Robot calibration methods, equipment, and storage media based on multi-dimensional dimensions

Abstract

This application discloses a multi-dimensional robot calibration method, device, and storage medium. The multi-dimensional robot calibration method includes: in response to a target robot receiving an instruction to proceed to a target location, obtaining the desired pose corresponding to the target location; predicting the target pose of the target robot at the target location based on the desired pose, laser data obtained from scanning the target location's location markers, and the target robot's current pose; in response to the target robot's current pose being the target pose, obtaining deviation information between the target robot and the target location's location markers; and performing offset compensation processing on the target robot's current positioning parameters based on the deviation information to obtain the target robot's calibration parameters. This scheme can optimize the robot calibration effect.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and in particular to a multi-dimensional robot calibration method, device, and storage medium. Background Technology

[0002] With the continuous development of robotics technology, mobile robots are frequently used in various production scenarios to perform tasks. For example, when performing cargo handling tasks, mobile robots need to dock with the machines that hold the goods in the warehouse and identify the location of the target goods in order to accurately perform the handling task.

[0003] Therefore, the localization method used by a robot is particularly important during task execution. Currently, common localization methods typically involve matching the robot's collected LiDAR data with a prior map to achieve the desired localization.

[0004] However, in frequently changing application scenarios, prior maps may not accurately reflect the current environmental information. Furthermore, errors in the sensor parameters of the mobile robot can significantly impact its localization accuracy. Summary of the Invention

[0005] This application provides at least one multi-dimensional robot calibration method, apparatus, device, and computer-readable storage medium.

[0006] A first aspect of this application provides a multi-dimensional robot calibration method, comprising: in response to a target robot receiving an instruction to proceed to a target location, obtaining a desired pose corresponding to the target location; predicting a target pose of the target robot at the target location based on the desired pose, laser data obtained by the target robot scanning the location marker of the target location, and the current pose of the target robot; in response to the current pose of the target robot being the target pose, obtaining deviation information between the target robot and the location marker of the target location; and performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain calibration parameters of the target robot.

[0007] In one embodiment, the deviation information includes a deviation angle, the point markers include a first point marker and a second point marker respectively disposed on both sides of the target point, the target robot includes a first sensor and a second sensor, the first sensor is used to acquire the first point marker, the second sensor is used to acquire the second point marker, and the step of acquiring the deviation information between the target robot and the point markers of the target point includes: acquiring first deviation information between the first sensor of the target robot and the first point marker, and second deviation information between the second sensor of the target robot and the second point marker; determining the deviation angle of the target robot at the target point based on the first deviation information, the second deviation information, and the sensor distance between the first sensor and the second sensor.

[0008] In one embodiment, the deviation information further includes a first deviation distance of the target robot relative to the target point in a first direction, where the first direction is the path of the target robot to dock with the target point. The calibration parameters include a calibration angle and a first calibration distance in the path. The step of performing offset compensation processing on the current positioning parameters of the target robot according to the deviation information to obtain the calibration parameters of the target robot includes: compensating the current positioning parameters of the target robot according to the deviation angle to obtain the calibration angle; adjusting the current running angle of the target robot according to the deviation angle to obtain the adjusted running angle; acquiring first deviation information between the first sensor and the first point marker and / or second deviation information between the second sensor and the second point marker when the target robot is at the adjusted running angle; and controlling the target robot to move in the path according to the first deviation information and / or the second deviation information to obtain the first calibration distance of the target robot in the path.

[0009] In one embodiment, the deviation information further includes a second deviation distance of the target robot relative to the target point in a second direction, the second direction being perpendicular to the first direction. The calibration parameters include a second calibration distance of the target robot and the target point in the second direction. The step of performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot includes: controlling the target robot to move in the second direction based on the second deviation distance to obtain the movement distance of the target robot in the second direction; and determining the second calibration distance based on the movement distance in response to a match between the movement distance and the second deviation distance.

[0010] In one embodiment, the step of predicting the target pose of the target robot at the target point based on the desired pose, the laser data obtained by the target robot scanning the point marker of the target point, and the current pose of the target robot includes: determining the marker pose of the point marker based on the laser data obtained by the target robot scanning the point marker of the target point; and performing matrix operation processing on the desired pose, the marker pose, the laser extrinsic parameters of the target robot, and the current pose of the target robot to obtain the target pose.

[0011] In one embodiment, the location marker includes three preset reflective markers, namely a first reflective marker, a second reflective marker, and a third reflective marker. The first reflective marker and the second reflective marker are respectively symmetrically arranged on both sides of the third reflective marker. The distance between the first reflective marker and the third reflective marker, as well as the distance between the second reflective marker and the third reflective marker, are fixed values. The size of the third reflective marker is smaller than that of the first reflective marker and the second reflective marker.

[0012] In one embodiment, after the step of performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot, the method further includes: obtaining the initial coordinate information of the location identifier; in response to the target robot detecting the presence of other robots heading to the target location, obtaining the current coordinate information of the location identifier identified by the other robots; and sending the relative deviation between the initial coordinate information and the current coordinate information to the other robots, so that the other robots perform offset compensation processing on the positioning parameters based on the received relative deviation.

[0013] In one embodiment, after the step of performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot, the method further includes: in response to the target robot receiving an instruction to go to another location, obtaining the target pose of the target robot at the other location; controlling the target robot to travel to the other location with the calibration parameters; in response to the current pose of the target robot being the target pose of the other location, obtaining current deviation information between the target robot and the location identifier of the other location; and performing offset compensation processing on the expected pose of the other location based on the current deviation information to obtain the calibration parameters of the other location.

