiency of inspection robots in signal-free scenarios.

[0005] To achieve the above purpose, the present application proposes a positioning method, which includes:

[0006] Collecting current environment information, and determining the current local map information according to the current environment information;

[0007] Matching the local map information with a preset global map to obtain a matching result;

[0008] Determine a rough position based on the matching result, and determine relative position information according to the rough position and the current environment information;

[0009] Positioning is performed according to the relative position information and the preset global map to obtain a positioning result.

[0010] Optionally, the step of determining relative position information according to the rough position and the current environment information includes:

[0011] Determine a target feature point according to the rough position;

[0012] Relative position information relative to the target feature point is determined based on the current environment information.

[0013] Optionally, the step of performing positioning according to the relative position information and the preset global map to obtain a positioning result includes:

[0014] Determine the absolute coordinates of the target feature point according to the preset global map;

[0015] Determine the offset information of the inspection robot relative to the target feature point according to the relative position information;

[0016] The absolute coordinates of the inspection robot are determined according to the offset information and the absolute coordinates.

[0017] Optionally, before the step of collecting current environment information and determining the current local map information according to the current environment information, the method further includes:

[0018] When receiving a path planning task, decomposing the path planning task to obtain path planning subtasks;

[0019] Performing path planning based on the path planning subtask by using a preset path planning algorithm to obtain path information corresponding to the path planning subtask;

[0020] determining a moving speed according to the path;

[0021] A motion trajectory is determined according to the path information, the moving speed, and the path planning task, and the path planning task is performed based on the motion trajectory.

[0022] Optionally, when receiving the path planning task, decomposing the path planning task to obtain path planning subtasks includes:

[0023] When receiving a path planning task, determining a starting point location and an end point location according to the path planning task;

[0024] Determine the task decomposition feature points based on the starting point location, the end point location and the preset global map;

[0025] The path planning task is decomposed according to the task decomposition feature points to obtain path planning subtasks.

[0026] Optionally, after the step of performing positioning according to the relative position information and the preset global map to obtain a positioning result, the step further includes:

[0027] Determining whether a preset parking condition is currently met according to the positioning result;

[0028] When the preset parking condition is currently met, the deceleration range information is determined;

[0029] determining a driving speed based on the deceleration range information;

[0030] Slow down to stop according to the driving speed, and start a timer to record the waiting time;

[0031] When the waiting time exceeds the preset waiting time, the obstacle bypassing function is enabled.

[0032] In addition, to achieve the above-mentioned purpose, the present application also proposes a positioning device, which includes:

[0033] A collection module, used to collect current environment information and determine the current local map information according to the current environment information;

[0034] A matching module, used for matching the local map information with a preset global map to obtain a matching result;

[0035] A determination module, configured to determine a rough position based on the matching result, and determine relative position information according to the rough position and the current environment information;

[0036] The positioning module is used to perform positioning according to the relative position information and the preset global map to obtain a positioning result.

[0037] In addition, to achieve the above objectives, the present application also proposes a positioning device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the positioning method described above.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the positioning method described above are implemented.

[0039] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the positioning method described above are implemented.

[0040] The present application collects current environmental information, and determines the current local map information based on the current environmental information; matches the local map information with a preset global map to obtain a matching result; determines a rough position based on the matching result, and determines relative position information based on the rough position and the current environmental information; performs positioning based on the relative position information and the preset global map to obtain a positioning result. Since the present application determines a rough position based on matching of a local map and a global map, and then determines relative position information based on the rough position and the current environmental information, and performs positioning based on the relative position information and a preset global map, compared to the existing method of using GPS for positioning, the above method of the present application can perform precise positioning when the GPS signal is weak. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0043] Figure 1 A schematic diagram of a flow chart provided for the first embodiment of the positioning method of the present application;

[0044] Figure 2 A schematic diagram of the positioning process provided in Embodiment 1 of the positioning method of the present application;

[0045] Figure 3 A schematic diagram of a flow chart provided for the second embodiment of the positioning method of the present application;

[0046] Figure 4 A schematic diagram of a map modeling process provided for the second embodiment of the positioning method of the present application;

[0047] Figure 5 This is a schematic diagram of the module structure of the positioning device according to an embodiment of the present application;

[0048] Figure 6 Schematic diagram of the device structure of the hardware operating environment involved in the positioning method in the embodiment of the present application.

