A method to eliminate the cumulative error of SLAM navigation

Abstract

The present invention relates to the field of navigation technology, and in particular to a method for eliminating accumulated errors in SLAM navigation, comprising: receiving position information collected by a modeling robot in real time, setting a movement logic of the modeling robot, controlling the modeling robot to move again based on the movement logic, and synchronously executing the re-collection of the position information collected last time by the modeling robot; obtaining the distance from the modeling robot to the collected position information when the modeling robot collected the position information last time, and obtaining the distance moved based on the movement logic when the modeling robot collects the position information collected last time again. The present invention comprehensively considers the error generated by the movement of the modeling robot and the error generated in the ranging process of a sensing device on the modeling robot, so that the SLAM is configured in the operation of the modeling robot, and more accurate position information can be collected, so as to realize the accurate construction of a scene to be measured where an accurate target to be measured is located, and greatly reduces the possibility and severity of the modeling loop being unable to be closed due to the accumulation of errors.

Description

Technical Field

[0001] The invention relates to the field of navigation technology, and in particular to a method for eliminating SLAM navigation cumulative errors. Background Art

[0002] SLAM navigation is an advanced technology mainly used in the fields of robotics and unmanned driving. Its core idea is to allow a mobile subject (such as a robot) to simultaneously determine its own position and build a map of the surrounding environment during movement in an unknown environment.

[0003] SLAM navigation enables robots to explore and navigate autonomously without prior maps, greatly improving their autonomy and adaptability. It provides key support for the effective operation of intelligent mobile systems in complex and unknown environments, and has important applications and broad development prospects in many fields such as warehousing and logistics, autonomous driving, and smart homes.

[0004] When SLAM technology is applied to modeling robots, in the process of the modeling robot moving to collect position information of each point in the scene to build a scene model, the errors caused by the robot's movement are often difficult to estimate and correct. As a result, when the modeling robot collects position information of each point in the scene and performs scene modeling based on SLAM technology, the scene modeling is inaccurate due to the existence of errors, or a complete closed-loop scene model cannot be built. Summary of the invention

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method for eliminating the cumulative error of SLAM navigation, which solves the technical problems raised in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] A method for eliminating SLAM navigation cumulative error, comprising:

[0008] Receive the position information collected by the modeling robot in real time, set the movement logic of the modeling robot, control the modeling robot to move again based on the movement logic, and synchronously perform the re-collection of the position information collected by the modeling robot last time;

[0009] Obtain the distance between the modeling robot and the collected position information when the modeling robot last collected position information, obtain the distance moved based on the movement logic when the modeling robot collects the last collected position information again, calculate the distance between the modeling robot and the collected position information when the modeling robot collects the last collected position information again based on the two sets of distances, and synchronously obtain the distance between the modeling robot and the collected position information when the modeling robot collects the last collected position information again;

[0010] When the modeling robot collects the location information collected last time again, the calculation logic of the distance from the modeling robot to the collected location information is:

[0011]

[0012] Where: c is the distance from the modeling robot to the collected position information when the modeling robot collects the position information collected last time; a is the distance from the modeling robot to the collected position information when the modeling robot collected the position information last time; b is the distance moved by the modeling robot based on the mobile logic; cosC is the cosine value of the angle between the line segments corresponding to distance a and distance b;

[0013] Based on the distance obtained by the measurement logic and the distance from the modeling robot to the collected position information when the modeling robot collected the last collected position information again, the error generation rate is analyzed, and the position information currently collected by the modeling robot is corrected according to the error generation rate;

[0014] Configure prior data, set the frequency of collecting position information of the modeling robot, and re-correct the position information collected by the corrected modeling robot based on the prior data and the frequency of collecting position information of the modeling robot.

[0015] Furthermore, the modeling robot integrated components include a mobile device, a ranging sensor and a camera. The modeling robot is operated based on SLAM control, and the mobile device carries the ranging sensor and the camera to move. The ranging sensor measures the distance from its own ranging end to a point on the ranging target, and obtains the position information of a point on the ranging target relative to the initial position information based on the initial position information combined with the ranging result. The camera synchronously collects the ranging target image from its own camera end to the perspective of a point on the ranging target.