[0014] A second aspect of this application provides a multi-dimensional robot calibration device, comprising: an acquisition module, configured to acquire a desired pose corresponding to the target point in response to a target robot receiving an instruction to proceed to a target point; a pose determination module, configured to predict a target pose of the target robot at the target point based on the desired pose, laser data obtained by the target robot scanning the point marker of the target point, and the current pose of the target robot; a deviation acquisition module, configured to acquire deviation information between the target robot and the point marker of the target point in response to the current pose of the target robot being the target pose; and a calibration module, configured to perform offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain calibration parameters of the target robot.

[0015] A third aspect of this application provides an electronic device including a memory and a processor, the processor being used to execute program instructions stored in the memory to implement the above-described multi-dimensional robot calibration method.

[0016] The fourth aspect of this application provides a computer-readable storage medium having program instructions stored thereon, which, when executed by a processor, implement the above-described multi-dimensional robot calibration method.

[0017] The above scheme, in response to the target robot receiving an instruction to proceed to a target location, acquires the desired pose corresponding to that location. During the process of the target robot accurately reaching the target location, laser data obtained by scanning the location markers of the target location is used. Based on the desired pose, the laser data, and the target robot's current pose, the ideal pose of the target robot at the target location can be predicted. If the target robot's current pose matches the target pose, the deviation information between the target robot and the location markers of the target location is acquired. The acquired deviation information is used to perform offset compensation processing on the target robot's current positioning parameters to obtain the target robot's calibration parameters. This allows the target robot's pose to be determined through location markers, eliminating odometry errors and eliminating reliance on laser navigation maps. This also eliminates docking fluctuations caused by map changes, optimizing the robot's calibration performance.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this application. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application.

[0020] Figure 1This is a flowchart illustrating an exemplary embodiment of the multi-dimensional robot calibration method of this application;

[0021] Figure 2 This is a simplified schematic diagram illustrating one of the applicable scenarios of the multi-dimensional robot calibration method proposed in this application.

[0022] Figure 3 This is a schematic diagram of the scenario for determining the deviation angle in the multi-dimensional robot calibration method of this application;

[0023] Figure 4 This is a schematic diagram of the reflective marking setting method in the multi-dimensional robot calibration method of this application;

[0024] Figure 5 This is a block diagram illustrating a multi-dimensional robot calibration device as an exemplary embodiment of this application;

[0025] Figure 6 This is a schematic diagram of the structure of an embodiment of the electronic device of this application;

[0026] Figure 7 This is a schematic diagram of the structure of an embodiment of the computer-readable storage medium of this application. Detailed Implementation

[0027] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0028] In the following description, specific details such as particular system architectures, interfaces, and technologies are presented for illustrative purposes rather than for limiting purposes, in order to provide a thorough understanding of this application.

[0029] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, "many" in this document means two or more. Moreover, the term "at least one" in this document means any combination of at least two of any one or more of a plurality of objects. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0030] For ease of understanding, specific scenarios in which the calibration method of this application can be applied are illustrated below. The robot in this application refers to a mobile robot or a mobile device, which executes corresponding tasks based on different received instructions. Taking a common robot operation scenario as an example, after receiving an instruction to go to a target location, the robot will move to that location. In existing technologies, the robot typically matches real-time laser data acquired via LiDAR with a prior map to determine its real-time pose; further, it may combine sensors such as odometry and ranging photoelectric devices to assist in localization.

[0031] However, when the working environment changes frequently—for example, when objects are frequently added or removed, or when moving objects are present—the current environmental information will differ significantly from the prior map. If the current laser data is not processed and directly matched with the prior map, it is highly likely to cause a large matching error, resulting in low robot positioning accuracy and poor docking between the robot and the target location.

[0032] Taking a warehousing environment as an example, when a mobile robot performs a task, it needs to dock with a machine located at a target point in the warehouse. Therefore, it needs to accurately identify the machine's position to perform the task accurately. It should be noted that the robot calibration method of this application is not limited to warehousing environments (such as handling robots), but can also be applied to other environments involving mobile robots (such as sweeping robots, flying robots, etc.), which will not be elaborated here. It should also be noted that the robot calibration method of this application can be applied to robots, or to servers or terminal devices that have a communication connection with the robot. The specific implementation process can be adjusted according to actual needs, and this application does not limit it.

[0033] Please see Figure 1 , Figure 1 This is a flowchart illustrating an exemplary embodiment of the multi-dimensional robot calibration method of this application. Specifically, it may include the following steps:

[0034] Step S110: In response to the target robot receiving the instruction to go to the target point, the desired pose corresponding to the target point is obtained.

[0035] It should be noted that the method in this application is mainly illustrated using a warehousing environment as an example. In a warehousing environment, robots typically need to dock at a target location and a machine used to store goods. The target location can be a preset coordinate point or a preset area; this application does not impose any limitations. See, for example... Figure 2 As shown, Figure 2This is a simplified schematic diagram illustrating one of the applicable scenarios for the multi-dimensional robot calibration method of this application. Therefore, to improve the robot's positioning and calibration accuracy, point markers can be set at least at the target point. In this application, the point markers set at the target point can be placed on the machine and / or at other locations at the target point. If the method of this application is applied to other environments without a machine, the point markers can be adaptively adjusted and placed at appropriate locations on the target point; this will not be elaborated upon here.

[0036] The instruction received by the target robot to go to the target location can be included in the pending tasks issued to the target robot (e.g., the target robot needs to go to the target location to perform the task according to the received pending tasks), or it can be issued directly (e.g., the target robot goes to the target location according to the received movement instruction). There is no limitation here.

[0037] The application scenarios of this application may include one or more points, which are not limited here. In this embodiment, the point that the target robot needs to go to is called the target point. Among each point, at least the target point needs to be marked with a point identifier, while other points may or may not be marked with point identifiers, which is not limited in this application. It should be noted that each point has its corresponding expected pose. (This refers to the desired pose of the target robot relative to the designated point when the target robot and the designated point are precisely docked.) Essentially, each point has its corresponding docking parameters for precise docking with the target robot. The desired pose can be preset and sent to the target robot by the server (this can include the server actively sending the pose and / or the server passively sending it in response to a request from the target robot). Specifically, the desired pose for the target point can be obtained only when the target robot receives an instruction to go to the target point; alternatively, the server can pre-send the desired poses of one or more points to the target robot, and the target robot can retrieve the desired pose for the target point from its own storage when it receives an instruction to go to the target point. This is not limited here.

