Simultaneous localization and mapping parameter determination method and device, equipment and storage medium

Abstract

This disclosure relates to a method, apparatus, device, and storage medium for determining synchronous positioning and mapping parameters. The method includes: determining the driving status information of the object to be located within a target time period based on pre-acquired path planning information of the object to be located, wherein the target time period includes the current time period and / or a set time period after the current time period; and determining synchronous positioning and mapping parameters of the object to be located based on the driving status information in response to detecting that the driving status information meets the set conditions. This disclosure allows the determined synchronous positioning and mapping parameters to be adapted to the driving status of the object to be located within the target time period, thereby improving the accuracy of determining the synchronous positioning and mapping parameters, thus improving the continuity of subsequent positioning of the object to be located, and ultimately improving the quality of synchronous positioning and mapping.

Description

Technical Field

[0001] This disclosure relates to the field of machine vision technology, and in particular to a method, apparatus, device and storage medium for determining synchronous positioning and mapping parameters. Background Technology

[0002] With the development of machine vision technology, Simultaneous Localization and Mapping (SLAM) algorithms are being applied to an increasing number of technological fields, such as robotics, autonomous driving, and drones. The problem of SLAM can be described as an object (e.g., a robot, autonomous vehicle, or drone) moving from an unknown location in an unknown environment, performing self-localization based on position estimation and a map during its movement, and simultaneously building an incremental map based on its self-localization to achieve autonomous localization and navigation.

[0003] Currently, SLAM algorithms typically predetermine the synchronous localization and mapping (SMR) parameters of the object to be localized, and then perform synchronous localization and mapping based on these predetermined parameters during subsequent movement of the object. However, this parameter determination scheme can easily lead to discontinuous localization of the object, which in turn affects subsequent localization and mapping. Summary of the Invention

[0004] To overcome the problems existing in the related technologies, the present disclosure provides a method, apparatus, device and storage medium for determining synchronous positioning and mapping parameters, so as to solve the defects in the related technologies.

[0005] According to a first aspect of the present disclosure, a method for determining synchronous positioning and mapping parameters is provided, the method comprising:

[0006] Based on the path planning information of the object to be located in advance, the driving status information of the object to be located within the target time period is determined, and the target time period includes the current time period and / or the set time period after the current time period.

[0007] In response to the detection that the driving status information meets the set conditions, the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information.

[0008] In one embodiment, the driving condition information includes acceleration, and the synchronous positioning and mapping parameters include acceleration error weights from inertial sensors;

[0009] The step of determining the synchronous positioning and mapping parameters of the object to be located based on the driving status information in response to detecting that the driving status information meets the set conditions includes:

[0010] In response to detecting that the acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor is determined based on the acceleration.

[0011] In one embodiment, determining the acceleration error weight of the inertial sensor based on the acceleration includes:

[0012] Obtain the first adjustable coefficient of the predetermined acceleration error weight;

[0013] The acceleration error weight is determined based on the product of the acceleration and the first adjustable coefficient.

[0014] In one embodiment, the driving condition information includes the driving road surface type, and the synchronous positioning and mapping parameters include the error weight of the encoder.

[0015] The step of determining the synchronous positioning and mapping parameters of the object to be located based on the driving status information in response to detecting that the driving status information meets the set conditions includes:

[0016] In response to the detection that the driving road surface type belongs to a set road surface type, the error weight of the encoder is determined based on the preset error weight corresponding to the set road surface type.

[0017] In one embodiment, the defined road surface type includes road surfaces that are prone to slipping.

[0018] The method further includes:

[0019] In response to the detection of a designated object on the driving road surface by the image acquisition device, it is determined that the driving road surface type belongs to the designated road surface type, and the designated object includes at least one of the following: mud, puddle, oil stain.

[0020] In one embodiment, the driving status information includes displacement and rotational angular velocity, and the synchronous positioning and mapping parameters include the image acquisition frame rate of the image acquisition device;

[0021] The step of determining the synchronous positioning and mapping parameters of the object to be located based on the driving status information in response to detecting that the driving status information meets the set conditions includes:

[0022] In response to the detection that the displacement and the rotational angular velocity satisfy the pure rotational motion condition, the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity.

[0023] In one embodiment, determining the image acquisition frame rate of the image acquisition device based on the rotational angular velocity includes:

[0024] Obtain a second adjustable coefficient for the predetermined image acquisition frame rate;

[0025] The image acquisition frame rate is determined based on the product of the rotational angular velocity and the second adjustable coefficient.

[0026] According to a second aspect of the present disclosure, a device for determining synchronous positioning and mapping parameters is provided, the device comprising:

[0027] The status information determination module is used to determine the driving status information of the object to be located within a target time period based on the path planning information of the object to be located in advance. The target time period includes the current time period and / or a set time period after the current time period.