[0049] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0050] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0051] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0052] The main solution of the embodiment of the present application is: collect current environmental information, and determine the current local map information based on the current environmental information; match the local map information with the preset global map to obtain a matching result; determine a rough position based on the matching result, and determine relative position information based on the rough position and the current environmental information; perform positioning based on the relative position information and the preset global map to obtain a positioning result. Since the present application determines the rough position based on the matching of the local map and the global map, and then determines the relative position information based on the rough position and the current environmental information, and performs positioning based on the relative position information and the preset global map, compared with the existing method of using GPS for positioning, the above method of the present application can perform accurate positioning when the GPS signal is weak.

[0053] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, an inspection robot, etc. The following takes the inspection robot as an example to illustrate this embodiment and the following embodiments.

[0054] Based on this, the present application embodiment provides a positioning method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the positioning method of the present application.

[0055] In this embodiment, the positioning method is applied to an inspection robot, and the positioning method includes steps S10 to S40:

[0056] Step S10, collecting current environment information, and determining the current local map information according to the current environment information;

[0057] It should be noted that the current environmental information collected may be the inspection robot collecting the current surrounding environmental information through sensors such as laser radar, gyroscope (IMU), wheel encoder (odometer), satellite navigation (GPS), etc. The local map information determined according to the current environmental information may be generated according to the current environmental information (also referred to as multi-sensor data) A priori high-precision three-dimensional point cloud map, i.e., local map information. Specifically, nonlinear Kalman filtering may be used to fuse the multi-sensor data to obtain a fusion result, and then NDT, ICP or probability grid-based modeling is selected to calculate the optimal sub-graph, and finally the optimal sub-graph is closed-loop detected and optimized, local accumulated errors are eliminated, and the map is built to obtain local map information containing the local map. Among them, the nonlinear Kalman filtering algorithm is an effective tool for processing nonlinear system state estimation. These algorithms can filter out noise and interference from continuous (or discrete) input data in the presence of nonlinear relationships, extract useful information, and thus achieve accurate estimation of the system state. In the field of multi-sensor data fusion, the nonlinear Kalman filter algorithm can fuse data from different sensors that may have different units, and obtain a more accurate target measurement value by optimizing the fusion result. Probability grid map is a very useful map form, and probability grid map usually uses logarithmic probability values.

[0058] In the specific implementation, how to construct a probability grid map based on a frame of laser scan? First, the world (task area) is rasterized according to a certain resolution, and then each laser point will fall in a certain grid (called a hit). The occupancy probability of the hit grid is the probability corresponding to the mean in the probability distribution curve; and for nearby grids that have not been hit, the probability value query will be made in the normal distribution curve according to the distance to the nearest hit grid, and the queried probability is the occupancy probability of this grid. In this way, the probability is processed logarithmically to obtain the grid probability actually used in the algorithm. All grids are processed in this way to obtain the probability grid map of this scan.

[0059] Step S20, matching the local map information with a preset global map to obtain a matching result;

[0060] It should be noted that the preset global map may be a map obtained by pre-modeling the area to be inspected by the inspection robot. The matching of the local map information with the preset global map to obtain the matching result may be to compare the local map information with the preset global map to determine the position of the local map in the local map information in the preset global map.

[0061] Step S30, determining a rough position based on the matching result, and determining relative position information according to the rough position and the current environment information;

[0062] It should be noted that the determination of the rough position based on the matching result may be to determine the position of the local map in the preset global map according to the matching result, that is, the rough position. The determination of the relative position information according to the rough position and the current environmental information may be to determine the target feature point at the rough position, and then determine the relative position of the inspection robot relative to the target feature point according to the current environmental information, including the relative distance and relative direction. In order to improve the positioning accuracy, there may be multiple target feature points. The target feature point may be a feature point with a certain degree of recognition selected when constructing the preset global map. The position of the target feature point in the preset global map is known and can be calibrated in advance.

[0063] Furthermore, in order to improve positioning accuracy, the step of determining relative position information according to the rough position and the current environment information includes:

[0064] Determine a target feature point according to the rough position;

[0065] Relative position information relative to the target feature point is determined based on the current environment information.