[0038] Step S120: Predict the target pose of the target robot at the target point based on the desired pose, the laser data obtained by the target robot scanning the target point marker, and the current pose of the target robot.

[0039] Based on the steps described above, after the target robot receives the instruction to proceed to the target location, it can obtain the desired pose corresponding to the target location. The desired pose is the pose of the target robot relative to the location marker. Therefore, it is also necessary to determine the pose of the target robot in the ideal state after arriving at the target location, which is the target pose.

[0040] In the process of the target robot docking with the machine at the target location, the laser data obtained by scanning the location marker at the target location can be used to determine the pose of the location marker. The current pose of the target robot is

[0041] Specifically, let the target point be A. During the docking process between the target robot and the machine at the target point, its expected position is... The identified target point's positional orientation is The current pose of the target robot is Combined with the laser extrinsic parameters of the target robot By performing matrix operations, the target pose of the target robot can be predicted.

[0042] For example, the mathematical expression of the target pose can be:

[0043]

[0044] Step S130: In response to the target robot's current pose being the target pose, obtain the deviation information between the target robot and the target point's position identifier.

[0045] To illustrate with the steps described above, the current pose of the target robot is the target pose. This is equivalent to the target robot reaching the target pose. Then, it is necessary to obtain the deviation information between the target robot and the target point's location marker to determine whether there is a deviation during the docking process between the target robot and the target point's machine, and whether the target robot needs to be calibrated.

[0046] For ease of explanation, the target point identifier will be referred to as the target point identifier in the following text. The deviation information may include, but is not limited to, the angular deviation and distance deviation between the target robot and the target point identifier.

[0047] For example, the method for obtaining deviation information in this application can be implemented by at least one sensor installed on the target robot. The sensor may include, but is not limited to, lidar, image sensors, photoelectric sensors, etc. By identifying the deviation information between the target robot and the target location marker using the sensors on the target robot, it can be determined whether there is a deviation during the docking process between the target robot and the target location machine. In addition to the aforementioned sensors, the target robot in this application may also include an odometer for initially estimating changes in robot angle and distance. A common odometer is a wheel encoder, which can estimate the robot's pose at the current moment based on the pose changes at previous and current moments and the pose at the previous moment. Further sensor configurations may also be included; specific details can be found in existing robot configurations, which will not be elaborated here.

[0048] Step S140: Perform offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot.

[0049] To illustrate the steps outlined above, if the deviation information indicates a discrepancy between the target robot and the target location's identifier, then offset compensation processing is required for the target robot's current positioning parameters to obtain the compensated (calibrated) positioning parameters, which are the target robot's calibration parameters. If the deviation information indicates no discrepancy between the target robot and the target location's identifier, then offset compensation processing is unnecessary, and the calibration parameters can be obtained directly.

[0050] The current positioning parameters may include, but are not limited to, the target robot's current pose and laser extrinsic parameters. After offset compensation processing of the current positioning parameters, calibration parameters can be obtained. The calibration parameters may include, but are not limited to, the target robot's adjusted pose, adjusted laser extrinsic parameters, and offset adjustment amount.

[0051] For example, the deviation information may include angular deviation and / or distance deviation. Therefore, based on the deviation information, the target robot can be adjusted in direction based on the angular deviation and / or in displacement based on the distance deviation, so that the target robot after offset adjustment can accurately dock with the target point machine.

[0052] As can be seen, this application responds to the target robot receiving an instruction to proceed to a target location by acquiring the desired pose corresponding to that target location. During the process of the target robot accurately reaching the target location, laser data obtained by scanning the target location's markers can be used. Based on the desired pose, the laser data, and the target robot's current pose, the target pose that the target robot should ideally be at the target location can be predicted. If the target robot's current pose is the target pose, the deviation information between the target robot and the target location's markers is acquired. The acquired deviation information is used to perform offset compensation processing on the target robot's current positioning parameters to obtain the target robot's calibration parameters. Therefore, the target robot's pose can be determined through the markers, eliminating the robot's odometry error and eliminating reliance on the laser navigation environment map. This eliminates docking fluctuations caused by map changes and optimizes the robot's calibration effect.

[0053] Based on the above embodiments, this application embodiment describes the steps for obtaining deviation information between the target robot and the point markers of the target point. The deviation information includes a deviation angle, and the point markers include a first point marker and a second point marker respectively disposed on both sides of the target point. The target robot includes a first sensor and a second sensor; the first sensor is used to acquire the first point marker, and the second sensor is used to acquire the second point marker. Specifically, the method of this embodiment includes the following steps:

[0054] Acquire first deviation information between the first sensor of the target robot and the first point marker, and second deviation information between the second sensor of the target robot and the second point marker; determine the deviation angle of the target robot at the target point based on the first deviation information, the second deviation information, and the sensor distance between the first sensor and the second sensor.

[0055] For example, refer to Figure 3 As shown, Figure 3 This is a schematic diagram illustrating the scenario for determining the deviation angle in the multi-dimensional robot calibration method of this application. Relative to the docking direction between the target robot and the target point station, a first point marker and a second point marker can be set on the left and right sides of the target point, respectively. The target robot is equipped with a first sensor and a second sensor; the first sensor is used to acquire the first point marker, and the second sensor is used to acquire the second point marker.

