High-precision positioning method and system for coal transporting shuttle car

Abstract

The invention discloses a high-precision positioning method and system for a coal transporting shuttle car, and relates to the technical field of vehicle positioning, and the method comprises the following steps: constructing environment structure reference information based on tunnel structure data collected by a laser scanning device installed on the shuttle car; the reliability of ranging signals collected by an ultra wide band ranging device installed on the shuttle car is evaluated in real time, and a shuttle car positioning strategy is selected between a first positioning mode and a second positioning mode; when the first positioning mode is selected, calculating motion parameters collected by an inertial measurement device mounted on the shuttle car to obtain a current pose of the shuttle car, correcting the current pose based on the distance measurement signal, and outputting a positioning result; and when the second positioning mode is selected, acquiring a current pose, querying the environment structure reference information to obtain a reference feature corresponding to the current pose, adjusting the current pose based on the reference feature, and outputting a positioning result. According to the method, the positioning precision and the operation safety of the coal transporting shuttle car under the complex working conditions can be guaranteed.

Description

Technical Field

[0001] This application relates to the field of vehicle positioning technology, and in particular to a high-precision positioning method and system for coal shuttle cars. Background Technology

[0002] In unmanned transportation systems in underground coal mines, coal shuttle cars rely on inertial measurement units (IMUs) and ultra-wideband (UWB) positioning systems to achieve high-precision autonomous operation. The IMU provides continuous trajectory calculations, while the UWB system periodically corrects the accumulated errors of the IMU by measuring the distance between the vehicle and fixed anchor points in the tunnel, thus jointly ensuring positioning accuracy.

[0003] However, the harsh and dynamically changing underground environment severely restricts the reliability of UWB systems. First, coal dust and a humid environment cause signal attenuation and changes in the propagation path, introducing systematic ranging errors. Second, strong electromagnetic interference generated by the operation of large equipment can cause UWB receivers to misinterpret signals, leading to large instantaneous ranging deviations or data loss. More complexly, when multiple shuttle cars operate in tandem, their UWB signals collide in narrow tunnels, making effective analysis difficult and further reducing the quality and quantity of usable ranging data.

[0004] The combined effects of environmental degradation, electromagnetic interference, and multi-vehicle signal conflicts cause a sharp decline in the quality and extreme instability of UWB ranging data. When the control system continuously uses this unreliable UWB data to correct the IMU, it not only fails to suppress the IMU's inherent drift but also introduces erroneous corrections, leading to serious deviations or even divergence in vehicle positioning estimation. This directly threatens the safe autonomous operation of the shuttle, easily causing path deviations, tunnel wall collisions, and multi-vehicle interaction risks, severely restricting the efficiency and reliability of the transportation system. Summary of the Invention

[0005] This application proposes a high-precision positioning method and system for coal shuttle cars, aiming to solve the technical problem that the ultra-wideband ranging system of coal shuttle cars is unstable due to factors such as the degradation of the underground environment, electromagnetic interference, and signal conflicts between multiple vehicles, which leads to a decrease in positioning accuracy and affects the safety and efficiency of autonomous vehicle operation.

[0006] Firstly, this application provides a high-precision positioning method for a coal transport shuttle car, comprising the following steps:

[0007] Based on the tunnel structure data collected by the laser scanning device installed on the shuttle car, environmental structure reference information is constructed.

[0008] The reliability of the ranging signal collected by the ultra-wideband ranging device installed on the shuttle car is evaluated in real time, and the evaluation results are obtained.

[0009] Based on the evaluation results, the positioning strategy of the shuttle is selected between the first positioning mode and the second positioning mode;

[0010] When the first positioning mode is selected, the current pose of the shuttle car is calculated from the motion parameters collected by the inertial measurement device installed on the shuttle car. Based on the ranging signal, the current pose is corrected and the positioning result is output.

[0011] When the second positioning mode is selected, the current pose is obtained, the environmental structure reference information is queried to obtain the reference features corresponding to the current pose, the current pose is adjusted based on the reference features, and the positioning result is output.

[0012] In some embodiments of this application, the step of constructing environmental structure reference information based on tunnel structure data collected by a laser scanning device mounted on a shuttle car includes:

[0013] Based on the tunnel structure data collected by the laser scanning device installed on the shuttle car, multiple reference features distributed in different structural parts of the tunnel area are identified and extracted.

[0014] Based on the aforementioned reference features, environmental structure reference information is constructed.

[0015] In some embodiments of this application, the step of identifying and extracting multiple reference features distributed in different structural parts of the roadway area based on roadway structure data collected by a laser scanning device mounted on a shuttle car includes:

[0016] Based on the laser scanning device installed on the shuttle car, the same tunnel area is scanned multiple times to obtain tunnel structure data;

[0017] Based on the tunnel structure data, multiple geometric features distributed in different structural parts of the tunnel area are identified and extracted;

[0018] Calculate the positional deviation of the geometric feature during multiple scans;

[0019] Geometric features whose positional deviation is less than a preset stability threshold are determined to be stable features.

[0020] In some embodiments of this application, the step of evaluating the reliability of the ranging signal collected by the ultra-wideband ranging device installed on the shuttle car in real time and obtaining the evaluation result includes:

[0021] Based on the motion prediction of the shuttle car by the inertial measurement device installed on the shuttle car, the predicted position range of the shuttle car after a preset short time is obtained;

[0022] Based on the known coordinates of the positioning anchor point and the predicted location range, the expected ranging range of the positioning anchor point is calculated. The positioning anchor point is pre-deployed in the roadway and used to communicate with the ultra-wideband ranging device installed on the shuttle car.

[0023] Based on the ranging signal collected by the ultra-wideband ranging device over the preset short time, a real-time ranging value is obtained.

[0024] The reliability assessment result of the ranging signal is obtained by comparing the real-time ranging value with the expected ranging range.