[0016] Among them, the ranging end of the ranging sensor, the camera end of the camera and a point on the ranging target are on the same straight line;

[0017] The modeling robot movement logic includes: monitoring whether the position information collected by the modeling robot in real time is received, setting the deflection angle and the rated movement distance after the position information collected by the modeling robot in real time is received, controlling the modeling robot to rotate based on the deflection angle, and after the rotation operation is completed, controlling the modeling robot to move based on the set rated movement distance again;

[0018] Among them, the set deflection angle obeys: the farther the distance between the position information collected by the modeling robot in real time and the initial position information of the modeling robot is, the larger the set deflection angle is; the closer the distance between the position information collected by the modeling robot in real time and the initial position information of the modeling robot is, the smaller the set deflection angle is, and the set rated moving distance is set by the user.

[0019] Furthermore, the mobile device is connected to the ranging sensor and the camera based on an electric universal shaft. After the ranging sensor measures the distance from its own ranging end to a point on the ranging target, it simultaneously identifies a point on the ranging target and a corresponding area in the ranging target image captured by the camera, and further obtains the center of the regional image in the corresponding area, which is recorded as the marking center.

[0020] When the modeling robot moves based on the mobile logic, the ranging sensor and the camera synchronously control the movement based on the electric universal shaft, so that the center of the ranging target image collected by the camera in real time is always the marking center.

[0021] Furthermore, the distance from the modeling robot to the collected position information is: the distance from the ranging end of the ranging sensor to a point on the ranging target;

[0022] In the stage of calculating the distance between the modeling robot and the collected position information when the modeling robot collects the position information collected last time again, the deflection angle, that is, cosC, is obtained synchronously in the movement logic of the modeling robot. The distance between the modeling robot and the collected position information when the modeling robot collects the position information collected last time is calculated in combination with the deflection angle.

[0023] Furthermore, the distance obtained by the measurement logic is recorded as x, and the distance from the modeling robot to the collected position information when the modeling robot collects the last collected position information again is recorded as y. The error generation rate analysis logic is expressed as:

[0024]

[0025] Where: d is the distance that the modeling robot moves based on the movement logic when the modeling robot collects the last collected position information again;

[0026] After the error generation rate f is obtained, the position information collected by the modeling robot last time is further corrected. The correction process is:

[0027] S1: The distance from the ranging sensor to a point on the ranging target measured by the ranging sensor at the last position information collected by the modeling robot is recorded as d0;

[0028] S2: According to the initial position information of the ranging sensor, the ranging end angle of the ranging sensor during ranging, and the value of d0±d0×f, the position information of a point on the ranging target relative to the initial position information is obtained.

[0029] Furthermore, the position information collected by the current modeling robot is corrected, and the position information of a point on the ranging target relative to the initial position information is obtained based on the distance from the modeling robot to the collected position information when the modeling robot collects the position information collected last time, and the position information after the modeling robot moves based on the movement logic, which is recorded as (J, K, L);

[0030] Based on the distance from the modeling robot to the collected position information when the modeling robot last collected position information, and the position information when the modeling robot last collected position information, obtain the position information of a point on the ranging target relative to the initial position information, recorded as (J′, K′, L′);

[0031]

[0032] Where: is the distance from (J, K, L) to the initial position information of the ranging sensor; is the distance from (J′, K′, L′) to the initial position information of the ranging sensor;

[0033] Among them, if formula (1) holds true, the value applied in the correction stage for the position information collected by the current modeling robot is d0-d0×f; if formula (2) holds true, the value applied in the correction stage for the position information collected by the current modeling robot is d0+d0×f. When both formula (1) and formula (2) are not true, it is determined that the current ranging operation of the modeling robot is invalid, and the ranging of the same point on the ranging target is performed again. When the current ranging operation of the modeling robot is determined to be invalid twice in succession, it is determined that there is no error in the position information collected by the current modeling robot, and the ranging and positioning of the point on the next ranging target are further performed.

[0034] Furthermore, the prior data is two known points and the distance between the two points. The modeling robot position information collection frequency is set by the user end. The modeling robot position information collection frequency is the operating frequency of the distance measuring sensor in the modeling robot. Before the modeling robot performs position information collection, the modeling robot repeatedly collects the distance between the two known points in the prior data based on the modeling robot position information collection frequency. The collection results are recorded as d1, d2, ...d x-1 d x , based on the collection result, the value closest to the distance between the two points in the prior data is obtained, the difference between the obtained value and the distance between the two points in the prior data is calculated, and the ratio of the difference to the distance between the two points is further calculated. The ratio is used to re-correct the position information collected by the corrected modeling robot.