[0066] It should be noted that the selection requirements of the target feature point may include: the point must be within the preset global map range; the point has a high degree of recognition, which is convenient for the consistency of the equipment position when collecting the relative coordinates and absolute coordinates of the point, reducing the collection error; there are fewer obstructions above the point, ensuring that the positioning device can enter a higher precision positioning combination when collecting the absolute coordinates of the point; the road environment around the point has a certain degree of passability, which is convenient for controlling the robot or positioning device to perform coordinate collection operations. The method of collecting the coordinates of the target feature point may include: the collection of relative coordinates: controlling the inspection robot to drive to the target feature point, adjusting the posture and position of the inspection robot, so that the center point of the body defined by the inspection robot coincides with the target feature point as much as possible. Under the condition that the inspection robot is in a good navigation and positioning state, the position information fed back by the inspection robot is read, which is the relative coordinate of the target feature point in the preset global map; the collection of absolute coordinates: through a portable outdoor geographic coordinate collection device such as a total station, the absolute coordinates of the target feature point (based on the latitude and longitude, elevation information values ​​of the common geographic coordinate system) are collected.

[0067] Step S40, performing positioning according to the relative position information and the preset global map to obtain a positioning result.

[0068] It should be noted that, the positioning is performed according to the relative position information and the preset global map, and the positioning result obtained can be that the precise position of the target feature point corresponding to the relative position information is determined according to the preset global map, and then the relative direction and relative distance of the inspection robot relative to the precise position of the target feature point are determined based on the relative position information, and the positioning result of the inspection robot is determined according to the relative direction, relative distance and the precise position of the target feature point.

[0069] Furthermore, in order to improve the positioning efficiency of the inspection robot, the step S40 further includes: determining the absolute coordinates of the target feature point according to the preset global map;

[0070] Determine the offset information of the inspection robot relative to the target feature point according to the relative position information;

[0071] The absolute coordinates of the inspection robot are determined according to the offset information and the absolute coordinates.

[0072] It should be noted that the absolute coordinates may be the longitude and latitude, elevation information value and other position information of the target feature point calibrated in advance. The offset information may be the direction and distance information of the inspection robot relative to the target feature point.

[0073] In the specific implementation, please refer to Figure 2 , Figure 2 A schematic diagram of the positioning process provided for the first embodiment of the positioning method of the present application. First, the inspection robot reports the relative coordinate information relative to the preset global map. Then, according to the relative coordinate information, two reference points are selected from the reference point data of the preset global map (i.e., the target feature point information), that is, two target feature points are selected, the relative coordinate system of the reference points is converted to the Mercator projection coordinate system, the relative coordinates of the inspection robot are also converted to the Mercator projection coordinates, and then the Mercator projection coordinates are converted to GPS coordinates, and then the positioning result of the inspection robot is obtained.

[0074] Furthermore, in order to improve the inspection efficiency of the inspection robot, after step S40, the method further includes: judging whether a preset parking condition is currently met according to the positioning result;

[0075] When the preset parking condition is currently met, the deceleration range information is determined;

[0076] determining a driving speed based on the deceleration range information;

[0077] Slow down to stop according to the driving speed, and start a timer to record the waiting time;

[0078] When the waiting time exceeds the preset waiting time, the obstacle bypassing function is enabled.

[0079] It should be noted that the preset parking conditions may include positioning scores lower than a preset trustworthy threshold, positioning timeout, positioning error, odometer timeout, obstacle detection, driving out of a feasible area, i.e., a preset global map area, etc. The determination of the deceleration range information may be to determine the deceleration distance for deceleration to parking based on information such as the current speed and the distance to the obstacle, and to avoid emergency parking as much as possible. The determination of the driving speed based on the deceleration range information may be to calculate the acceleration for uniform deceleration to stop based on the current speed and the deceleration distance. The deceleration to parking based on the driving speed may be to control the inspection robot to uniformly decelerate to parking based on the driving speed. In the case where the reason for parking is an obstacle ahead, the parking time is also recorded, and when the parking time is greater than the preset waiting time, the obstacle bypass is enabled. In the case where the reason for parking is driving out of the feasible area, the inspection robot may be controlled to turn around and then return to the preset global map area. Among them, the odometer data timeout may be that the odometer data is greater than the preset time threshold and is not updated. For example, in the navigation moving state, if no update of the odometer data message is received within a certain period of time, or the value changes, it can be determined that the odometer data has timed out, and the inspection robot is stopped. The positioning score can be a positioning reliability calculated in real time, which is related to map matching. The fused sensor data (i.e., local map information) is matched with a known map (i.e., a preset global map) to determine the location of the inspection robot or mobile device. For example, in LiDAR SLAM, the point cloud obtained by the LiDAR scan is matched with the features in the map to determine the current position. If the matching result is good, that is, the sensor data is highly consistent with the features in the map, then the positioning reliability is high; conversely, if the matching result is poor, there may be a large positioning error, and the positioning reliability is low.