[0025] In some embodiments of this application, the step of comparing the real-time ranging value with the expected ranging range to obtain an evaluation result of the reliability of the ranging signal includes:

[0026] If the real-time ranging value is within the expected ranging range, then the reliability assessment result of the ranging signal is determined to be reliable.

[0027] If the real-time ranging value exceeds the expected ranging range, the reliability assessment result of the ranging signal is determined to be unreliable.

[0028] In some embodiments of this application, the step of selecting the shuttle's positioning strategy between a first positioning mode and a second positioning mode based on the evaluation result includes:

[0029] Obtain evaluation results of multiple ranging signals corresponding to multiple positioning anchor points;

[0030] If the proportion of reliable ranging signals is greater than or equal to a preset determination proportion, the positioning strategy of the shuttle car is the first positioning mode, and the operating frequency of the ultra-wideband ranging device is adjusted to the preset first frequency.

[0031] If the proportion of ranging signals deemed reliable is less than the determined proportion, the positioning strategy of the shuttle car is the second positioning mode, and the operating frequency of the ultra-wideband ranging device is adjusted to a preset second frequency, which is lower than the first frequency.

[0032] In some embodiments of this application, the step of calculating the current pose of the shuttle car from the motion parameters collected by the inertial measurement device installed on the shuttle car when the first positioning mode is selected, correcting the current pose based on the ranging signal, and outputting the positioning result includes:

[0033] The current pose of the shuttle car is calculated from the motion parameters collected by the inertial measurement unit installed on the shuttle car;

[0034] Based on the ranging signal, a pose correction amount is obtained to correct the current pose.

[0035] The current pose is corrected based on the pose correction amount, and the positioning result is output.

[0036] In some embodiments of this application, the step of obtaining the pose correction amount for correcting the current pose based on the ranging signal includes:

[0037] Based on the evaluation results, multiple fusion weights are assigned to the ranging signals corresponding to multiple positioning anchor points;

[0038] Based on the fusion weights and the pre-stored coordinates of multiple positioning anchors, the multiple ranging signals are weighted and the positioning solution is calculated to obtain the estimated pose of the shuttle car.

[0039] The pose deviation between the current pose and the estimated pose is calculated to obtain the pose correction amount.

[0040] In some embodiments of this application, the steps of obtaining the current pose, querying the environmental structure reference information to obtain reference features corresponding to the current pose, adjusting the current pose based on the reference features, and outputting the positioning result when the second positioning mode is selected include:

[0041] Obtain the current pose and determine the spatial query range based on the current pose;

[0042] From the environmental structure reference information, select reference features that are within the spatial query range;

[0043] Calculate the geometric deviation between the current pose and the reference feature;

[0044] If the geometric deviation exceeds a preset deviation range, a geometric correction amount proportional to the geometric deviation is calculated. The geometric correction amount is equal to the product of the geometric deviation and a preset correction ratio, where the correction ratio is less than 1.

[0045] Based on the geometric correction, the current pose is adjusted, and the positioning result is output.

[0046] Secondly, this application also provides a high-precision positioning system for a coal transport shuttle car, comprising:

[0047] The environmental information construction module is used to construct environmental structure reference information based on the tunnel structure data collected by the laser scanning device installed on the shuttle car;

[0048] The ranging signal evaluation module is used to evaluate the reliability of the ranging signal collected by the ultra-wideband ranging device installed on the shuttle in real time and obtain the evaluation result.

[0049] The positioning strategy adjustment module is used to select the positioning strategy of the shuttle car between the first positioning mode and the second positioning mode based on the evaluation results.

[0050] The internal sensing and positioning module is used to calculate the current pose of the shuttle car from the motion parameters collected by the inertial measurement device installed on the shuttle car when the first positioning mode is selected, correct the current pose based on the ranging signal, and output the positioning result.

[0051] An external auxiliary positioning module is used to obtain the current pose, query the environmental structure reference information to obtain reference features corresponding to the current pose, adjust the current pose based on the reference features, and output the positioning result when the second positioning mode is selected.

[0052] The technical solution according to the embodiments of this application has at least the following beneficial effects: Through this dynamic switching mechanism, the positioning method of this application can effectively cope with problems such as underground environment degradation, electromagnetic interference, and multi-vehicle signal conflicts. When the quality of the ultra-wideband ranging signal is good, its high precision is used for correction; when the signal quality is poor, it switches to a positioning method based on reference feature matching, thereby ensuring the positioning accuracy and operational safety of the coal shuttle car under complex working conditions, reducing the transportation risk of the shuttle car, and ensuring the transportation efficiency of the shuttle car.

[0053] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0054] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0055] Figure 1 This is a flowchart illustrating a high-precision positioning method for a coal shuttle car provided in an embodiment of this application.

[0056] Figure 2 This is a schematic diagram of the architecture of a high-precision positioning system for a coal shuttle car provided in an embodiment of this application. Detailed Implementation

[0057] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0058] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0059] In the demanding environment of underground coal mines, ensuring the accurate positioning of unmanned coal shuttles is crucial for guaranteeing transportation safety and efficiency. Traditional positioning methods, under the combined effects of environmental degradation, electromagnetic interference, and signal conflicts between multiple vehicles, render ultra-wideband ranging systems extremely unstable. This causes the drift of the inertial measurement unit (IMU) to not only fail to be suppressed but is also erroneously guided, leading to its position and attitude estimates deviating from the true trajectory at a faster rate and with greater magnitude. Ultimately, this results in the shuttle's inability to accurately perceive its precise position within the tunnel, nor to accurately identify tunnel boundaries and dynamic obstacles, severely threatening its autonomous operation capabilities.