[0028] The synchronous positioning and mapping parameter determination module is used to determine the synchronous positioning and mapping parameters of the object to be positioned based on the driving condition information in response to the detection that the driving condition information meets the set conditions.

[0029] In one embodiment, the driving condition information includes acceleration, and the synchronous positioning and mapping parameters include acceleration error weights from inertial sensors;

[0030] The synchronous positioning and mapping parameter determination module is also used to determine the acceleration error weight of the inertial sensor based on the acceleration in response to detecting that the acceleration is less than or equal to a set threshold.

[0031] In one embodiment, the synchronous positioning and mapping parameter determination module includes:

[0032] The first adjustable coefficient acquisition unit is used to acquire the first adjustable coefficient of the predetermined acceleration error weight;

[0033] An acceleration error weight determination unit is used to determine the acceleration error weight based on the product of the acceleration and the first adjustable coefficient.

[0034] In one embodiment, the driving condition information includes the driving road surface type, and the synchronous positioning and mapping parameters include the error weight of the encoder.

[0035] The synchronous positioning and mapping parameter determination module is also used to determine the error weight of the encoder based on the preset error weight corresponding to the set road surface type in response to detecting that the driving road surface type belongs to the set road surface type.

[0036] In one embodiment, the defined road surface type includes road surfaces that are prone to slipping.

[0037] The device further includes:

[0038] The road surface type determination module is used to determine the road surface type as defined by the image acquisition device based on the detection of a defined object on the road surface. The defined object includes at least one of the following: mud, puddle, and oil stain.

[0039] In one embodiment, the driving status information includes displacement and rotational angular velocity, and the synchronous positioning and mapping parameters include the image acquisition frame rate of the image acquisition device;

[0040] The synchronous positioning and mapping parameter determination module is also used to determine the image acquisition frame rate of the image acquisition device based on the rotation angular velocity in response to detecting that the displacement and the rotation angular velocity meet the pure rotation motion condition.

[0041] In one embodiment, the synchronous positioning and mapping parameter determination module includes:

[0042] The second adjustable coefficient acquisition unit is used to acquire a second adjustable coefficient of the predetermined image acquisition frame rate;

[0043] The image acquisition frame rate determination unit is used to determine the image acquisition frame rate based on the product of the rotational angular velocity and the second adjustable coefficient.

[0044] According to a third aspect of the present disclosure, an electronic device is provided, the device comprising:

[0045] Processor and memory used to store computer programs;

[0046] The processor is configured to, when executing the computer program, implement:

[0047] Based on the path planning information of the object to be located in advance, the driving status information of the object to be located within the target time period is determined, and the target time period includes the current time period and / or the set time period after the current time period.

[0048] In response to the detection that the driving status information meets the set conditions, the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information.

[0049] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided having a computer program stored thereon, the program being implemented when executed by a processor:

[0050] Based on the path planning information of the object to be located in advance, the driving status information of the object to be located within the target time period is determined, and the target time period includes the current time period and / or the set time period after the current time period.

[0051] In response to the detection that the driving status information meets the set conditions, the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information.

[0052] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects:

[0053] This disclosure determines the driving status information of the object to be located within a target time period based on pre-acquired path planning information. In response to detecting that the driving status information meets set conditions, it determines the synchronous positioning and mapping parameters of the object based on the driving status information. Since the synchronous positioning and mapping parameters are determined based on the driving status information within the target time period, the determined synchronous positioning and mapping parameters can be adapted to the driving status of the object within the target time period, improving the accuracy of the determined synchronous positioning and mapping parameters. This enhances the continuity of subsequent positioning of the object and improves the quality of synchronous positioning and mapping.

[0054] 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 disclosure. Attached Figure Description

[0055] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0056] Figure 1 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to an exemplary embodiment of the present disclosure;

[0057] Figure 2 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to yet another exemplary embodiment of this disclosure;

[0058] Figure 3 This is a flowchart illustrating how to determine the acceleration error weight of the inertial sensor based on the acceleration, according to an exemplary embodiment of the present disclosure;

[0059] Figure 4 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to another exemplary embodiment of this disclosure;

[0060] Figure 5 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to another exemplary embodiment of the present disclosure;

[0061] Figure 6This is a flowchart illustrating how to determine the image acquisition frame rate of the image acquisition device based on the rotational angular velocity, according to an exemplary embodiment of this disclosure;

[0062] Figure 7 This is a block diagram illustrating a synchronous positioning and mapping parameter determination device according to an exemplary embodiment of the present disclosure;

[0063] Figure 8 This is a block diagram illustrating yet another synchronous positioning and mapping parameter determination device according to an exemplary embodiment of the present disclosure;

[0064] Figure 9 This is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0065] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0066] Figure 1 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to an exemplary embodiment; the method of this embodiment can be applied to a control device for an object to be positioned, which may include a robot, a drone, an autonomous vehicle, etc.