[0080] This embodiment collects current environmental information, and determines the current local map information based on the current environmental information; matches the local map information with a preset global map to obtain a matching result; determines a rough position based on the matching result, and determines relative position information based on the rough position and the current environmental information; performs positioning based on the relative position information and the preset global map to obtain a positioning result. Since this embodiment determines a rough position based on matching of a local map and a global map, and then determines relative position information based on the rough position and the current environmental information, and performs positioning based on the relative position information and the preset global map, compared to the existing method of using GPS for positioning, the above method of this embodiment can perform precise positioning when the GPS signal is weak.

[0081] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 , Figure 3 The flowchart provided in the second embodiment of the positioning method of the present application includes the following steps before step S10:

[0082] Step S001: when receiving a path planning task, decomposing the path planning task to obtain path planning subtasks;

[0083] It should be noted that the path planning task may be an inspection task sent by an upstream device, and may include information such as inspection time, inspection target, and inspection target point. Decomposing the path planning task to obtain path planning subtasks may be decomposing the path planning task into multiple subtasks, such as a subtask for reaching the target point, a subtask for inspecting the target point, and a subtask for returning.

[0084] Further, the step S001 may include: upon receiving a path planning task, determining a starting point location and an end point location according to the path planning task;

[0085] Determine the task decomposition feature points based on the starting point location, the end point location and the preset global map;

[0086] The path planning task is decomposed according to the task decomposition feature points to obtain path planning subtasks.

[0087] It should be noted that the starting position may be the current position of the inspection robot. The end position may be the feature point position to be inspected in the path planning task. A path planning task may include multiple feature point positions. When there is only one feature point position in the path planning task, the feature point position is the end position. When there are multiple feature point positions in the path planning task, the inspection order of the multiple feature point positions is determined according to the path planning task, and the feature point positions are sorted according to the inspection order. The first feature point position is first used as the end position. After the inspection of the first feature point position is completed, the first feature point position is used as the starting position, and the second feature point position is used as the end position, until the inspection of the feature point positions in the path planning task is completed. If the inspection order of the feature point positions is not specified in the path planning task, the distance between each feature point position and the starting position is determined, and the feature point positions are sorted according to the distance between each feature point position and the starting position. The task decomposition feature points determined based on the starting position, the end position and the preset global map can be selected from the preset global map according to the starting position and the end position as the target feature points located between the starting position and the end position, and the target feature points are pre-calibrated feature points whose relative position coordinates and absolute positions are known. The path planning task is decomposed according to the task decomposition feature points to obtain the path planning subtasks: for example, the starting position is A, the end position is B, the task decomposition feature points include C and D, the path planning task is from A to B, and the decomposed path planning subtasks include subtask 1: from A to C; subtask 2: from C to D; subtask 3: from D to B.

[0088] Step S002: performing path planning based on the path planning subtask by using a preset path planning algorithm to obtain path information corresponding to the path planning subtask;

[0089] It should be noted that the preset path planning algorithm can be an A* algorithm, which is a heuristic search algorithm. During the search process, it not only considers the actual cost (such as distance, time, etc.) from the starting point to the current node, but also uses a heuristic function to estimate the cost from the current node to the target point. This heuristic function is like providing a "foresight" to the search process, guiding the search in the direction of the target point, thereby reducing unnecessary searches. For example, in the path planning of a two-dimensional plane map, if the straight-line distance between two points is computable, then this straight-line distance can be used as part of the heuristic function because it is a lower limit estimate of the shortest distance from the current point to the target point.

[0090] The search process of the A* algorithm: The A* algorithm starts from the starting point, gradually expands the surrounding nodes, and sorts these nodes according to the evaluation function. It records the nodes that have been explored to avoid repeated exploration. As the search proceeds, the algorithm gradually approaches the target point until it finds the target point or determines that there is no feasible path. Significance in global planning:

[0091] 1) Global perspective: The goal of global planning is to find the best path from the starting point to the target point within the scope of the entire environment map. The A* algorithm can fully consider the information of the entire environment in this process. It can handle complex map structures, including various obstacles, different terrains, etc. By searching the entire map, the A* algorithm can find a path that avoids all obstacles and has the lowest total cost. This cost can be defined according to the specific application scenario, such as the shortest path length, the shortest walking time, etc.