[0035] Furthermore, the value closest to the distance between two points in the prior data can be obtained based on the acquisition result:

[0036] Any group;

[0037] Where: d max is d1, d2, ...d x-1 d x The maximum value; d min is d1, d2, ...d x-1 d x Minimum value in d s is d1, d2, ...d x-1 d x The value that is closest to the distance between two points in the prior data.

[0038] Furthermore, the position information collected by the modeling robot after correction is corrected again by:

[0039] (d0±d0×f)+(d0±d0×f)×k;

[0040] Where: k is the ratio of the difference between the value closest to the distance between two points in the prior data and the distance between two points in the prior data to the distance between two points in the prior data;

[0041] Among them, (d0±d0×f)+(d0±d0×f)×k is the distance from the ranging end of the ranging sensor to a point on the ranging target obtained after two corrections. Based on the position information of the ranging sensor when performing the ranging operation, the value of (d0±d0×f)+(d0±d0×f)×k, and the angle of the ranging end of the ranging sensor, the position information of a point on the ranging target relative to the initial position information is obtained.

[0042] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0043] The present invention provides a method for eliminating the accumulated error of SLAM navigation. During the execution of the method, the error generated by the movement of a modeling robot and the error generated in the ranging process of a sensing device on the modeling robot are comprehensively considered, and the final ranging result is corrected. Based on the corrected ranging result, the ranging direction and the initial ranging point are combined in the SLAM, and the error of the position information of a point on a target to be measured that is finally processed and output by the SLAM is eliminated, so that the SLAM is configured to run the modeling robot and can collect more accurate position information, so as to realize the accurate construction of the scene to be measured where the target to be measured is located, and the possibility and severity of the modeling loop being unable to be closed due to the error accumulation are greatly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 A schematic diagram of the process of obtaining the distance based on the measurement logic in the method of the present invention;

[0046] Figure 2 A schematic diagram of the process of measuring the distance during the re-collection of the position information collected last time by the modeling robot in the present invention;

[0047] Figure 3 The present invention is based on Figure 1 The distance and Figure 2 Schematic diagram of the error comparison produced by the measured distance level;

[0048] The numbers in the figure represent: 1. The initial position of the ranging end of the ranging sensor carried by the modeling robot; 2. The modeling robot; 3. The modeling robot after moving based on the mobile logic; 4. The distance moved by the modeling robot based on the mobile logic; 5. The distance to a point on the ranging target measured by the ranging end of the ranging sensor carried by the modeling robot when collecting position information; 6. The ranging end of the ranging sensor carried by the modeling robot; 7. A point on the ranging target; 8. The distance to a point on the ranging target calculated by the modeling robot after moving based on the mobile logic; 9. Ranging target; 10. The distance to a point on the ranging target measured by the ranging sensor carried by the modeling robot after moving based on the mobile logic. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0050] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, "plurality" means two or more, unless otherwise clearly and specifically defined.

[0051] In the description of the present application, the term "for example" is used to mean "used as an example, illustration or description". Any embodiment described as "for example" in the present application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid unnecessary details to obscure the description of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present application.

[0052] Embodiment 1:

[0053] A method for eliminating the cumulative error of SLAM navigation in this embodiment is as follows: Figure 1 As shown, including:

[0054] Receive the position information collected by the modeling robot in real time, set the movement logic of the modeling robot, control the modeling robot to move again based on the movement logic, and synchronously perform the re-collection of the position information collected by the modeling robot last time;

[0055] Obtain the distance between the modeling robot and the collected position information when the modeling robot last collected position information, obtain the distance moved based on the movement logic when the modeling robot collects the last collected position information again, calculate the distance between the modeling robot and the collected position information when the modeling robot collects the last collected position information again based on the two sets of distances, and synchronously obtain the distance between the modeling robot and the collected position information when the modeling robot collects the last collected position information again;

[0056] When the modeling robot collects the location information collected last time again, the calculation logic of the distance from the modeling robot to the collected location information is:

[0057]

[0058] Where: c is the distance from the modeling robot to the collected position information when the modeling robot collects the position information collected last time; a is the distance from the modeling robot to the collected position information when the modeling robot collected the position information last time; b is the distance moved by the modeling robot based on the mobile logic; cosC is the cosine value of the angle between the line segments corresponding to distance a and distance b;

[0059] Based on the distance obtained by the measurement logic and the distance from the modeling robot to the collected position information when the modeling robot collected the last collected position information again, the error generation rate is analyzed, and the position information currently collected by the modeling robot is corrected according to the error generation rate;

[0060] Configure prior data, set the frequency of collecting position information of the modeling robot, and re-correct the position information collected by the corrected modeling robot based on the prior data and the frequency of collecting position information of the modeling robot;

[0061] The prior data is two known points and the distance between them. The frequency of collecting the position information of the modeling robot is set by the user. The frequency of collecting the position information of the modeling robot is the operating frequency of the distance measuring sensor in the modeling robot. Before the modeling robot performs position information collection, it repeatedly collects the distance between the two known points in the prior data based on the frequency of collecting the position information of the modeling robot. The collection results are recorded as d1, d2, ...d x-1 d x , based on the collected results, the value closest to the distance between the two points in the prior data is obtained, the difference between the obtained value and the distance between the two points in the prior data is calculated, and the ratio of the difference to the distance between the two points is further calculated, and the position information collected by the corrected modeling robot is corrected again by using the ratio;

[0062] The value closest to the distance between two points in the prior data based on the acquisition results can be:

[0063] Any group;

[0064] Where: d max is d1, d2, ...d x-1 d x The maximum value; d min is d1, d2, ...d x-1 d x Minimum value in d s is d1, d2, ...d x-1 d x The value closest to the distance between two points in the prior data;

[0065] The operation of re-correcting the position information collected by the corrected modeling robot is as follows:

[0066] (d0±d0×f)+(d0±d0×f)×k;

[0067] Where: k is the ratio of the difference between the value closest to the distance between two points in the prior data and the distance between two points in the prior data to the distance between two points in the prior data;

[0068] Among them, (d0±d0×f)+(d0±d0×f)×k is the distance from the ranging end of the ranging sensor to a point on the ranging target obtained after two corrections. Based on the position information of the ranging sensor when performing the ranging operation, the value of (d0±d0×f)+(d0±d0×f)×k, and the angle of the ranging end of the ranging sensor, the position information of a point on the ranging target relative to the initial position information is obtained.

[0069] In this embodiment, based on the above method, in the process of the modeling robot constructing the scene model based on SLAM navigation, the errors caused by the movement of the modeling robot and the errors caused by the measurement data of the sensor equipment are continuously predicted and eliminated, which effectively reduces the error of the modeling robot in constructing the test scene model based on SLAM navigation, and minimizes the possibility and severity of the modeling loop being unable to close due to error accumulation.

[0070] See also Figure 1 and Figure 2 As shown, Figure 1 The purpose is to show the distance 8 to a point on the distance measurement target measured by the modeling robot after it moves based on the movement logic, and the distance 10 to a point on the distance measurement target measured by the distance measurement sensor carried by the modeling robot after it moves based on the movement logic. For ease of viewing, mark 8 and mark 10 are placed on Figure 3 In the figure, based on markers 8 and 10, data support is provided for the error generation rate analysis logic to ensure the stable operation of the error generation rate analysis logic, so that the modeling robot can obtain the correction of the error generation rate f at the moving level of the modeling robot in the process of building the scene model to be tested based on SLAM navigation.

[0071] Embodiment 2:

[0072] In terms of specific implementation, based on Example 1, this example refers to Figure 1 A method for eliminating the cumulative error of SLAM navigation in Example 1 is further described in detail:

[0073] The integrated components of the modeling robot include a mobile device, a ranging sensor and a camera. The modeling robot is operated based on SLAM control. The mobile device carries the ranging sensor and the camera to move. The ranging sensor measures the distance from its own ranging end to a point on the ranging target, and obtains the position information of a point on the ranging target relative to the initial position information based on the initial position information and the ranging result. The camera synchronously collects the ranging target image from the perspective of its own camera end to a point on the ranging target.