[0067] like Figure 1 As shown, the method includes the following steps S101-S102:

[0068] In step S101, based on the path planning information of the object to be located obtained in advance, the driving status information of the object to be located within the target time period is determined.

[0069] In this embodiment, the control device for the object to be located can determine the driving status information of the object within a target time period based on the pre-acquired path planning information of the object. The control device for the object to be located may include a controller or data processor installed on the object, or it may be a remote control device associated with the object, such as a remote server.

[0070] The target time period mentioned above may include the current time period and / or a set time period following the current time period. It is worth noting that the length of the aforementioned time period can be set based on actual business needs, such as being set to a unit of time length like seconds, minutes, or hours; this embodiment does not limit this. Furthermore, the set time period following the current time period can be a time period of a preset length following the current time period, such as one minute or several minutes after the current minute, or one hour or several hours after the current hour.

[0071] For example, when an object to be located is in an unknown location within an unknown environment requiring localization, pre-defined path planning information can be obtained. Then, during movement, the object's travel status within a target time period can be determined based on this path planning information. For instance, the aforementioned travel status information may include travel information and / or road condition information. Travel information may include at least one of the following: travel speed, acceleration, rotation angle, angular velocity, etc., and road condition information may include at least the type of road surface.

[0072] In step S102, in response to detecting that the driving status information meets the set conditions, the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information.

[0073] In this embodiment, when the control device of the object to be located determines the driving status information of the object to be located within the target time period based on the path planning information of the object to be located in advance, it can determine the synchronous positioning and mapping parameters of the object to be located based on the driving status information in response to detecting that the driving status information meets the set conditions.

[0074] The conditions for the aforementioned driving status information can be set based on the actual type of the driving status information, such as threshold conditions for the numerical value of the corresponding driving status information, and / or type conditions for the type of driving status information.

[0075] In one embodiment, the synchronous positioning and mapping parameters of the object to be located may include the parameters or error weights of the sensors of the object to be located. For example, the sensors of the object to be located may include various sensors and / or image acquisition devices preset on the object, and thus the synchronous positioning and mapping parameters of the object to be located may be the error weights of the corresponding sensors and / or the image acquisition parameters of the image acquisition devices, etc.

[0076] As described above, this embodiment determines the driving status information of the object to be located within a target time period based on the pre-acquired path planning information of the object to be located. In response to detecting that the driving status information meets set conditions, it determines the synchronous positioning and mapping parameters of the object to be located based on the driving status information. Since the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information within the target time period, the determined synchronous positioning and mapping parameters can be adapted to the driving status of the object within the target time period, improving the accuracy of the determined synchronous positioning and mapping parameters. This enhances the continuity of subsequent positioning of the object to be located, thereby improving the quality of synchronous positioning and mapping.

[0077] Figure 2 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to another exemplary embodiment of the present disclosure; the method of this embodiment can be applied to a control device for an object to be positioned, which may include a robot, a drone, an autonomous vehicle, etc.

[0078] In this embodiment, the driving status information may include acceleration, and the synchronous localization and mapping parameters may include the acceleration error weights of the inertial sensor (e.g., an inertial measurement unit, IMU, etc.) (i.e., the weights of the acceleration errors of the inertial sensor in the subsequent application of the synchronous localization and mapping SLAM algorithm). It is worth noting that the specific methods for performing synchronous localization and mapping SLAM based on the acceleration error weights of the inertial sensor can be found in the explanations and descriptions of related technologies (such as tightly coupled SLAM algorithms based on vision and IMU, tightly coupled SLAM algorithms based on vision, IMU, and encoder disks, etc.), and will not be elaborated upon here.

[0079] Based on this, such as Figure 2 As shown, the method includes the following steps S201-S202:

[0080] In step S201, the acceleration of the object to be located within the target time period is determined based on the path planning information of the object to be located obtained in advance.

[0081] In this embodiment, the control device for the object to be located can determine the acceleration of the object within a target time period based on pre-acquired path planning information of the object. The control device may include a controller or data processor mounted on the object, or it may be a remote control device associated with the object, such as a remote server.

[0082] The target time period mentioned above may include the current time period and / or a set time period following the current time period. It is worth noting that the length of the aforementioned time period can be set based on actual business needs, such as being set to a unit of time length like seconds, minutes, or hours; this embodiment does not limit this. Furthermore, the set time period following the current time period can be a time period of a preset length following the current time period, such as one minute or several minutes after the current minute, or one hour or several hours after the current hour.

[0083] For example, when an object to be located is in an unknown location in an unknown environment that needs to be located, pre-defined path planning information can be obtained, and then the acceleration of the object within the target time period can be determined based on the path planning information during the movement.

[0084] In step S202, in response to detecting that the acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor is determined based on the acceleration.

[0085] In this embodiment, when the control device of the object to be located determines the acceleration of the object within the target time period based on the path planning information of the object to be located in advance, the acceleration can be compared with a set threshold. Then, when the acceleration is detected to be less than or equal to the set threshold, the acceleration error weight of the inertial sensor can be determined based on the acceleration.