[0056] It should be noted that the location markers in this application may include, but are not limited to, reflective markers and image markers (such as QR code markers, barcode markers, etc.). Reflective markers are mainly used to reflect the laser point cloud data emitted by the robot's lidar, allowing the robot to perform positioning and calibration using the acquired laser data; image markers are mainly used by the robot to perform image recognition using visual technology to achieve positioning and calibration. The specific method of setting up the location markers needs to be adapted to the specific application scenario, and is not limited here. For example, in the target location of this application, only reflective markers, only image markers, or both reflective markers and image markers may be set.

[0057] For example, in the process of the target robot determining the target pose based on the point markers, a reflective marker can be set, and the pose of the reflective marker can be determined by the laser point cloud data reflected by the reflective marker. In the process of the target robot determining the deviation angle based on the point markers, a QR code marker can be set, and the deviation angle can be determined by the recognition effect of the QR code marker. In the process of the target robot determining the deviation distance based on the point markers, the deviation distance can still be determined by the recognition effect of the QR code marker and / or by the photoelectric ranging technology of the photoelectric sensor, which is not limited here. The above is only one possible implementation of this application, and the specific implementation can be flexibly adjusted and combined according to the application scenario, which will not be elaborated here.

[0058] Specifically, in combination Figure 3 For clarity, in this embodiment, the first and second location markers can be QR code markers. The target robot reaches the target pose. At the same time, the existing identification method can obtain the first deviation information d1 between the first sensor and the first point marker in the docking direction, which is equivalent to the left deviation information. It can also obtain the second deviation information between the second sensor and the second point marker in the docking direction, which is equivalent to the right deviation information d2.

[0059] Furthermore, the sensor distance L between the first sensor and the second sensor is obtained. b (It can be preset or acquired in real time, which is not limited here), based on the first deviation information d1, the second deviation information d2, and the sensor distance L b The deviation angle α1 of the target robot at the target point is calculated. This can be done by referring to the principles of trigonometric functions, and its mathematical expression can be:

[0060] α1=(d1-d2) / L b

[0061] It should be noted that the calculation process for (d1-d2) in this application is because, due to the recognition direction, one of the data in d1 or d2 may be negative. However, the calculation process essentially involves summing the distances d1 and d2 and then comparing this sum with the sensor distance to obtain the deviation angle. This deviation angle α1 can then be compensated for in the target robot's laser extrinsic parameters. The calibration parameters of the target robot are obtained from the yaw angle.

[0062] Based on the above embodiments, this application embodiment describes the steps of performing offset compensation processing on the current positioning parameters of the target robot according to the deviation information to obtain the calibration parameters of the target robot. The deviation information further includes a first deviation distance of the target robot relative to the target point in a first direction, where the first direction is the direction in which the target robot moves towards the target point for docking. The calibration parameters include a calibration angle and the first calibration distance in the direction of movement. Specifically, the method of this embodiment includes the following steps:

[0063] The current positioning parameters of the target robot are compensated based on the deviation angle to obtain the calibration angle; the current running angle of the target robot is adjusted based on the deviation angle to obtain the adjusted running angle; the first deviation information between the first sensor and the first position marker and / or the second deviation information between the second sensor and the second position marker are obtained when the target robot is at the adjusted running angle; the target robot is controlled to move in the direction of travel based on the first deviation information and / or the second deviation information to obtain the first calibration distance of the target robot in the direction of travel.

[0064] Referring to the foregoing embodiments, after compensating the laser extrinsic parameters of the target robot, the compensated angle (i.e., the calibrated angle) is obtained. The current running angle of the target robot is also adjusted according to the deviation angle, so that the target robot is aligned with the machine to be docked at the target point, which is equivalent to the docking surface of the target robot being parallel to the docking surface of the machine to be docked at the target point.

[0065] Even after angle alignment, there may still be displacement deviations between the target robot and the machine at the target point. Please refer to [the relevant documentation / reference]. Figure 3The displacement deviation between the target robot and the target point can include, but is not limited to, front-back displacement deviation and left-right displacement deviation. Front-back displacement deviation refers to the first deviation distance of the target robot relative to the target point in a first direction. The first direction is the direction in which the target robot moves towards the target point (docking direction). The calibration parameters include the calibration angle and the first calibration distance in the direction of movement. For front-back displacement deviation, the identification method for determining the deviation angle in the aforementioned embodiments can still be used. After adjusting the operating angle of the target robot, the identified front-back displacement deviation is obtained (specifically, it can be determined by the first deviation information between the first sensor and the first point marker and / or the second deviation information between the second sensor and the second point marker). For example, the first deviation information can be used as the front-back displacement deviation, or the second deviation information can be used as the front-back displacement deviation, or the average of the first and second deviation information can be used as the front-back displacement deviation, etc., which is not limited here.

[0066] Then, based on the front and rear deviation distance, the target robot is controlled to move in the direction of travel (docking direction), so that the target robot recognizes that the front and rear deviation distance is zero or less than or equal to the preset offset distance threshold, and the first calibration distance of the target robot in the direction of travel is obtained.

[0067] Based on the above embodiments, this application embodiment describes the steps of performing offset compensation processing on the current positioning parameters of the target robot according to the deviation information to obtain the calibration parameters of the target robot. The deviation information further includes a second deviation distance of the target robot relative to the target point in a second direction, the second direction being perpendicular to the first direction. The calibration parameters include the second calibration distance between the target robot and the target point in the second direction. Specifically, the method of this embodiment includes the following steps:

[0068] The target robot is controlled to move in the second direction based on the second deviation distance, and the movement distance of the target robot in the second direction is obtained; in response to the matching of the movement distance and the second deviation distance, the second calibration distance is determined based on the movement distance.

[0069] Referring to the foregoing embodiments, the foregoing embodiments compensated for the offset angle and the first deviation distance (front-to-back deviation distance). However, in reality, there may still be displacement offset between the target robot and the machine platform at the target point in the second direction. The second direction is perpendicular to the first direction, and the deviation distance in the second direction is equivalent to the left-to-right deviation distance.