[0060] In this regard, such as Figure 1 As shown, this application discloses a high-precision positioning method for a coal shuttle car, including the following steps:

[0061] S110, based on the tunnel structure data collected by the laser scanning device installed on the shuttle car, constructs environmental structure reference information;

[0062] S120, evaluates in real time the reliability of the ranging signal collected by the ultra-wideband ranging device installed on the shuttle car, and obtains the evaluation results;

[0063] S130, Based on the evaluation results, select the shuttle's positioning strategy between the first positioning mode and the second positioning mode;

[0064] S140, when the first positioning mode is selected, the current pose of the shuttle car is calculated from the motion parameters collected by the inertial measurement device installed on the shuttle car, the current pose is corrected based on the ranging signal, and the positioning result is output.

[0065] S150, when the second positioning mode is selected, the current pose is obtained, the environmental structure reference information is queried to obtain the reference features corresponding to the current pose, the current pose is adjusted based on the reference features, and the positioning result is output.

[0066] This application effectively addresses the challenges posed by the complex underground environment by constructing environmental structure reference information, evaluating the reliability of ranging signals in real time, and dynamically selecting positioning strategies, thereby significantly improving the positioning accuracy and reliability of coal shuttle cars under various working conditions.

[0067] To better understand the technical solution proposed in this application, some key terms involved will be explained first.

[0068] "Shuttle car" refers to an unmanned vehicle used for transporting coal in underground coal mines. Its precise positioning is the foundation for ensuring transportation safety and efficiency.

[0069] A laser scanning device is a device that can emit laser beams and receive reflected signals. By scanning the tunnel environment, it can obtain geometric data of the tunnel.

[0070] "Tunnel structure data" refers to the data set of tunnel geometry, dimensions, and internal feature points collected by a laser scanning device.

[0071] "Environmental structure reference information" is a database or model built based on tunnel structure data to describe the fixed structural features inside the tunnel, which can be compared and referenced by the shuttle car during positioning.

[0072] "Ultra-wideband ranging device" is a device that uses ultra-wideband technology to measure distances with high precision. It usually consists of ultra-wideband tags installed on a shuttle car and ultra-wideband positioning anchors deployed in the tunnel. The distance is calculated by measuring the flight time of the signal.

[0073] "Range signal" refers to the radio signal transmitted and received by an ultra-wideband ranging device when performing distance measurement.

[0074] "Inertial measurement device" usually refers to inertial measurement unit (IMU), which integrates accelerometer and gyroscope to measure the linear acceleration and angular velocity of the shuttle, thereby calculating the motion parameters and attitude of the shuttle.

[0075] "Motion parameters" include the linear acceleration and angular velocity of the shuttle, which are the raw output data of the inertial measurement unit.

[0076] "Current pose" refers to the spatial position (e.g., three-dimensional coordinates) and attitude (e.g., pitch angle, roll angle, yaw angle) of the shuttle at a certain moment.

[0077] The "first positioning mode" and the "second positioning mode" are two different positioning strategies dynamically selected by this application based on the reliability of the ranging signal, and are respectively applicable to scenarios where the ranging signal is reliable and scenarios where it is unreliable.

[0078] "Reference features" refer to geometric or structural features extracted from environmental structural reference information that correspond to the current pose of the shuttle and can be used for positioning.

[0079] The core of the high-precision positioning method for coal shuttle cars proposed in this application lies in adapting to the complex underground environment through multi-source information fusion and dynamic strategy selection.

[0080] The steps for "Constructing Environmental Structure Reference Information" aim to provide a stable external reference benchmark for the shuttle. Specifically, this can be achieved by installing a laser scanning device, such as a 2D or 3D lidar, on the shuttle. As the shuttle travels through the tunnel, the laser scanning device continuously emits laser beams and receives reflected signals, thereby acquiring geometric data of the tunnel walls, roof, floor, and other fixed structures (such as supports, cable trays, etc.). This raw laser point cloud data, after preprocessing (such as denoising and filtering), can be used to construct local or global maps of the tunnel. For example, this point cloud data can be fitted into a series of planes, straight lines, or curves, or corner points, edge lines, etc., with significant geometric features can be extracted. These geometric features and their positional information in the tunnel coordinate system constitute the environmental structure reference information. Another approach is to use the laser scanning device to scan the tunnel multiple times, and then fuse the data from these multiple scans using point cloud registration technology to obtain a more complete and accurate 3D model of the tunnel. In this 3D model, some long-term stable structural features can be identified and extracted, such as the outline of the tunnel and the fixed position of specific equipment. These features and their coordinate information can then be stored as environmental structural reference information.

[0081] Regarding the step of "obtaining the evaluation results," this step is crucial for the dynamic positioning strategy selection in this application. One approach is to evaluate the reliability of the ranging signal by analyzing physical parameters such as its strength and signal-to-noise ratio (SNR). For example, if the strength of the ranging signal is below a preset threshold or the SNR is too low, the ranging signal can be deemed unreliable. This is because signal strength and SNR are important indicators of signal quality, and they are affected by factors such as coal dust, water vapor, and electromagnetic interference. Another approach is to evaluate reliability by comparing the volatility of continuous ranging results. For example, if the ranging value obtained from the same ultra-wideband positioning anchor point fluctuates drastically within a short period, exceeding a preset reasonable range, the ranging signal can be considered unreliable. This is because under normal circumstances, the shuttle's movement is continuous and smooth within a short period, and the ranging value should also exhibit a smooth trend.

[0082] Regarding the steps for "selecting the shuttle's positioning strategy," this step is the core of this application's dynamic adjustment of the positioning scheme based on environmental changes. One implementation method is to set a reliability threshold. When the reliability assessment result of the ranging signal reaches or exceeds this threshold, the first positioning mode is selected; otherwise, the second positioning mode is selected. For example, the proportion of reliable ranging signals among all ultra-wideband positioning anchor points within a certain time window can be statistically analyzed. If this proportion is higher than a preset value, the overall working condition of the ultra-wideband ranging system is considered good, and the first positioning mode is selected. Conversely, if the proportion of reliable signals is low, the ultra-wideband ranging system is considered to be severely interfered with, and the second positioning mode is selected.