[0086] It is worth noting that the above-mentioned acceleration threshold can be set based on actual business needs. For example, setting it to 0 means that the object to be located is in a state of uniform linear motion during the target time period. This embodiment does not limit this.

[0087] Understandably, in uniform linear motion, the acceleration data output by the IMU of the object to be determined is extremely small due to the presence of errors, which leads to low IMU error availability and increased uncertainty. Therefore, in this embodiment, when the detected acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor can be determined based on the acceleration, thereby reducing the proportion of inertial sensor acceleration error in the subsequent Simultaneous Localization and Mapping (SLAM) algorithm.

[0088] As described above, this embodiment determines the acceleration of the object to be located within a target time period based on the path planning information of the object to be located in advance. In response to detecting that the acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor is determined based on the acceleration. Since the acceleration error weight of the inertial sensor of the object to be located is determined based on the acceleration within the target time period of the object to be located, the determined acceleration error weight can be adapted to the driving conditions of the object to be located within the target time period, which can improve the accuracy of determining the acceleration error weight. This can improve the continuity of subsequent positioning of the object to be located, thereby improving the quality of synchronous positioning and mapping.

[0089] Figure 3 This is a flowchart illustrating how to determine the acceleration error weight of the inertial sensor based on the acceleration, according to an exemplary embodiment of this disclosure. This embodiment, based on the above embodiment, provides an illustrative example of how to determine the acceleration error weight of the inertial sensor based on the acceleration. Figure 3 As shown, the step S202 above, which involves determining the acceleration error weight of the inertial sensor based on the acceleration, may include the following steps S301-S302:

[0090] In step S301, the first adjustable coefficient of the predetermined acceleration error weight is obtained.

[0091] In this embodiment, when it is necessary to determine the acceleration error weight of the inertial sensor based on the acceleration, a first adjustable coefficient of the predetermined acceleration error weight can be obtained. This first adjustable coefficient can be a parameter with an adjustable value, so that when the object to be located is officially put into use, such as during synchronous positioning and mapping based on the object, the acceleration error weight can be adjusted based on this first adjustable coefficient to make the adjusted acceleration error weight more in line with actual needs.

[0092] In step S302, the acceleration error weight is determined based on the product of the acceleration and the first adjustable coefficient.

[0093] In this embodiment, after obtaining the first adjustable coefficient of the predetermined acceleration error weight, the acceleration error weight can be determined based on the product of the acceleration and the first adjustable coefficient. For example, after determining the first adjustable coefficient of the acceleration error weight and the acceleration of the object to be located, the product of the acceleration and the first adjustable coefficient can be calculated, and then the product can be used to determine the acceleration error weight.

[0094] As described above, this embodiment obtains a first adjustable coefficient of the predetermined acceleration error weight and determines the acceleration error weight based on the product of the acceleration and the first adjustable coefficient. This allows the determined acceleration error weight to be adapted to the driving conditions of the object to be located within the target time period. Furthermore, it enables subsequent adjustment of the acceleration error weight based on the first adjustable coefficient, which can further improve the accuracy of determining the acceleration error weight and thus enhance the quality of subsequent synchronous positioning and mapping.

[0095] Figure 4 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to another exemplary embodiment of the present disclosure; the method of this embodiment can be applied to a control device for an object to be positioned, which may include a robot, a drone, an autonomous vehicle, etc.

[0096] In this embodiment, the driving condition information may include the road surface type, and the simultaneous localization and mapping (SLAM) parameters include the encoding disk error weights (i.e., the weights of the encoding disk errors in the subsequent application of the SLAM algorithm). It is worth noting that the specific methods for performing SLAM based on the encoding disk error weights can be found in explanations and descriptions of related technologies (such as tightly coupled SLAM algorithms based on vision and encoding disks, and tightly coupled SLAM algorithms based on vision, IMU, and encoding disks, etc.), and will not be elaborated upon here.

[0097] Based on this, such as Figure 4 As shown, the method includes the following steps S401-S402:

[0098] In step S401, based on the path planning information of the object to be located obtained in advance, the road surface type of the object to be located within the target time period is determined.

[0099] In this embodiment, the control device for the object to be located can determine the road surface type for the target time period based on the pre-acquired path planning information of the object. The control device may include a controller or data processor mounted on the object, or it may be a remote control device associated with the object, such as a remote server.

[0100] The target time period mentioned above may include the current time period and / or a set time period following the current time period. It is worth noting that the length of the aforementioned time period can be set based on actual business needs, such as being set to a unit of time length like seconds, minutes, or hours; this embodiment does not limit this. Furthermore, the set time period following the current time period can be a time period of a preset length following the current time period, such as one minute or several minutes after the current minute, or one hour or several hours after the current hour.