[0070] For example, the target robot can obtain the second deviation distance by similarly adopting the scheme in the foregoing embodiment of identifying the first point marker and the second point marker to determine the distance between the first sensor and the first point marker in the second direction and / or the distance between the second sensor and the second point marker in the second direction, and then determine the second deviation distance (left and right deviation distance) based on the distance between the first sensor and the first point marker in the second direction and / or the distance between the second sensor and the second point marker in the second direction.

[0071] Similarly, referring to the aforementioned embodiments, the target robot is controlled to move in the second direction according to the second deviation distance to obtain the moving distance. The moving distance and the second deviation distance are matched, and then the second calibration distance can be determined based on the moving distance.

[0072] For example, to ensure that the target robot docks with the target point machine in a centered position, the target robot needs to be moved left and right so that the distance between the first sensor and the first point marker of the target robot in the second direction and the distance between the second sensor and the second point marker in the second direction are the same. In other words, the distance between the two side sensors of the target robot and the corresponding two side point markers is the same, so as to keep the target robot in a centered position relative to the target point machine.

[0073] Furthermore, for example, the distance between the first sensor and the first position marker in the second direction is 20cm, and the distance between the second sensor and the second position marker in the second direction is 30cm. To determine that the target robot is in a centered pose relative to the target position platform, the distance between the first sensor and the first position marker in the second direction and the distance between the second sensor and the second position marker in the second direction should be the average of the two distances (20+30) / 2 = 25cm. Therefore, the second deviation distance is ±5cm, which means that the target robot needs to be controlled to move in the direction with the larger distance in the second direction until the moving distance is equal to the second deviation distance.

[0074] It should also be noted that the method for determining the second deviation distance (left-right offset distance) in this embodiment may include, but is not limited to, identifying the distance between the left and right QR code labels using image sensors on the left and right sides of the robot, respectively, to obtain distances c1 and c2. For a handling robot, lifting arms are typically located on both sides, so the image sensors can be mounted on the lifting arms on both sides, without limitation. Alternatively, the distances between the target robot and the left and right sides of the platform can be measured using photoelectric sensors on the left and right sides of the robot, respectively, to obtain distances c1 and c2. Alternatively, the left-right distances measured by the image sensors and the left-right distances measured by the photoelectric sensors can be averaged to obtain distances c1 and c2, without limitation.

[0075] Based on the above embodiments, this application embodiment describes the steps of predicting the target pose of the target robot at the target point based on the desired pose, the laser data obtained by the target robot scanning the target point's identifier, and the target robot's current pose. Specifically, the method of this embodiment includes the following steps:

[0076] Based on the laser data obtained by the target robot scanning the target point markers, the marker pose is determined; matrix operations are performed on the desired pose, marker pose, laser extrinsic parameters of the target robot, and the current pose of the target robot to obtain the target pose.

[0077] In conjunction with the foregoing embodiments, the method for determining the target pose provided in this embodiment has been described in the foregoing embodiments. Specifically, it involves performing matrix operations on the desired pose of the target point obtained by the target robot, the laser data of the point marker obtained by scanning the point marker (point marker pose), the current pose of the target robot, and the laser extrinsic parameters of the target robot. The target pose that the target robot should reach under ideal conditions can then be obtained. This will not be elaborated further here.

[0078] Based on the above embodiments, it should be noted that in the point marking setting method of this application, the point marking may include reflective markings and image markings. See, for example... Figure 4 As shown, Figure 4This is a schematic diagram illustrating the reflective marker setting method in the multi-dimensional robot calibration method of this application. The diagram is primarily shown from the perspective of the robot's LiDAR. The reflective markers in this application can be an odd number (at least one, preferably multiple). Taking a point marker comprising three preset reflective markers as an example, these are a first reflective marker, a second reflective marker, and a third reflective marker. The first and second reflective markers are symmetrically positioned on either side of the third reflective marker. The spacing between the first and third reflective markers, as well as the spacing between the second and third reflective markers, are fixed values. The size of the third reflective marker is smaller than that of the first and second reflective markers (e.g., ...). Figure 4 (Among them, the third reflective mark is thinner than the first and second reflective marks).

[0079] It should be noted that by using the above method to set up reflective markers, the reflective markers on both sides are symmetrically arranged with respect to the central reflective marker, and the spacing between any two adjacent reflective markers is a fixed value. This allows for the elimination of interfering reflective point clouds in the environment during the docking process between the target robot and the machine, based on a preset point cloud distance. Furthermore, because the reflective marker in the middle is smaller, it avoids excessive laser point clouds hitting the central reflective marker, thus preventing a large center deviation calculated by the target robot.

[0080] Based on the above embodiments, this application embodiment describes the steps after performing offset compensation processing on the current positioning parameters of the target robot according to the deviation information to obtain the calibration parameters of the target robot. Specifically, the method of this embodiment includes the following steps:

[0081] Obtain the initial coordinate information of the location marker; in response to the target robot detecting the presence of other robots heading towards the target location, obtain the current coordinate information of the location marker identified by the other robots; send the relative deviation between the initial coordinate information and the current coordinate information to the other robots so that the other robots can perform offset compensation processing of the positioning parameters based on the received relative deviation.

[0082] Referring to the foregoing embodiments, the specific application scenarios of this application typically include multiple robots and multiple locations. Different robots may have different laser extrinsic parameters, requiring different calibrations. Furthermore, for machines at different locations, installation deviations between machines and installation deviations of location markers can lead to docking deviations between the same robot and different machines. However, calibrating each robot and each machine separately would be extremely time-consuming and labor-intensive.

[0083] Therefore, this application also proposes a robot calibration method that can extend the calibration parameters of a target robot to other robots in the current scene by calibrating the target robot, thereby improving the calibration efficiency of other robots. Essentially, it uses the calibrated target robot as a benchmark to calibrate other robots.

[0084] The initial coordinate information of the point marker refers to the initial coordinate information of the point marker identified by the calibrated target robot at the target point.