[0083] In the first positioning mode, the ultra-wideband ranging signal is considered reliable and can therefore be used to correct the drift of the inertial measurement unit (IMU). Specifically, the IMU continuously collects motion parameters such as the shuttle's acceleration and angular velocity. By integrating these parameters and calculating the attitude, the shuttle's current pose can be calculated in real time. However, the IMU has inherent drift errors, and its calculated pose accumulates errors over time. This is where the reliable ultra-wideband ranging signal comes in. For example, data fusion algorithms such as Kalman filtering or extended Kalman filtering can be used to combine the pose calculated by the IMU as a predicted value with the position information calculated from the ultra-wideband ranging signal as an observed value. The fusion algorithm then corrects the IMU's pose in real time, resulting in a more accurate positioning result.

[0084] In the second positioning mode, due to the unreliability of ultra-wideband ranging signals, the positioning system will instead rely on environmental structural reference information for positioning. Specifically, the current pose calculated by the inertial measurement unit (IMU) is first acquired. Although the IMU may experience some drift at this point, its relative accuracy remains high over a short period. Then, using this current pose, the system searches through the pre-built environmental structural reference information to find the reference feature that is spatially closest to or best matches the current pose. For example, if the current pose indicates that the shuttle is located near a bend in a tunnel, the system will search the environmental structural reference information for the geometric features of that bend area (such as the curve, specific corner points, etc.) as reference features. Based on this reference feature, the current pose calculated by the IMU is adjusted, and the final positioning result is output.

[0085] The high-precision positioning method for coal shuttle cars proposed in this application works by constructing an adaptive positioning framework that can dynamically adjust the positioning strategy according to real-time changes in the underground environment, thereby maintaining high-precision positioning under complex working conditions.

[0086] Specifically, during the initial operation of the shuttle or when the environment is stable, the laser scanning device continuously collects tunnel structure data and constructs detailed environmental structure reference information accordingly. During shuttle operation, the ultra-wideband ranging device continuously collects ranging signals. Simultaneously, the system evaluates the reliability of these ranging signals in real time. Based on the evaluation results of the ranging signals, the positioning strategy adjustment module intelligently switches between the first and second positioning modes.

[0087] In the first positioning mode, the inertial measurement unit (IMU) continuously calculates the shuttle's current pose, while a reliable ultra-wideband ranging signal is used to correct the IMU's accumulated errors. This mode fully utilizes the advantages of the ultra-wideband ranging system in favorable environments, effectively suppressing IMU drift.

[0088] In the second positioning mode, since ultra-wideband ranging data may contain significant errors or even be completely unusable, the system switches to relying on pre-built environmental structural reference information for positioning. The current pose calculated by the inertial measurement unit (IMU) serves as an initial estimate, and the system queries the corresponding reference features in the environmental structural reference information based on this pose. This mode utilizes the structural stability of the tunnel environment, enabling positioning through environmental feature matching even in the event of IMU failure. This avoids positioning divergence caused by erroneous ranging data and effectively mitigates the negative impact of unreliable ranging data on the positioning system. The IMU's pose is corrected through reference feature matching. This essentially provides a "backup plan" or "degradation mode" for the positioning system, ensuring that the system maintains a certain level of positioning capability even when the primary positioning sensor (ultra-wideband) fails, thus avoiding the risk of complete positioning failure.

[0089] Through this dynamic switching mechanism, the positioning method of this application can effectively address issues such as underground environmental degradation, electromagnetic interference, and signal conflicts between multiple vehicles. When the quality of the ultra-wideband ranging signal is good, its high precision is used for correction; when the signal quality is poor, it switches to a positioning method based on reference feature matching, thereby ensuring the positioning accuracy and operational safety of the coal shuttle car under complex working conditions, reducing the transportation risk of the shuttle car, and ensuring the transportation efficiency of the shuttle car.

[0090] In some embodiments of this application, the step of constructing environmental structure reference information based on tunnel structure data collected by a laser scanning device mounted on a shuttle car preferably includes:

[0091] Based on the tunnel structure data collected by the laser scanning device installed on the shuttle car, multiple reference features distributed in different structural parts of the tunnel area are identified and extracted.

[0092] Based on the aforementioned reference features, environmental structure reference information is constructed.

[0093] The identification and extraction of multiple reference features distributed across different structural parts of the tunnel area involves using pre-stored algorithms and processing methods to filter out stable and recognizable geometric or textural features from the raw tunnel structure data acquired by the laser scanning device. These features can include tunnel wall corners, support structures, equipment outlines, etc., which are relatively fixed in the tunnel environment and easily repeatedly detected by the laser scanning device. Reference features can be understood as entities with unique geometric shapes or spatial locations in the tunnel environment, such as specific protrusions or depressions in the tunnel wall, edges of support frames, or prominent parts of other fixed facilities. The purpose of selecting these features is to provide stable and reliable reference points for the shuttle's positioning.

[0094] Constructing environmental structural reference information refers to organizing and storing the identified and extracted stable reference features and their corresponding spatial location information to form a database or map that can be used for subsequent positioning queries. For example, these reference features can be represented as 3D point clouds, line segments, planes, or more complex geometric models, and associated with their position information in a global coordinate system. The purpose is to provide accurate structured environmental information for the shuttle to perform external assisted positioning in the second positioning mode.

[0095] The proposed solution first identifies and extracts multiple reference features distributed across different structural locations within the tunnel area based on tunnel structure data acquired by a laser scanning device mounted on a shuttle car. This avoids directly using raw tunnel structure data, which may contain noise or unstable information, to construct environmental structure reference information. It is precisely this preprocessing and feature filtering of the raw data that makes the constructed environmental structure reference information more refined and representative. Subsequently, environmental structure reference information is constructed based on these filtered stable reference features, ensuring that the constructed reference information accurately reflects the actual structure of the tunnel and provides a reliable reference during shuttle car positioning, effectively improving the quality and usability of the environmental structure reference information.