[0101] For example, when an object to be located is in an unknown location within an unknown environment requiring positioning, pre-defined path planning information can be obtained. Then, during movement, the type of road surface to be traveled within a target time period can be determined based on this path planning information. The types of road surfaces can be set according to actual business needs, such as dry surfaces (not prone to slipping) or muddy / icy surfaces (prone to slipping). This embodiment does not limit the specific types.

[0102] In step S402, in response to detecting that the driving road surface type belongs to a set road surface type, the error weight of the encoder is determined based on the preset error weight corresponding to the driving road surface type.

[0103] In this embodiment, when the control device of the object to be located determines the type of the road surface within the target time period of the object to be located based on the path planning information of the object to be located in advance, it can match the type of the road surface with the set road surface type. Then, when it is detected that the type of the road surface matches the set road surface type, it is determined that the type of the road surface belongs to the set road surface type. Then, the error weight of the encoder can be determined based on the preset error weight corresponding to the set road surface type.

[0104] It is worth noting that the preset error weights corresponding to the aforementioned road surface types can be set in advance. For example, a corresponding error weight set {wn} can be defined for different road surface types. Then, when the driving road surface type is detected to belong to the set road surface type, the error weight of the encoder can be determined directly based on the preset error weights in the aforementioned error weight set {wn} corresponding to the set road surface type.

[0105] In one embodiment, the aforementioned road surface type can be a road surface type prone to slippage. Exemplarily, this embodiment may further include: in response to the detection of a designated object on the road surface by an image acquisition device, determining that the road surface type belongs to the designated road surface type, wherein the designated object includes at least one of the following: mud, puddles, oil stains. The image acquisition device may include a camera, etc. That is, the object to be located can detect the presence of the aforementioned designated object on the road surface using its own image acquisition device, and then, when the presence of the designated object is detected, determine that the road surface type belongs to a road surface type prone to slippage.

[0106] It is understandable that when the object to be located is a robot or autonomous vehicle moving using wheels, the encoder data of the object will be inaccurate when the wheels are slipping, leading to increased uncertainty in the encoder error. Therefore, in this embodiment, when the road surface type is detected to belong to a set road surface type, the error weight of the encoder can be determined based on the preset error weight corresponding to the set road surface type, thereby appropriately adjusting the proportion of encoder error in the subsequent Simultaneous Localization and Mapping (SLAM) algorithm.

[0107] As described above, this embodiment determines the road surface type of the object to be located within a target time period based on the pre-acquired path planning information of the object to be located. In response to detecting that the road surface type belongs to a set road surface type, the error weight of the encoder is determined based on the preset error weight corresponding to the set road surface type. Since the error weight of the encoder of the object to be located is determined based on the road surface type within the target time period of the object to be located, the determined error weight of the encoder can be adapted to the driving conditions of the object within the target time period of the object to be located, which can improve the accuracy of determining the error weight of the encoder. This can improve the continuity of subsequent positioning of the object to be located, thereby improving the quality of synchronous positioning and mapping.

[0108] Figure 5 This is a flowchart illustrating a method for determining synchronous positioning and mapping parameters according to another exemplary embodiment of the present disclosure; the method of this embodiment can be applied to a control device for an object to be positioned, which may include a robot, a drone, an autonomous vehicle, etc.

[0109] In this embodiment, the driving status information may include displacement and rotational angular velocity, and the synchronous positioning and mapping parameters may include the image acquisition frame rate of the image acquisition device, such as... Figure 5 As shown, the method includes the following steps S501-S502:

[0110] In step S501, based on the path planning information of the object to be located obtained in advance, the displacement and rotational angular velocity of the object to be located within the target time period are determined.

[0111] In this embodiment, the control device for the object to be located can determine the displacement and rotational angular velocity of the object within a target time period based on pre-acquired path planning information of the object. The control device may include a controller or data processor mounted on the object, or it may be a remote control device associated with the object, such as a remote server.

[0112] The target time period mentioned above may include the current time period and / or a set time period following the current time period. It is worth noting that the length of the aforementioned time period can be set based on actual business needs, such as being set to a unit of time length like seconds, minutes, or hours; this embodiment does not limit this. Furthermore, the set time period following the current time period can be a time period of a preset length following the current time period, such as one minute or several minutes after the current minute, or one hour or several hours after the current hour.

[0113] For example, when an object to be located is in an unknown position within an unknown environment requiring positioning, pre-defined path planning information can be obtained. Then, during movement, the object's displacement and rotational angular velocity within a target time period can be determined based on this path planning information. The displacement includes the displacement of the object in each coordinate axis direction of the set coordinate system, and the rotational angular velocity includes the rotational angular velocity in each coordinate axis direction of the set coordinate system.

[0114] In step S502, in response to detecting that the displacement and the rotational angular velocity satisfy the pure rotational motion condition, the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity.