[0085] For example, let the target robot be denoted as B1, and its offset-adjusted pose be denoted as Z. Figure 4 In the example where the target location has three reflective markers, the coordinates of the three reflective markers recorded by B1 at point Z are as follows: (First location marker) (Second location marker) and (Third point marker). The coordinates of the reflective marker can be the coordinates of its geometric center or other coordinate data corresponding to the reflective marker. This application does not limit the scope of the reference.

[0086] After B1 leaves the target location, B1 can report the various data obtained in the aforementioned embodiments to the server and / or other robots, which is not limited here. For example, in response to the target robot detecting the presence of another robot B2 heading towards the target location, it can send the initial coordinate information of the reflective marker to the corresponding other robot B2. When the other robot B2 reaches point Z, it will obtain its current coordinate information based on the recognition result of the reflective marker. and Other robots can use ICP (Iterative Closest Point) matching technology to match the initial coordinate information with the current coordinate information to obtain the actual relative positional deviation between robots B1 and B2. and This refers to the displacement deviation between the laser extrinsic parameters of the two robots, where... This represents the x and y dimensions of the robot's pose in its body coordinate system. In other words, using the B1 robot as the baseline robot, it can use... This is used to adjust the displacement deviation of the laser extrinsic parameters of other robots. As for the angle deviation, the angle deviation compensation method for the target robot in the previous embodiment can be referred to in the same way. Other robots can also compensate for the laser extrinsic parameter angle in this way, which will not be elaborated here.

[0087] In addition to the target robot sending its initial coordinate information to other robots for processing as described above, other robots can also send their current coordinate information to the target robot, which then processes the information and sends the required displacement deviation to the other robots for adjustment. Alternatively, the target robot can send its initial coordinate information to the server, which then actively sends the information to the other robots, or receives a request from another robot and sends the information thereafter, allowing the target robot to perform the aforementioned processing. Another possibility is that the target robot sends its initial coordinate information to the server, and other robots send their current coordinate information to the server, which then processes the information and sends the required displacement deviation to the other robots for adjustment.

[0088] Based on the above embodiments, this application embodiment describes the steps after performing offset compensation processing on the current positioning parameters of the target robot according to the deviation information to obtain the calibration parameters of the target robot. Specifically, the method of this embodiment includes the following steps:

[0089] In response to the target robot receiving an instruction to go to other locations, the system obtains the target robot's target pose at those locations; controls the target robot to travel to the other locations with calibration parameters; in response to the target robot's current pose being the target pose at the other locations, the system obtains the current deviation information between the target robot and the location identifiers of the other locations; and performs offset compensation processing on the expected poses of the other locations based on the current deviation information to obtain the calibration parameters for the other locations.

[0090] Other points refer to the points other than the target point in the target robot's operating scenario.

[0091] In conjunction with the foregoing embodiments, this application demonstrates that, in addition to calibrating other robots using a target robot, it can also calibrate other points using a target robot. This primarily refers to calibrating the docking parameters (e.g., desired pose) of other points.

[0092] For example, after the target robot completes the calibration of the target point, if the target robot receives an instruction to go to other points, it will similarly refer to the aforementioned embodiments to obtain the target pose of the target robot at other points (specifically, it is determined by the expected pose of other points, the point identifier pose of other points identified by the robot, the current pose of the robot, and the laser extrinsic parameters of the robot. The laser extrinsic parameters of the robot have been successfully calibrated and will not be described in detail here).

[0093] The target robot is controlled to travel to other locations using calibration parameters (calibrated laser extrinsic parameters). When the target robot reaches the target pose at another location (i.e., the target robot's current pose is the target pose at that location), similarly referring to the previous embodiment, the current deviation information between the target robot and the location markers of the other locations is obtained. Then, offset compensation processing is performed on the docking parameters (desired pose) of the other locations based on the current deviation information, rather than calibrating the target robot, to obtain the calibration parameters for the other locations. This eliminates docking differences between different locations, ensures calibration consistency between different locations, and allows different robots to achieve consistent docking positions at different locations.

[0094] Specifically, the target robot can internally perform offset compensation processing on the docking parameters (desired pose) of other points, and then upload the calibration parameters of those other points to the server. When other robots subsequently travel to those other points, they can obtain the calibrated docking parameters from the server, enabling them to reach the same pose as the target robot. Alternatively, the target robot can send its current deviation information to the server, which then calculates the calibration parameters for the other points. Or, the target robot can send its current deviation information to the server, and when other robots travel to those other points, they can obtain this information from the server, calculate the calibration parameters for those points, and so on.

[0095] For example, due to construction errors between different machine positions, the same robot may have deviations in docking position on different machine positions. In this case, the docking parameters (desired pose) associated with each point can be used directly. To correct this, the parameter is associated with the location attributes of each machine. The parameter may differ for different machines. The calculation method for this parameter is as follows:

[0096] First, after robot Bi has undergone compensation and calibration for laser extrinsic parameter angle deviation and displacement deviation at the target point in the aforementioned embodiments, it also reaches the target pose corresponding to machine Aj at the target point through the identified pose. At this point, the deviation angle β is calculated using the method described in the aforementioned embodiment. j and β j Add docking parameters to this location Within the yaw angle, complete the angle compensation calibration. Then, allow the robot to leave (exit) the machine at that point and utilize the new docking parameters. Reaching the target pose at that point again Then, by processing the displacement deviation compensation calibration method provided in the aforementioned embodiments, displacement deviation compensation can be completed, and the calibration parameters after offset compensation at that point can be obtained. After adjusting the docking parameters for each machine at each point through the above steps, the consistency of robot docking on different machines can be achieved.

[0097] Of course, this solution is not limited to using reflective strips to calculate the docking position, or using reflective strip matching to eliminate displacement deviations between different lasers; it is also applicable to using reflective pillars or good feature contours to achieve the same purpose, only the calculation method for the docking position is different.