[0096] In a preferred embodiment of this application, the step of identifying and extracting multiple reference features distributed in different structural parts of the roadway area based on the roadway structure data collected by the laser scanning device installed on the shuttle car includes:

[0097] Based on the laser scanning device installed on the shuttle car, the same tunnel area is scanned multiple times to obtain tunnel structure data;

[0098] Based on the tunnel structure data, multiple geometric features distributed in different structural parts of the tunnel area are identified and extracted;

[0099] Calculate the positional deviation of the geometric feature during multiple scans;

[0100] Geometric features whose positional deviation is less than a preset stability threshold are determined to be stable features.

[0101] Multiple scans of the same roadway area refer to the repeated data collection of that area at different times or angles using a laser scanning device as the coal shuttle car passes through or stops in that specific roadway area. The purpose is to obtain more comprehensive and redundant structural data for subsequent stability analysis of the features.

[0102] Identifying and extracting multiple geometric features distributed across different structural parts of the tunnel area can be understood as using algorithms such as point cloud segmentation, edge detection, and plane fitting from raw point cloud data or raster images obtained through multiple scans to identify structural elements with specific geometric shapes and spatial locations, such as walls, supports, pipes, and cables. These geometric features are the basic components constituting the tunnel environment.

[0103] Calculating the positional deviation of the geometric feature across multiple scans refers to aligning and comparing the positions of the same geometric feature identified in different scans using feature matching algorithms (such as Iterative Closest Point (ICP) and Normal Distribution Transform (NDT) algorithms), thereby quantifying the degree of change in its spatial position. Positional deviation can be expressed as the Euclidean distance between the feature's center point coordinates, the average distance of the feature boundary, etc.

[0104] Determining a geometric feature whose positional deviation is less than a preset stability threshold as a stable feature means setting an allowable range of positional variation. Only when the positional change of a geometric feature in multiple scans is less than this range is the feature considered reliable and stable. The preset stability threshold is an empirical value that can be set according to the characteristics of the tunnel environment, the accuracy of the laser scanning device, and the requirements of the positioning system. Its purpose is to screen out structural features whose positions remain unchanged or change very little under long-term or multiple observations, so as to serve as a reliable basis for constructing environmental structural reference information.

[0105] The proposed solution acquires richer and more redundant tunnel structure data by scanning the same tunnel area multiple times. Based on this, by identifying and extracting geometric features distributed across different structural parts of the tunnel area, and further calculating the positional deviations of these geometric features across multiple scans, the stability of each geometric feature can be effectively evaluated. It is precisely because of the introduction of positional deviation calculation and the determination of a preset stability threshold that the system can classify geometric features with small positional changes across multiple observations as stable features. These stable features, due to their inherent spatial invariance, can effectively resist temporary interference or measurement noise in the tunnel environment, thus providing a more reliable and accurate foundation for subsequently constructing environmental structural reference information. This mechanism of stability evaluation based on multi-frame data significantly improves the quality of the selected reference features.

[0106] The following is a specific example to illustrate this.

[0107] Suppose that when a coal transport shuttle enters a specific roadway area, its onboard laser scanning device performs three consecutive scans of that area. The first scan acquires geometric feature data of a protrusion on the left wall of the roadway, a support, and a depression in the ground. The second and third scans also acquire data for these features. The system then matches and calculates the positions of the protrusion, support, and depression in the three scans to obtain their respective positional deviations. For example, if the positional deviation of the protrusion in all three scans is less than a preset stability threshold (e.g., 5 cm), it is determined to be a stable feature. A support, however, might have a positional deviation greater than the threshold due to slight shaking, and therefore is not determined to be a stable feature. A depression might have unclear features or a large positional deviation due to coal dust accumulation on the ground, and similarly, it is not determined to be a stable feature. Ultimately, only protrusions determined to be stable features are used to construct environmental structural reference information, thus ensuring the reliability of the reference information.

[0108] In some embodiments of this application described above, the step of evaluating the reliability of the ranging signal acquired by the ultra-wideband ranging device installed on the shuttle car in real time and obtaining the evaluation result includes:

[0109] Based on the motion prediction of the shuttle car by the inertial measurement device installed on the shuttle car, the predicted position range of the shuttle car after a preset short time is obtained;

[0110] Based on the known coordinates of the positioning anchor point and the predicted location range, the expected ranging range of the positioning anchor point is calculated. The positioning anchor point is pre-deployed in the roadway and used to communicate with the ultra-wideband ranging device installed on the shuttle car.

[0111] Based on the ranging signal collected by the ultra-wideband ranging device over the preset short time, a real-time ranging value is obtained.

[0112] The reliability assessment result of the ranging signal is obtained by comparing the real-time ranging value with the expected ranging range.

[0113] An inertial measurement unit (IMU) can be understood as a device capable of measuring an object's three-axis attitude angles (or angular rates) and acceleration, such as an inertial measurement unit (IMU). Motion parameters collected by the IMU, such as acceleration and angular velocity, can be used to predict the motion state of a shuttle. After a preset short time, by integrating or Kalman filtering these motion parameters, the predicted position of the shuttle at a future moment can be calculated. Considering the error accumulation characteristics of the IMU, this predicted position is usually presented as a range, representing the spatial region where the shuttle may exist after that short time, thus providing a priori constraint for the subsequent reliability assessment of the ranging signal.

[0114] Positioning anchors are reference points with known, precise coordinates that are pre-deployed within the tunnel. These anchors can wirelessly communicate with an ultra-wideband ranging device mounted on the shuttle car to provide distance measurements. Based on the known coordinates of these anchors and the predicted position range of the shuttle car after a preset short time, the expected ranging range between the shuttle car and each anchor point can be calculated. This expected ranging range takes into account the uncertainty of the shuttle car's predicted position; that is, if the shuttle car is actually located at any point within the predicted position range, the distance between it and the anchor point should fall within this expected ranging range.