[0115] In this embodiment, after the control device of the object to be located determines the displacement and rotational angular velocity of the object within the target time period based on the path planning information of the object to be located in advance, it can detect whether the displacement and rotational angular velocity meet the pure rotational motion condition. Then, when it is detected that the displacement and rotational angular velocity meet the pure rotational motion condition, the image acquisition frame rate of the image acquisition device can be determined based on the rotational angular velocity.

[0116] The pure rotational motion condition described above includes zero displacement but a non-zero rotational angular velocity. For example, assuming the displacement and rotational acceleration of the object to be positioned along the three axes of the established coordinate system are vectors T and R, respectively, then the pure rotational motion condition could include T = [0,0,0] and R = [r1,r2,r3]. Here, r1, r2, and r3 are not simultaneously zero, i.e., R ≠ [0,0,0].

[0117] It is understandable that when the object to be located is in a state of pure rotational motion, the reduced overlap area between frames leads to a decrease in the accuracy of visual measurement, and may even result in unsuccessful inter-frame matching, making it impossible to calculate the inter-frame pose change. Therefore, in this embodiment, when the object to be located is detected to be in a state of pure rotational motion, the image acquisition frame rate of the image acquisition device can be determined based on the rotational angular velocity. This allows the adjusted image acquisition frame rate f to be increased, thereby increasing the overlap area between frames, improving the accuracy of visual measurement, and thus improving the success rate of inter-frame matching, which is beneficial for subsequent calculation of the inter-frame pose change.

[0118] As described above, this embodiment determines the displacement and rotational angular velocity of the object to be located within a target time period based on the path planning information of the object to be located in advance. In response to the detection that the displacement and rotational angular velocity satisfy the pure rotational motion condition, the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity. Since the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity when the displacement and rotational angular velocity of the object to be located satisfy the pure rotation condition, the determined image acquisition frame rate can be adapted to the driving conditions of the object to be located within the target time period. This improves the rationality of determining the image acquisition frame rate of the image acquisition device. Furthermore, increasing the inter-frame overlap area can improve the success rate of inter-frame matching, which is beneficial for subsequent calculation of inter-frame pose changes. This, in turn, improves the continuity of subsequent positioning of the object to be located and enhances the quality of synchronous positioning and mapping.

[0119] Figure 6 This is a flowchart illustrating how to determine the image acquisition frame rate of an image acquisition device based on the rotational angular velocity, according to an exemplary embodiment of this disclosure. This embodiment, based on the above embodiment, provides an exemplary description of how to determine the image acquisition frame rate of the image acquisition device based on the rotational angular velocity. Figure 6 As shown, the step S502 above, which involves determining the image acquisition frame rate of the image acquisition device based on the rotational angular velocity, may include the following steps S601-S602:

[0120] In step S601, a second adjustable coefficient of the predetermined image acquisition frame rate is obtained.

[0121] In this embodiment, when it is necessary to determine the image acquisition frame rate of the image acquisition device based on the rotational angular velocity, a pre-determined second adjustable coefficient for the image acquisition frame rate can be obtained. This second adjustable coefficient can be a parameter with an adjustable value, allowing the image acquisition frame rate of the image acquisition device to be adjusted based on this second adjustable coefficient when the object to be located is officially put into use, such as during synchronous positioning and mapping based on the object, so that the adjusted image acquisition frame rate better meets actual needs.

[0122] In step S602, the image acquisition frame rate is determined based on the product of the rotational angular velocity and the second adjustable coefficient.

[0123] In this embodiment, after obtaining the predetermined second adjustable coefficient of the image acquisition frame rate, the image acquisition frame rate can be determined based on the product of the rotational angular velocity and the second adjustable coefficient. For example, after determining the rotational angular velocity and the second adjustable coefficient, the product of the rotational angular velocity and the second adjustable coefficient can be calculated, and then the product can be used to determine the image acquisition frame rate of the image acquisition device.

[0124] As described above, this embodiment obtains a predetermined second adjustable coefficient for the image acquisition frame rate and determines the image acquisition frame rate based on the product of the rotational angular velocity and the second adjustable coefficient. This allows the determined image acquisition frame rate to adapt to the driving conditions of the object to be located within the target time period. Furthermore, it enables subsequent adjustments to the image acquisition frame rate of the image acquisition device based on the second adjustable coefficient, thereby improving the accuracy of determining the image acquisition frame rate and enhancing the quality of subsequent synchronous positioning and mapping.

[0125] Figure 7 This is a block diagram illustrating a synchronous positioning and mapping parameter determination device according to an exemplary embodiment; the device of this embodiment can be applied to the control equipment of an object to be positioned, which may include a robot, a drone, an autonomous vehicle, etc.

[0126] like Figure 7 As shown, the device includes: a status information determination module 110 and a synchronous positioning and mapping parameter determination module 120, wherein:

[0127] The status information determination module 110 is used to determine the driving status information of the object to be located within a target time period based on the path planning information of the object to be located in advance. The target time period includes the current time period and / or a set time period after the current time period.