[0098] In summary, the multi-dimensional robot calibration method proposed in this application can not only calibrate a single robot, but also extend to the calibration of other robots and other points based on the calibrated robot, thereby ensuring the consistency of a single robot or multiple robots reaching the target point.

[0099] Based on the above embodiments, this embodiment illustrates the application scenarios of robots whose sensors include at least lidar sensors, image sensors, and photoelectric sensors.

[0100] The robot described in this application can initially confirm its pose (target pose) by identifying reflective markers using LiDAR. Then, after the robot reaches the target pose, it uses image sensors on both lifting arms to identify QR code markers to confirm angular deviations and compensate for the laser angle extrinsic parameters. Next, using the lateral distance between the robot and the docking station fed back by photoelectric sensors and / or image sensors, the robot moves to the centered pose of the docking station, completing distance compensation. For compensation calibration between different robots, after different robots reach the same position in the centered pose of the docking station (i.e., the docking station center), point cloud matching is performed using the identified reflective marker poses to compensate for displacement deviations in the laser extrinsic parameters between different robots. For different docking stations, due to installation deviations between the stations and the installation deviations of the point markers, the same robot may still have positioning deviations when docking between different stations. In this case, the deviation value is recorded by the feedback from image sensors and photoelectric sensors, and this deviation value is recorded in the docking parameters of the corresponding station. During docking, the corresponding docking parameters are used to compensate for this deviation value, thereby ensuring consistency when the same or different robots dock on different stations.

[0101] It should be further noted that the execution entity of the multi-dimensional robot calibration method can be a multi-dimensional robot calibration device. For example, the multi-dimensional robot calibration method can be executed by a terminal device, server, or other processing device. The terminal device can be user equipment (UE), computer, mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA), handheld device, computing device, vehicle-mounted device, wearable device, etc. In some possible implementations, the multi-dimensional robot calibration method can be implemented by a processor calling computer-readable instructions stored in memory.

[0102] Figure 5 This is a block diagram illustrating a multi-dimensional robot calibration device as shown in an exemplary embodiment of this application. Figure 5 As shown, this exemplary multi-dimensional robot calibration device 500 includes: an acquisition module 510, a pose determination module 520, a deviation acquisition module 530, and a calibration module 540. Specifically:

[0103] The acquisition module 510 is used to acquire the desired pose corresponding to the target point in response to the target robot receiving the instruction to go to the target point.

[0104] The pose determination module 520 is used to predict the target pose of the target robot at the target point based on the desired pose, the laser data obtained by the target robot scanning the target point marker, and the current pose of the target robot.

[0105] The deviation acquisition module 530 is used to acquire deviation information between the target robot and the target point identifier in response to the target robot's current pose being the target pose.

[0106] The calibration module 540 is used to perform offset compensation processing on the current positioning parameters of the target robot based on the deviation information, so as to obtain the calibration parameters of the target robot.

[0107] In this exemplary multi-dimensional robot calibration device, in response to the target robot receiving an instruction to proceed to a target location, the desired pose corresponding to the target location is acquired. During the process of the target robot accurately reaching the target location, laser data obtained by scanning the location markers of the target location can be used. Based on the desired pose, the laser data, and the current pose of the target robot, the target pose that the target robot should ideally be at the target location can be predicted. In response to the target robot's current pose being the target pose, the deviation information between the target robot and the location markers of the target location is acquired. The acquired deviation information is used to perform offset compensation processing on the target robot's current positioning parameters to obtain the target robot's calibration parameters. This allows the target robot's pose to be determined through location markers, eliminating robot odometry errors and eliminating reliance on laser navigation environment maps. This also eliminates docking fluctuations caused by map changes, optimizing the robot's calibration performance.

[0108] It should be noted that the apparatus and method provided in the above embodiments belong to the same concept, and the specific ways in which each module and unit performs operations have been described in detail in the method embodiments, and will not be repeated here. In practical applications, the apparatus provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the apparatus can be divided into different functional modules to complete all or part of the functions described above, and this is not a limitation.

[0109] The functions of each module can be found in the implementation examples of the multi-dimensional robot calibration method, which will not be repeated here.

[0110] Please see Figure 6 , Figure 6 This is a schematic diagram of an embodiment of the electronic device of this application. The electronic device 100 includes a memory 101 and a processor 102. The processor 102 is used to execute program instructions stored in the memory 101 to implement the steps in any of the above embodiments of the multi-dimensional robot calibration method. In a specific implementation scenario, the electronic device 100 may include, but is not limited to, a microcomputer or a server. In addition, the electronic device 100 may also include mobile devices such as laptops and tablets, which are not limited here.

[0111] Specifically, processor 102 controls itself and memory 101 to implement the steps in any of the above-described embodiments of the multi-dimensional robot calibration method. Processor 102 can also be referred to as a CPU (Central Processing Unit). Processor 102 may be an integrated circuit chip with signal processing capabilities. Processor 102 can also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor. Furthermore, processor 102 can be implemented using integrated circuit chips.

[0112] In this exemplary electronic device, in response to a target robot receiving an instruction to proceed to a target location, the desired pose corresponding to the target location is acquired. During the process of the target robot accurately reaching the target location, laser data obtained by scanning the location markers of the target location is used. Based on the desired pose, the laser data, and the current pose of the target robot, the target pose that the target robot should ideally be at the target location can be predicted. In response to the target robot's current pose being the target pose, deviation information between the target robot and the location markers of the target location is acquired. The acquired deviation information is used to perform offset compensation processing on the target robot's current positioning parameters to obtain the target robot's calibration parameters. This allows the target robot's pose to be determined using location markers, eliminating robot odometry errors and eliminating reliance on laser navigation environment maps. This also eliminates docking fluctuations caused by map changes, optimizing the robot's calibration performance.