[0115] After a preset short period of time, the ultra-wideband ranging device will collect real-time ranging signals between itself and each positioning anchor point, and calculate the real-time ranging value from these signals. This real-time ranging value is the actual measured distance between the shuttle and the corresponding positioning anchor point at the current moment.

[0116] The real-time ranging value is compared with the expected ranging range calculated for each positioning anchor point. This comparison determines whether the real-time ranging value falls within the expected distance range. If the real-time ranging value is within the expected ranging range, the ranging signal is considered reliable; conversely, if the real-time ranging value exceeds the expected ranging range, the ranging signal is considered to be affected by interference, obstruction, or multipath effects, and is therefore deemed unreliable. Thus, the reliability assessment result of the ranging signal is obtained.

[0117] Through the above technical solution, this application enables real-time, dynamic evaluation of the reliability of ultra-wideband ranging signals. This evaluation mechanism effectively utilizes the motion prediction capability of inertial measurement devices, providing a priori constraints based on physical motion laws for the validity of ranging signals. This significantly improves the accuracy of ranging signal selection, reduces positioning errors introduced by abnormal ranging data, and thus enhances the robustness and accuracy of the overall positioning system for the coal shuttle car. This solution avoids positioning drift or jumps that may result from blindly using all ranging data during the positioning process, ensuring the stability and accuracy of the positioning results.

[0118] In a specific embodiment of this application, the step of comparing the real-time ranging value with the expected ranging range to obtain an evaluation result of the reliability of the ranging signal preferably includes:

[0119] If the real-time ranging value is within the expected ranging range, then the reliability assessment result of the ranging signal is determined to be reliable.

[0120] If the real-time ranging value exceeds the expected ranging range, the reliability assessment result of the ranging signal is determined to be unreliable.

[0121] The real-time ranging value refers to the ranging data collected by the ultra-wideband ranging device during actual operation, while the expected ranging range is a reasonable distance interval pre-calculated based on the shuttle's motion prediction and the known coordinates of the positioning anchor point. Comparing the real-time ranging value with the expected ranging range aims to determine whether the real-time ranging data is within a reasonable physical range. If the real-time ranging value falls within the expected ranging range, it indicates that the ranging signal matches the shuttle's motion prediction result and has high reliability, thus being judged as reliable. Conversely, if the real-time ranging value exceeds the expected ranging range, it means that the ranging signal deviates significantly from the shuttle's predicted trajectory, possibly due to environmental interference, equipment failure, or other abnormal factors, resulting in low reliability and being judged as unreliable.

[0122] This application's solution establishes clear judgment rules to logically compare real-time ranging values ​​with the expected ranging range obtained based on motion prediction. When the real-time ranging value matches the expected range, it indicates that the ranging signal conforms to physical laws and system expectations, and is thus confirmed as reliable data. Conversely, when the real-time ranging value deviates from the expected range, it is considered that the signal may be subject to abnormal interference, its accuracy is questionable, and it is therefore marked as unreliable. This range-comparison-based judgment mechanism can effectively filter out abnormal ranging data, avoiding its negative impact on subsequent positioning processes.

[0123] It is worth mentioning that the step of selecting the shuttle's positioning strategy between the first positioning mode and the second positioning mode based on the evaluation results preferably includes:

[0124] Obtain evaluation results of multiple ranging signals corresponding to multiple positioning anchor points;

[0125] If the proportion of reliable ranging signals is greater than or equal to a preset determination proportion, the positioning strategy of the shuttle car is the first positioning mode, and the operating frequency of the ultra-wideband ranging device is adjusted to the preset first frequency.

[0126] If the proportion of ranging signals deemed reliable is less than the determined proportion, the positioning strategy of the shuttle car is the second positioning mode, and the operating frequency of the ultra-wideband ranging device is adjusted to a preset second frequency, which is lower than the first frequency.

[0127] The acquisition of evaluation results for multiple ranging signals corresponding to multiple positioning anchor points refers to the pre-deployment of multiple positioning anchor points within the tunnel. Each anchor point can communicate with the ultra-wideband ranging device on the shuttle car and generate a ranging signal. For each anchor point, its corresponding ranging signal undergoes a reliability assessment, yielding a reliable or unreliable evaluation result. These evaluation results are collected for comprehensive judgment. A preset judgment ratio is a configurable threshold used to measure the overall reliability level of the ranging signal under the current environment. For example, this ratio can be set to 0.6, 0.7, or 0.8, depending on the requirements for positioning accuracy and robustness. When the proportion of ranging signals judged as reliable is greater than or equal to this judgment ratio, it indicates that the ultra-wideband ranging conditions under the current environment are good, and high-precision positioning can be achieved using ultra-wideband ranging; therefore, the first positioning mode is selected. Simultaneously, to fully utilize the favorable ranging conditions, the operating frequency of the ultra-wideband ranging device is adjusted to a preset first frequency. This first frequency is typically higher, providing finer ranging resolution and higher positioning accuracy. In practical applications, if the proportion of ranging signals deemed reliable is less than the predetermined proportion, it indicates poor ultra-wideband ranging conditions in the current environment, such as the presence of numerous obstacles, signal interference, or severe multipath effects. In this case, to ensure the continuity and stability of positioning, the system selects a second positioning mode, which may rely more heavily on environmental structural reference information for positioning. Simultaneously, the operating frequency of the ultra-wideband ranging device is adjusted to a preset second frequency. This second frequency is lower than the first frequency, reducing the power consumption of the ultra-wideband ranging device and providing a basis for continuously assessing the reliability of the ranging signals.