[0128] The synchronous positioning and mapping parameter determination module 120 is used to determine the synchronous positioning and mapping parameters of the object to be located based on the driving condition information in response to detecting that the driving condition information meets the set conditions.

[0129] As described above, this embodiment determines the driving status information of the object to be located within a target time period based on the pre-acquired path planning information of the object to be located. In response to detecting that the driving status information meets set conditions, it determines the synchronous positioning and mapping parameters of the object to be located based on the driving status information. Since the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information within the target time period, the determined synchronous positioning and mapping parameters can be adapted to the driving status of the object within the target time period, improving the accuracy of the determined synchronous positioning and mapping parameters. This enhances the continuity of subsequent positioning of the object to be located, thereby improving the quality of synchronous positioning and mapping.

[0130] Figure 8 This is a block diagram illustrating a synchronous positioning and mapping parameter determination device according to yet another exemplary embodiment. The device in this embodiment can be applied to a control device for an object to be positioned, which may include a robot, a drone, an autonomous vehicle, etc. The status information determination module 210 and the synchronous positioning and mapping parameter determination module 220 are as described above. Figure 8 The status information determination module 110 and the synchronous positioning and mapping parameter determination module 120 in the illustrated embodiment have the same function, and will not be described in detail here.

[0131] The driving status information in this embodiment may include acceleration, and the synchronous positioning and mapping parameters may include the acceleration error weights of the inertial sensor. Based on this, such as... Figure 8 As shown, the synchronous positioning and mapping parameter determination module 220 can also be used to determine the acceleration error weight of the inertial sensor based on the acceleration in response to detecting that the acceleration is less than or equal to a set threshold.

[0132] In one embodiment, the synchronous positioning and mapping parameter determination module 220 may include:

[0133] The first adjustable coefficient acquisition unit 221 is used to acquire the first adjustable coefficient of the predetermined acceleration error weight;

[0134] Acceleration error weight determination unit 222 is used to determine the acceleration error weight based on the product of the acceleration and the first adjustable coefficient.

[0135] In another embodiment, the driving condition information may include the road surface type, and the synchronous positioning and mapping parameters include the error weight of the encoder. Based on this, the synchronous positioning and mapping parameter determination module 220 can also be used to determine the error weight of the encoder based on the preset error weight corresponding to the set road surface type in response to detecting that the road surface type belongs to a set road surface type.

[0136] In one embodiment, the aforementioned road surface type may include a road surface that is prone to slippage;

[0137] The above-mentioned device may further include:

[0138] The road surface type determination module 240 is used to determine the road surface type as defined by the image acquisition device based on the detection of a defined object on the road surface. The defined object includes at least one of the following: mud, puddle, and oil stain.

[0139] In another embodiment, the driving status information may include displacement and rotational angular velocity, and the synchronous positioning and mapping parameters include the image acquisition frame rate of the image acquisition device.

[0140] Based on this, the synchronous positioning and mapping parameter determination module 220 can also be used to determine the image acquisition frame rate of the image acquisition device based on the rotation angular velocity in response to detecting that the displacement and the rotation angular velocity meet the pure rotation motion condition.

[0141] In one embodiment, the synchronous positioning and mapping parameter determination module 220 may include:

[0142] The second adjustable coefficient acquisition unit 223 is used to acquire a second adjustable coefficient of the predetermined image acquisition frame rate;

[0143] The image acquisition frame rate determination unit 224 is used to determine the image acquisition frame rate based on the product of the rotational angular velocity and the second adjustable coefficient.

[0144] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0145] Figure 9 This is a block diagram illustrating an electronic device according to an exemplary embodiment. For example, device 900 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc.

[0146] Reference Figure 9The device 900 may include one or more of the following components: a processing component 902, a memory 904, a power supply component 906, a multimedia component 908, an audio component 910, an input / output (I / O) interface 912, a sensor component 914, and a communication component 916.

[0147] Processing component 902 typically controls the overall operation of device 900, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 902 may include one or more processors 920 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 902 may include one or more modules to facilitate interaction between processing component 902 and other components. For example, processing component 902 may include a multimedia module to facilitate interaction between multimedia component 908 and processing component 902.

[0148] Memory 904 is configured to store various types of data to support the operation of device 900. Examples of this data include instructions for any application or method operating on device 900, contact data, phonebook data, messages, pictures, videos, etc. Memory 904 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0149] Power supply component 906 provides power to various components of device 900. Power supply component 906 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 900.

[0150] Multimedia component 908 includes a screen that provides an output interface between the device 900 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 908 includes a front-facing camera and / or a rear-facing camera. When the device 900 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0151] Audio component 910 is configured to output and / or input audio signals. For example, audio component 910 includes a microphone (MIC) configured to receive external audio signals when device 900 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 904 or transmitted via communication component 916. In some embodiments, audio component 910 also includes a speaker for outputting audio signals.