[0092] 2) Optimality guarantee: Under certain conditions, the A* algorithm can ensure that the path found is the best. This is very critical for path planning because it ensures efficient use of resources. For example, in robot navigation, the optimal path allows the robot to reach the target location with the shortest distance or the least energy consumption; in logistics distribution, the optimal path can reduce transportation costs and time.

[0093] 3) Adaptability and flexibility: The A* algorithm can be adjusted according to different environments and task requirements. For example, the definition of the heuristic function can be changed to adapt to different map types and path cost calculation methods. In an environment with dynamic obstacles, the algorithm can be appropriately improved so that it can replan the path during operation to adapt to changes in the environment.

[0094] Step S003: determining the moving speed according to the path;

[0095] It should be noted that determining the moving speed according to the path may be determining the road condition corresponding to the path information, and determining the moving speed of the inspection robot according to the road condition. During the driving process of the inspection robot, the speed may not match the pre-planned speed due to the road condition. In this case, it is also necessary to calculate the real-time moving speed based on the current speed, road condition and pre-planned speed.

[0096] Step S004: determining a motion trajectory according to the path information, the moving speed and the path planning task, and executing the path planning task based on the motion trajectory.

[0097] It should be noted that the determination of the motion trajectory according to the path information, the moving speed and the path planning task may be to determine the driving path corresponding to the path planning subtask and the driving speed on each path according to the path information and the moving speed, and then determine the final motion trajectory of the inspection robot according to the execution order corresponding to each path planning subtask in the path planning task. The motion trajectory includes the driving path and the driving speed of each path.

[0098] Furthermore, in order to improve the positioning accuracy, before step S20, it is necessary to first map the inspection area. Figure 4 , Figure 4 The map modeling process diagram provided for the second embodiment of the positioning method of the present application is that the regional map to be created is the region corresponding to the preset global map, and the inspection task route can be the route in the preset global map. The exported task area navigation map is the preset global map.

[0099] When receiving a path planning task, this embodiment decomposes the path planning task to obtain path planning subtasks; performs path planning based on the path planning subtasks by using a preset path planning algorithm to obtain path information corresponding to the path planning subtasks; determines a moving speed according to the path; determines a motion trajectory according to the path information, the moving speed, and the path planning task, and executes the path planning task based on the motion trajectory. This embodiment decomposes the path planning task into path planning subtasks, then determines the path information corresponding to the path planning subtasks according to a preset path planning algorithm, and then determines the motion trajectory corresponding to the path planning task in combination with the moving speed, which can improve the inspection efficiency of the inspection robot.

[0100] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the positioning method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0101] This application also provides a positioning device, please refer to Figure 5 , the positioning device comprises:

[0102] The acquisition module 10 is used to acquire current environment information and determine the current local map information according to the current environment information;

[0103] A matching module 20, used to match the local map information with a preset global map to obtain a matching result;

[0104] A determination module 30, configured to determine a rough position based on the matching result, and determine relative position information according to the rough position and the current environment information;

[0105] The positioning module 40 is used to perform positioning according to the relative position information and the preset global map to obtain a positioning result.

[0106] This embodiment collects current environmental information, and determines the current local map information based on the current environmental information; matches the local map information with a preset global map to obtain a matching result; determines a rough position based on the matching result, and determines relative position information based on the rough position and the current environmental information; performs positioning based on the relative position information and the preset global map to obtain a positioning result. Since this embodiment determines a rough position based on matching of a local map and a global map, and then determines relative position information based on the rough position and the current environmental information, and performs positioning based on the relative position information and the preset global map, compared to the existing method of using GPS for positioning, the above method of this embodiment can perform precise positioning when the GPS signal is weak.

[0107] The positioning device provided by the present application adopts the positioning method in the above embodiment, which can solve the technical problem of low positioning efficiency of the inspection robot in a signal-free scene. Compared with the prior art, the beneficial effects of the positioning device provided by the present application are the same as the beneficial effects of the positioning method provided by the above embodiment, and the other technical features in the positioning device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0108] The present application provides a positioning device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the positioning method in the above-mentioned embodiment 1.