[0074] Among them, the ranging end of the ranging sensor, the camera end of the camera and a point on the ranging target are on the same straight line;

[0075] The movement logic of the modeling robot includes: monitoring whether the position information collected by the modeling robot in real time is received, setting the deflection angle and the rated movement distance after the position information collected by the modeling robot in real time is received, controlling the modeling robot to rotate based on the deflection angle, and after the rotation operation is completed, controlling the modeling robot to move based on the set rated movement distance again;

[0076] The set deflection angle is subject to the following conditions: the farther the distance between the position information collected by the modeling robot in real time and the initial position information of the modeling robot is, the larger the set deflection angle is; the closer the distance between the position information collected by the modeling robot in real time and the initial position information of the modeling robot is, the smaller the set deflection angle is. The set rated moving distance is set by the user end;

[0077] The mobile device is connected to the ranging sensor and the camera based on an electric universal shaft. After measuring the distance from its own ranging end to a point on the ranging target, the ranging sensor synchronously identifies the corresponding area of ​​the ranging target in the ranging target image collected by the camera, and further obtains the center of the regional image in the corresponding area, which is recorded as the marking center.

[0078] When the modeling robot moves based on the mobile logic, the ranging sensor and the camera synchronously control the movement based on the electric universal shaft, so that the center of the ranging target image collected by the camera in real time is always the marking center.

[0079] like Figure 1 As shown, the distance from the modeling robot to the collected position information is: the distance from the ranging end of the ranging sensor to a point on the ranging target;

[0080] In the stage of calculating the distance between the modeling robot and the collected position information when the modeling robot collects the position information collected last time again, the deflection angle, that is, cosC, is obtained synchronously in the movement logic of the modeling robot. The distance between the modeling robot and the collected position information when the modeling robot collects the position information collected last time is calculated in combination with the deflection angle.

[0081] In this embodiment, through the above settings, the interaction logic between the modeling robot and SLAM and the specific structure of the modeling robot are limited to ensure the stable operation of the modeling robot, and perform two consecutive ranging operations on a point on the same ranging target, providing data support for the execution of the steps of the method in Example 1.

[0082] Embodiment 3:

[0083] In terms of specific implementation, based on Example 1, this example refers to Figure 1 A method for eliminating the cumulative error of SLAM navigation in Example 1 is further described in detail:

[0084] The distance obtained by the measurement logic is recorded as x, and the distance from the modeling robot to the collected position information when the modeling robot collects the last collected position information again is recorded as y. The error generation rate analysis logic is expressed as:

[0085]

[0086] Where: d is the distance that the modeling robot moves based on the movement logic when the modeling robot collects the last collected position information again;

[0087] After the error generation rate f is obtained, the position information collected by the modeling robot last time is further corrected. The correction process is:

[0088] S1: The distance from the ranging sensor to a point on the ranging target measured by the ranging sensor at the last position information collected by the modeling robot is recorded as d0;

[0089] S2: According to the initial position information of the ranging sensor, the ranging end angle of the ranging sensor during ranging, and the value of d0±d0×f, the position information of a point on the ranging target relative to the initial position information is obtained.

[0090] Through the above settings, the calculation logic of the error generation rate f and the process of applying the error generation rate f to correct the position information collected last time by the modeling robot are further limited.

[0091] like Figure 1 As shown, the position information collected by the current modeling robot is corrected, and the distance from the modeling robot to the collected position information when the modeling robot collects the last collected position information again, and the position information of the modeling robot after moving based on the mobile logic, the position information of a point on the ranging target relative to the initial position information is obtained, which is recorded as (J, K, L);

[0092] Based on the distance from the modeling robot to the collected position information when the modeling robot last collected position information, and the position information when the modeling robot last collected position information, obtain the position information of a point on the ranging target relative to the initial position information, recorded as (J′, K′, L′);

[0093]

[0094] Where: is the distance from (J, K, L) to the initial position information of the ranging sensor; is the distance from (J′, K′, L′) to the initial position information of the ranging sensor;

[0095] Among them, if formula (1) holds true, the value applied in the correction stage for the position information collected by the current modeling robot is d0-d0×f; if formula (2) holds true, the value applied in the correction stage for the position information collected by the current modeling robot is d0+d0×f. When both formula (1) and formula (2) are not true, it is determined that the current ranging operation of the modeling robot is invalid, and the ranging of the same point on the ranging target is performed again. When the current ranging operation of the modeling robot is determined to be invalid twice in succession, it is determined that there is no error in the position information collected by the current modeling robot, and the ranging and positioning of the point on the next ranging target are further performed.