[0152] I / O interface 912 provides an interface between processing component 902 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0153] Sensor assembly 914 includes one or more sensors for providing status assessments of various aspects of device 900. For example, sensor assembly 914 may detect the on / off state of device 900, the relative positioning of components such as the display and keypad of device 900, changes in the position of device 900 or a component of device 900, the presence or absence of user contact with device 900, the orientation or acceleration / deceleration of device 900, and temperature changes of device 900. Sensor assembly 914 may also include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 914 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 914 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0154] Communication component 916 is configured to facilitate wired or wireless communication between device 900 and other devices. Device 900 can access wireless networks based on communication standards, such as WiFi, 2G or 3G, 4G or 5G, or combinations thereof. In one exemplary embodiment, communication component 916 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 916 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0155] In an exemplary embodiment, device 900 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0156] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 904 including instructions, which can be executed by a processor 920 of device 900 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0157] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0158] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for determining synchronous positioning and mapping parameters, characterized in that, The method includes: Based on the acquired pre-customized path planning information of the object to be located, the driving status information of the object to be located within a target time period is determined. The target time period includes a set time period after the current time period. The driving status information includes at least one of acceleration, road surface type, displacement, and rotational angular velocity. In response to detecting that the driving status information meets the set conditions, the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information, including: In response to detecting that the acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor is determined based on the acceleration; In response to detecting that the driving road surface type belongs to a set road surface type, the error weight of the encoder is determined based on the preset error weight corresponding to the set road surface type; In response to the detection that the displacement and the rotational angular velocity satisfy the pure rotational motion condition, the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity.

2. The method according to claim 1, characterized in that, The determination of the acceleration error weight of the inertial sensor based on the acceleration includes: Obtain the first adjustable coefficient of the predetermined acceleration error weight; The acceleration error weight is determined based on the product of the acceleration and the first adjustable coefficient.

3. The method according to claim 1, characterized in that, The specified road surface type includes road surfaces that are prone to slipping. The method further includes: In response to the detection of a designated object on the driving road surface by the image acquisition device, it is determined that the driving road surface type belongs to the designated road surface type, and the designated object includes at least one of the following: mud, puddle, oil stain.

4. The method according to claim 1, characterized in that, The process of determining the image acquisition frame rate of the image acquisition device based on the rotational angular velocity includes: Obtain a second adjustable coefficient for the predetermined image acquisition frame rate; The image acquisition frame rate is determined based on the product of the rotational angular velocity and the second adjustable coefficient.

5. A device for determining synchronous positioning and mapping parameters, characterized in that, The device includes: The status information determination module is used to determine the driving status information of the object to be located within a target time period based on the acquired pre-customized path planning information of the object to be located. The target time period includes a set time period after the current time period. The driving status information includes at least one of acceleration, road surface type, displacement and rotational angular velocity. The synchronous positioning and mapping parameter determination module is used to determine the synchronous positioning and mapping parameters of the object to be positioned based on the driving condition information in response to detecting that the driving condition information meets the set conditions, including: In response to detecting that the acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor is determined based on the acceleration; In response to detecting that the driving road surface type belongs to a set road surface type, the error weight of the encoder is determined based on the preset error weight corresponding to the set road surface type; In response to the detection that the displacement and the rotational angular velocity satisfy the pure rotational motion condition, the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity.

6. An electronic device, characterized in that, The device includes: Processor and memory used to store computer programs; The processor is configured to, when executing the computer program, implement: Based on the acquired pre-customized path planning information of the object to be located, the driving status information of the object to be located within a target time period is determined. The target time period includes a set time period after the current time period. The driving status information includes at least one of acceleration, road surface type, displacement, and rotational angular velocity. In response to detecting that the driving status information meets the set conditions, the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information, including: In response to detecting that the acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor is determined based on the acceleration; In response to detecting that the driving road surface type belongs to a set road surface type, the error weight of the encoder is determined based on the preset error weight corresponding to the set road surface type; In response to the detection that the displacement and the rotational angular velocity satisfy the pure rotational motion condition, the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the following is achieved: Based on the acquired pre-customized path planning information of the object to be located, the driving status information of the object to be located within a target time period is determined. The target time period includes a set time period after the current time period. The driving status information includes at least one of acceleration, road surface type, displacement, and rotational angular velocity. In response to detecting that the driving status information meets the set conditions, the synchronous positioning and mapping parameters of the object to be located are determined based on the driving status information, including: In response to detecting that the acceleration is less than or equal to a set threshold, the acceleration error weight of the inertial sensor is determined based on the acceleration; In response to detecting that the driving road surface type belongs to a set road surface type, the error weight of the encoder is determined based on the preset error weight corresponding to the set road surface type; In response to the detection that the displacement and the rotational angular velocity satisfy the pure rotational motion condition, the image acquisition frame rate of the image acquisition device is determined based on the rotational angular velocity.

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