[0113] Please see Figure 7 , Figure 7 This is a schematic diagram of a computer-readable storage medium according to an embodiment of the present application. The computer-readable storage medium 110 stores program instructions 111 that can be executed by a processor. The program instructions 111 are used to implement the steps in any of the above embodiments of the multi-dimensional robot calibration method.

[0114] In this exemplary storage medium, the program instructions stored in the storage medium are executed in response to the target robot receiving an instruction to proceed to a target location, thereby obtaining the desired pose corresponding to the target location. During the process of the target robot accurately reaching the target location, laser data obtained by scanning the location markers of the target location can be used. Based on the desired pose, the laser data, and the current pose of the target robot, the target pose that the target robot should ideally be at the target location can be predicted. In response to the target robot's current pose being the target pose, the deviation information between the target robot and the location markers of the target location is obtained. The obtained deviation information is used to perform offset compensation processing on the target robot's current positioning parameters to obtain the target robot's calibration parameters. This allows the target robot's pose to be determined through location markers, eliminating robot odometry errors and eliminating reliance on laser navigation environment maps. This also eliminates docking fluctuations caused by map changes, optimizing the robot's calibration performance.

[0115] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0116] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed methods and apparatus can be implemented in other ways. For example, the apparatus implementations described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0118] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A multi-dimensional robot calibration method, characterized in that, The method includes: In response to the target robot receiving an instruction to go to the target point, the desired pose corresponding to the target point is obtained; wherein, the desired pose is the desired pose of the target robot relative to the point identifier of the target point; The target pose of the target robot at the target point is predicted based on the desired pose, the laser data obtained by the target robot scanning the point marker of the target point, and the current pose of the target robot; wherein, the target pose is the pose of the target robot when it reaches the target point under ideal conditions. In response to the target robot's current pose being the target pose, deviation information between the target robot and the point identifiers of the target point is obtained; the deviation information includes a deviation angle, the point identifiers include a first point identifier and a second point identifier respectively set on both sides of the target point, the target robot includes a first sensor and a second sensor, the first sensor is used to obtain the first point identifier, and the second sensor is used to obtain the second point identifier. The step of obtaining deviation information between the target robot and the location identifier of the target point includes: obtaining first deviation information between the first sensor of the target robot and the first location identifier, and second deviation information between the second sensor of the target robot and the second location identifier; determining the deviation angle of the target robot at the target point based on the first deviation information, the second deviation information, and the sensor distance between the first sensor and the second sensor; The target robot's current positioning parameters are offset compensation processed based on the deviation information to obtain the target robot's calibration parameters.

2. The method according to claim 1, characterized in that, The deviation information also includes a first deviation distance of the target robot relative to the target point in a first direction, where the first direction is the direction in which the target robot moves towards the target point for docking. The calibration parameters include a calibration angle and a first calibration distance in the direction of movement. The step of performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot includes: The calibration angle is obtained by compensating the current positioning parameters of the target robot based on the deviation angle. The current running angle of the target robot is adjusted according to the deviation angle to obtain the adjusted running angle; Acquire the first deviation information between the first sensor and the first point marker and / or the second deviation information between the second sensor and the second point marker when the target robot is at the adjusted running angle; Based on the first deviation information and / or the second deviation information, the target robot is controlled to move in the direction of travel to obtain the first calibrated distance of the target robot in the direction of travel.

3. The method according to claim 1, characterized in that, The deviation information also includes a second deviation distance of the target robot relative to the target point in a second direction, the second direction being perpendicular to the first direction. The calibration parameters include the second calibration distance between the target robot and the target point in the second direction. The step of performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot includes: Based on the second deviation distance, the target robot is controlled to move in the second direction, thereby obtaining the movement distance of the target robot in the second direction; In response to the matching of the travel distance and the second deviation distance, the second calibration distance is determined based on the travel distance.

4. The method according to claim 1, characterized in that, The step of predicting the target pose of the target robot at the target point based on the desired pose, the laser data obtained by the target robot scanning the point markers of the target point, and the current pose of the target robot includes: The pose of the marker is determined based on the laser data obtained by the target robot scanning the marker of the target point. The target pose is obtained by performing matrix operations on the desired pose, the identified pose, the laser extrinsic parameters of the target robot, and the current pose of the target robot.

5. The method according to claim 4, characterized in that, The location marker includes three preset reflective markers, namely a first reflective marker, a second reflective marker, and a third reflective marker. The first reflective marker and the second reflective marker are respectively symmetrically arranged on both sides of the third reflective marker. The distance between the first reflective marker and the third reflective marker, as well as the distance between the second reflective marker and the third reflective marker, are fixed values. The size of the third reflective marker is smaller than that of the first reflective marker and the second reflective marker.

6. The method according to claim 1, characterized in that, After the step of performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot, the method further includes: Obtain the initial coordinate information of the point identifier; In response to the target robot detecting the presence of other robots heading towards the target location, the current coordinate information of the location identifier identified by the other robots is obtained; The relative deviation between the initial coordinate information and the current coordinate information is sent to the other robots so that the other robots can perform offset compensation processing of the positioning parameters based on the received relative deviation.

7. The method according to claim 1, characterized in that, After the step of performing offset compensation processing on the current positioning parameters of the target robot based on the deviation information to obtain the calibration parameters of the target robot, the method further includes: In response to the target robot receiving an instruction to go to other locations, the target robot's target pose at those other locations is obtained; Control the target robot to travel to the other locations using the calibration parameters; In response to the target robot's current pose being the target pose of the other points, the current deviation information between the target robot and the point identifiers of the other points is obtained; Based on the current deviation information, offset compensation processing is performed on the expected pose of the other points to obtain the calibration parameters of the other points.

8. An electronic device, characterized in that, The method includes a memory and a processor, the processor being configured to execute program instructions stored in the memory to implement the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having program instructions stored thereon, characterized in that, When the program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

Images