[0109] Reference below Figure 6 , which shows a schematic diagram of the structure of a positioning device suitable for implementing the embodiments of the present application. The positioning device in the embodiments of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The positioning device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0110] like Figure 6As shown, the positioning device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the positioning device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the positioning device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a positioning device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0111] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0112] The positioning device provided by the present application adopts the positioning method in the above embodiment, which can solve the technical problem of low positioning efficiency of the inspection robot in a signal-free scene. Compared with the prior art, the beneficial effects of the positioning device provided by the present application are the same as the beneficial effects of the positioning method provided by the above embodiment, and the other technical features in the positioning device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0113] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0114] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0115] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the positioning method in the above-mentioned embodiment.

[0116] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0117] The computer-readable storage medium may be included in the positioning device; or may exist independently without being assembled into the positioning device.

[0118] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the positioning device, the positioning device executes the positioning method.

[0119] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0120] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0121] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0122] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned positioning method, and can solve the technical problem of low positioning efficiency of the inspection robot in a signal-free scene. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the positioning method provided by the above-mentioned embodiment, and will not be repeated here.

[0123] The present application also provides a computer program product, including a computer program, which implements the steps of the positioning method as described above when executed by a processor.

[0124] The computer program product provided by this application can solve the technical problem of low positioning efficiency of the inspection robot in a signal-free scene. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the positioning method provided by the above embodiment, which will not be repeated here.

[0125] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A positioning method, characterized in that: Applied to the inspection robot, the positioning method comprises the following steps: Collecting current environment information, and determining the current local map information according to the current environment information; Matching the local map information with a preset global map to obtain a matching result; Determine a rough position based on the matching result, and determine relative position information according to the rough position and the current environment information; Positioning is performed according to the relative position information and the preset global map to obtain a positioning result.

2. The positioning method according to claim 1, characterized in that: The step of determining the relative position information according to the rough position and the current environment information comprises: Determine a target feature point according to the rough position; Relative position information relative to the target feature point is determined based on the current environment information.

3. The positioning method according to claim 2, characterized in that: The step of performing positioning according to the relative position information and the preset global map to obtain a positioning result comprises: Determine the absolute coordinates of the target feature point according to the preset global map; Determine the offset information of the inspection robot relative to the target feature point according to the relative position information; The absolute coordinates of the inspection robot are determined according to the offset information and the absolute coordinates.

4. The positioning method according to claim 1, characterized in that: Before the step of collecting current environment information and determining the current local map information according to the current environment information, the method further includes: When receiving a path planning task, decomposing the path planning task to obtain path planning subtasks; Performing path planning based on the path planning subtask by using a preset path planning algorithm to obtain path information corresponding to the path planning subtask; determining a moving speed according to the path; A motion trajectory is determined according to the path information, the moving speed, and the path planning task, and the path planning task is performed based on the motion trajectory.

5. The positioning method according to claim 4, characterized in that: The step of decomposing the path planning task to obtain path planning subtasks upon receiving the path planning task includes: When receiving a path planning task, determining a starting point location and an end point location according to the path planning task; Determine the task decomposition feature points based on the starting point location, the end point location and the preset global map; The path planning task is decomposed according to the task decomposition feature points to obtain path planning subtasks.

6. The positioning method according to any one of claims 1 to 5, characterized in that: After the step of performing positioning according to the relative position information and the preset global map to obtain a positioning result, the method further includes: Determining whether a preset parking condition is currently met according to the positioning result; When the preset parking condition is currently met, the deceleration range information is determined; determining a driving speed based on the deceleration range information; decelerate to a stop according to the driving speed, and start a timer to record the waiting time; When the waiting time exceeds the preset waiting time, the obstacle bypassing function is enabled.

7. A positioning device, characterized in that: Applied to the inspection robot, the positioning device comprises: A collection module, used to collect current environment information and determine the current local map information according to the current environment information; A matching module, used for matching the local map information with a preset global map to obtain a matching result; A determination module, configured to determine a rough position based on the matching result, and determine relative position information according to the rough position and the current environment information; The positioning module is used to perform positioning according to the relative position information and the preset global map to obtain a positioning result.

8. A positioning device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the positioning method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the positioning method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the positioning method according to any one of claims 1 to 6 are implemented.

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