[0128] This application's solution effectively addresses the positioning strategy misjudgment problem that might arise from relying solely on the reliability assessment of a single ranging signal by introducing a comprehensive judgment of the reliability ratio of multiple ranging signals. When most ranging signals are deemed reliable, it indicates a favorable ultra-wideband (UWB) ranging environment. In this case, selecting the primary positioning mode based on UWB ranging and employing a higher operating frequency maximizes the high accuracy advantage of UWB ranging. Conversely, when the proportion of reliable ranging signals is low, the system can promptly identify a harsh UWB ranging environment, switching to a secondary positioning mode based on environmental structure reference information and reducing the operating frequency of the UWB ranging device. This adaptive strategy selection and frequency adjustment mechanism allows the positioning system to dynamically optimize its performance based on actual environmental conditions.

[0129] The following is a specific example to illustrate this.

[0130] Suppose that five positioning anchor points are pre-deployed in the tunnel area where the coal shuttle car travels. At a certain moment, the ultra-wideband ranging device on the shuttle car communicates with each of the five anchor points and collects five ranging signals. After real-time evaluation, the reliability assessment results of these five ranging signals are as follows: Anchor 1 (reliable), Anchor 2 (reliable), Anchor 3 (unreliable), Anchor 4 (reliable), and Anchor 5 (reliable). At this time, four ranging signals are judged to be reliable. If the preset judgment ratio is 0.7 (i.e., 70%), then the proportion of reliable ranging signals is 4 / 5 = 0.8, which is greater than or equal to the preset judgment ratio of 0.7. Therefore, the system will select the first positioning mode and adjust the operating frequency of the ultra-wideband ranging device to the preset first frequency to achieve high-precision positioning. As another specific implementation, suppose that at another moment, the reliability assessment results of the five ranging signals are as follows: Anchor 1 (reliable), Anchor 2 (unreliable), Anchor 3 (unreliable), Anchor 4 (reliable), and Anchor 5 (unreliable). At this point, two ranging signals are determined to be reliable. The proportion of reliable ranging signals is 2 / 5 = 0.4, which is less than the preset determination proportion of 0.7. Therefore, the system will select the second positioning mode and adjust the operating frequency of the ultra-wideband ranging device to the preset second frequency.

[0131] In some embodiments of this application, when the first positioning mode is selected, the steps of calculating the current pose of the shuttle car from the motion parameters collected by the inertial measurement device installed on the shuttle car, correcting the current pose based on the ranging signal, and outputting the positioning result preferably include:

[0132] The current pose of the shuttle car is calculated from the motion parameters collected by the inertial measurement unit installed on the shuttle car;

[0133] Based on the ranging signal, a pose correction amount is obtained to correct the current pose.

[0134] The current pose is corrected based on the pose correction amount, and the positioning result is output.

[0135] The calculation of the shuttle car's current pose from motion parameters collected by the inertial measurement unit (IMU) mounted on the shuttle car involves using motion parameters such as acceleration and angular velocity acquired by the IMU to continuously calculate the shuttle car's position and attitude through an inertial navigation algorithm, thereby obtaining the shuttle car's real-time pose at a certain moment. This calculation process typically involves integrating acceleration and angular velocity to estimate velocity, position, and attitude, with the aim of providing continuous, high-frequency pose information.

[0136] Based on the ranging signal, the pose correction amount used to correct the current pose is obtained. This involves using the ranging signal acquired by the ultra-wideband ranging device installed on the shuttle car, combined with the known coordinates of pre-deployed positioning anchor points in the tunnel, and calculating the independent position estimate of the shuttle car using a positioning algorithm (e.g., trilateration or polygonal measurement). Subsequently, this independent position estimate is compared with the current pose calculated by the inertial measurement unit, and the deviation between the two is calculated. This deviation is the pose correction amount used to correct the current pose. Its purpose is to quantify the difference between the inertial-calculated pose and the external reference pose.

[0137] Correcting the current pose based on the pose correction amount and outputting the positioning result means applying the obtained pose correction amount to the current pose calculated by the inertial measurement unit (IMU) to eliminate or reduce accumulated errors during inertial navigation. Specific correction methods can employ state estimation algorithms such as Kalman filtering, extended Kalman filtering, or unscented Kalman filtering, incorporating the pose correction amount as an observation into the state update process to optimize and correct the current pose. The corrected pose is the final positioning result, which is then output for use by subsequent systems. The aim is to improve the accuracy and robustness of shuttle positioning.

[0138] Through the above technical solution, this application clarifies the specific implementation mechanism of shuttle pose correction in the first positioning mode. By combining continuous calculations from the inertial measurement unit with external correction from the ultra-wideband ranging signal, and introducing the concept of pose correction, the inherent cumulative error of the inertial navigation system can be effectively identified and compensated. This step-by-step correction process improves the accuracy and reliability of the positioning results.

[0139] In a further embodiment of this application, the step of obtaining the pose correction amount for correcting the current pose based on the ranging signal preferably includes:

[0140] Based on the evaluation results, multiple fusion weights are assigned to the ranging signals corresponding to multiple positioning anchor points;

[0141] Based on the fusion weights and the pre-stored coordinates of multiple positioning anchors, the multiple ranging signals are weighted and the positioning solution is calculated to obtain the estimated pose of the shuttle car.

[0142] The pose deviation between the current pose and the estimated pose is calculated to obtain the pose correction amount.

[0143] The fusion weighting of multiple ranging signals corresponding to multiple positioning anchor points involves assigning a weight value to each ranging signal based on the reliability assessment of that signal. Reliable ranging signals are typically assigned higher fusion weights, while unreliable signals are assigned lower weights, or even zero weights. Various strategies can be employed for weight allocation. For example, different weight ranges can be set based on the reliability level of the ranging signals (e.g., high, medium, low), or a continuous function can be used to map reliability assessment values ​​to weight values. The aim is to ensure that in subsequent positioning calculations, more reliable ranging signals have a greater impact on the final positioning result, thereby improving positioning accuracy and robustness.