[0096] In this embodiment, through the above settings, the process of correcting the position information collected by the modeling robot last time is further refined to ensure the stable output of the correction results of the position information collected by the modeling robot, and further provide correction target data for the second correction of the position information collected by the modeling robot in Example 1.

[0097] In summary, during the execution of the method in the above embodiment, the errors caused by the movement of the modeling robot and the errors caused by the ranging process of the sensing equipment on the modeling robot are comprehensively considered, and the final ranging result is corrected. Based on the corrected ranging result, the ranging direction and the initial ranging point are combined in SLAM to eliminate the error of the position information of a point on the target to be measured that is finally processed and output by SLAM, so that the SLAM is configured to run the modeling robot and can collect more accurate position information, so as to realize the accurate construction of the scene to be measured where the target to be measured is located, and minimize the possibility and severity of the modeling loop being unable to be closed due to error accumulation.

[0098] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0101] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0102] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0103] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0104] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for eliminating SLAM navigation cumulative error, characterized in that: include: Receive the position information collected by the modeling robot in real time, set the movement logic of the modeling robot, control the modeling robot to move again based on the movement logic, and synchronously perform the re-collection of the position information collected by the modeling robot last time; Obtain the distance between the modeling robot and the collected position information when the modeling robot last collected position information, obtain the distance moved based on the movement logic when the modeling robot collects the last collected position information again, calculate the distance between the modeling robot and the collected position information when the modeling robot collects the last collected position information again based on the two sets of distances, and synchronously obtain the distance between the modeling robot and the collected position information when the modeling robot collects the last collected position information again; When the modeling robot collects the location information collected last time again, the calculation logic of the distance from the modeling robot to the collected location information is: ； Where: When the modeling robot collects the last collected position information again, the distance from the modeling robot to the collected position information; The distance from the modeling robot to the collected position information when the modeling robot last collected position information; To model the distance the robot moves based on movement logic; For distance and distance The cosine of the angle between the corresponding line segments; Based on the distance obtained by the measurement logic and the distance from the modeling robot to the collected position information when the modeling robot collected the last collected position information again, the error generation rate is analyzed, and the position information currently collected by the modeling robot is corrected according to the error generation rate; Configure prior data, set the frequency of collecting position information of the modeling robot, and re-correct the position information collected by the corrected modeling robot based on the prior data and the frequency of collecting position information of the modeling robot; The distance obtained by the measurement logic is recorded as x, and the distance from the modeling robot to the collected position information when the modeling robot collects the last collected position information again is recorded as y. The error generation rate analysis logic is expressed as: ； Where: The distance that the modeling robot moves based on the movement logic when the modeling robot collects the last collected position information again; Error generation rate After obtaining, the position information collected by the modeling robot last time is further corrected. The correction process is: S1: The distance from the ranging sensor to a point on the ranging target measured by the ranging sensor during the last position information collection of the modeling robot is recorded as ; S2: Based on the initial position information of the ranging sensor, the ranging end angle of the ranging sensor during ranging, and The value of is used to obtain the position information of a point on the ranging target relative to the initial position information; The current position information collected by the modeling robot is corrected. The position information of a point on the ranging target relative to the initial position information is obtained based on the distance from the modeling robot to the collected position information when the modeling robot collects the last collected position information again, and the position information after the modeling robot moves based on the mobile logic, which is recorded as (J, K, L). Based on the distance from the modeling robot to the collected position information when the modeling robot last collected position information, and the position information when the modeling robot last collected position information, obtain the position information of a point on the ranging target relative to the initial position information, recorded as (J′, K′, L′); ； Where: is the distance from (J, K, L) to the initial position information of the ranging sensor; is the distance from (J′, K′, L′) to the initial position information of the ranging sensor; Among them, if formula (1) holds true, then the value applied in the correction phase of the position information collected by the current modeling robot is , if formula (2) holds, then the value applied in the correction phase of the position information collected by the current modeling robot is , when both formula (1) and formula (2) are not true, the current distance measurement operation of the modeling robot is judged to be invalid, and the distance measurement of the same point on the distance measurement target is performed again. When the current distance measurement operation of the modeling robot is judged to be invalid twice in succession, it is judged that the current location information collected by the modeling robot is error-free, and the distance measurement and positioning of the next point on the distance measurement target are further performed; The prior data is two known points and the distance between the two points. The modeling robot position information collection frequency is set by the user end. The modeling robot position information collection frequency is the operating frequency of the distance measuring sensor in the modeling robot. Before executing position information collection, the modeling robot repeatedly collects the distance between the two known points in the prior data based on the modeling robot position information collection frequency. The collection result is recorded as , based on the collection result, the value closest to the distance between the two points in the prior data is obtained, the difference between the obtained value and the distance between the two points in the prior data is calculated, and the ratio of the difference to the distance between the two points is further calculated. The ratio is used to re-correct the position information collected by the corrected modeling robot.

2. A method for eliminating SLAM navigation cumulative error according to claim 1, characterized in that: The integrated components of the modeling robot include a mobile device, a ranging sensor and a camera. The modeling robot is operated based on SLAM control. The mobile device carries the ranging sensor and the camera to move. The ranging sensor measures the distance from its own ranging end to a point on the ranging target, and obtains the position information of a point on the ranging target relative to the initial position information based on the initial position information and the ranging result. The camera synchronously collects the ranging target image from the perspective of its own camera end to a point on the ranging target. Among them, the ranging end of the ranging sensor, the camera end of the camera and a point on the ranging target are on the same straight line; The modeling robot movement logic includes: monitoring whether the position information collected by the modeling robot in real time is received, setting the deflection angle and the rated movement distance after the position information collected by the modeling robot in real time is received, controlling the modeling robot to rotate based on the deflection angle, and after the rotation operation is completed, controlling the modeling robot to move based on the set rated movement distance again; Among them, the set deflection angle obeys: the farther the distance between the position information collected by the modeling robot in real time and the initial position information of the modeling robot is, the larger the set deflection angle is; the closer the distance between the position information collected by the modeling robot in real time and the initial position information of the modeling robot is, the smaller the set deflection angle is, and the set rated moving distance is set by the user.

3. A method for eliminating SLAM navigation cumulative error according to claim 2, characterized in that: The mobile device is connected to the ranging sensor and the camera based on an electric universal shaft. After the ranging sensor measures the distance from its own ranging end to a point on the ranging target, it synchronously identifies a point on the ranging target and a corresponding area in the ranging target image captured by the camera, and further obtains the center of the regional image in the corresponding area, which is recorded as the marking center. When the modeling robot moves based on the mobile logic, the ranging sensor and the camera synchronously control the movement based on the electric universal shaft, so that the center of the ranging target image collected by the camera in real time is always the marking center.

4. A method for eliminating SLAM navigation cumulative error according to claim 1, characterized in that: The distance from the modeling robot to the collected position information is: the distance from the ranging end of the ranging sensor to a point on the ranging target; When the modeling robot collects the position information collected last time again, the distance between the modeling robot and the collected position information is calculated, and the deflection angle is obtained synchronously in the movement logic of the modeling robot, that is, , combined with the deflection angle, the distance from the modeling robot to the collected position information is calculated when the modeling robot collects the last collected position information again.

5. A method for eliminating SLAM navigation cumulative error according to claim 1, characterized in that: The value closest to the distance between two points in the prior data based on the acquisition results is: Any group; Where: for The maximum value; for The minimum value; for The value that is closest to the distance between two points in the prior data.

6. A method for eliminating SLAM navigation cumulative error according to claim 1 or 5, characterized in that: The operation of re-correcting the position information collected by the corrected modeling robot is as follows: ； Where: To find the ratio of the difference between the value closest to the distance between two points in the prior data and the distance between two points in the prior data; in, is the distance from the ranging end of the ranging sensor to a point on the ranging target obtained after two calibrations, based on the position information when the ranging sensor performs the ranging operation, The value of and the angle of the ranging sensor's ranging end are used to obtain the position information of a point on the ranging target relative to the initial position information.

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