[0144] Based on the fusion weights and the pre-stored coordinates of multiple positioning anchors, weighted positioning calculations are performed on multiple ranging signals to obtain the estimated pose of the shuttle. This involves using the known spatial coordinates of each positioning anchor and its corresponding weighted ranging signal, and employing a positioning algorithm (e.g., least squares, Kalman filtering, or particle filtering) to calculate the estimated pose of the shuttle. Weighted positioning calculation means that in the algorithm, the contribution of each ranging signal to the shuttle pose is proportional to its assigned fusion weight. For example, in the least squares method, the error term is multiplied by the corresponding weight to minimize the weighted squared error. The aim is to comprehensively utilize the ranging information from multiple positioning anchors and optimize it based on its reliability, thereby obtaining a more accurate and stable estimated shuttle pose than a single ranging signal.

[0145] The pose correction amount is calculated by comparing the current pose calculated by the inertial measurement unit (IMU) with the estimated pose calculated by weighted positioning, and then calculating the difference in position and attitude between the two. This difference is the pose deviation, which reflects the inconsistency between the inertial calculation result and the external ranging correction result. The pose correction amount is calculated based on this pose deviation and is used to adjust the current pose calculated by the inertial measurement unit towards a more accurate estimated pose. Its purpose is to provide a precise correction value to eliminate or reduce the accumulated errors during the inertial calculation process, making the final positioning result of the shuttle closer to the true pose.

[0146] Through the above technical solution, this application can dynamically adjust the contribution of the ranging signal in the positioning calculation according to the actual reliability of the ranging signal, avoiding positioning errors introduced by low-quality ranging signals and improving the positioning accuracy of the shuttle car in the first positioning mode. Especially in the roadway environment, the ranging signal is easily interfered with. This solution ensures that even if some ranging signals are of poor quality, the overall positioning system can still maintain high accuracy by intelligently allocating fusion weights, thereby providing more reliable position and pose information for the safe and efficient operation of the coal transport shuttle car.

[0147] The following is a specific example to illustrate this.

[0148] Suppose three positioning anchor points A, B, and C are deployed in a tunnel, and their pre-stored coordinates are known. An ultra-wideband ranging device on the shuttle car collects ranging signals corresponding to these three anchor points. After real-time evaluation of the reliability of the ranging signals, the reliability evaluation result for the ranging signal of anchor point A is "reliable," the evaluation result for the ranging signal of anchor point B is "reliable," and the evaluation result for the ranging signal of anchor point C is "unreliable." Based on these evaluation results, the system can assign a higher fusion weight (e.g., 0.45) to the ranging signals of anchor points A and B, and a lower fusion weight (e.g., 0.1) to the ranging signal of anchor point C. Subsequently, using these three weighted ranging signals and the pre-stored coordinates of anchor points A, B, and C, the weighted least squares method is used to calculate the estimated pose of the shuttle car. For example, if the current pose calculated by the inertial measurement unit is (x_imu, y_imu, θ_imu), and the estimated pose obtained by the weighted positioning solution is (x_uwb, y_uwb, θ_uwb), then the pose deviation Δx = x_uwb - x_imu, Δy = y_uwb - y_imu, and Δθ = θ_uwb - θ_imu. This (Δx, Δy, Δθ) is the pose correction amount used to correct the current pose. By applying this correction amount to the inertial calculation result, a final positioning result optimized and corrected by the external ranging signal can be obtained, thereby effectively improving the positioning accuracy of the shuttle.

[0149] In some embodiments of this application, the steps of obtaining the current pose, querying the environmental structure reference information to obtain reference features corresponding to the current pose, adjusting the current pose based on the reference features, and outputting the positioning result when the second positioning mode is selected preferably include:

[0150] Obtain the current pose and determine the spatial query range based on the current pose;

[0151] From the environmental structure reference information, select reference features that are within the spatial query range;

[0152] Calculate the geometric deviation between the current pose and the reference feature;

[0153] If the geometric deviation exceeds a preset deviation range, a geometric correction amount proportional to the geometric deviation is calculated. The geometric correction amount is equal to the product of the geometric deviation and a preset correction ratio, where the correction ratio is less than 1.

[0154] Based on the geometric correction, the current pose is adjusted, and the positioning result is output.

[0155] The process involves acquiring the current pose of the shuttle, which can be calculated using an inertial measurement unit. Subsequently, based on this current pose, a spatial query range is determined. This spatial query range aims to define the area for searching relevant reference features within the environmental structural reference information; for example, it can be determined based on the uncertainty ellipse of the current pose or a preset search radius.

[0156] Reference features located within the spatial query range are selected from pre-built environmental structural reference information. These reference features can be geometric features within the alleyway, such as wall corners, support edges, or specific structural points, which have known precise locations and geometric descriptions in the environmental structural reference information.

[0157] The geometric deviation between the current pose and the reference feature is calculated. This geometric deviation quantifies the inconsistency between the currently estimated shuttle pose and the corresponding reference feature in the environmental structural reference information. For example, the geometric difference between the sensor data (such as laser scan data) corresponding to the current pose and the reference feature in the environmental structural reference information can be calculated using a point cloud registration algorithm (such as the Iterative Closest Point (ICP) algorithm or a variant thereof) to obtain the deviation in position and attitude.

[0158] If the calculated geometric deviation exceeds a preset deviation range, a geometric correction amount proportional to the geometric deviation is calculated. The preset deviation range is a threshold used to determine whether the matching degree between the current pose and the reference feature needs correction. When the deviation is too large, it indicates a significant error in the current pose, requiring adjustment. The geometric correction amount is designed to be equal to the product of the geometric deviation and a preset correction ratio, where the correction ratio is set to be less than 1. This aims to avoid making excessively large corrections at once, thereby improving the stability and convergence of the adjustment process.

[0159] Based on the calculated geometric correction, the current pose is adjusted, and the final positioning result is output. This adjustment process corrects the current pose to a position and orientation that better conforms to the environmental structural reference information.

[0160] This application's solution effectively addresses the issues of insufficient positioning accuracy and poor stability that may result from simple adjustments based solely on reference features in the second positioning mode. By introducing spatial query range, geometric deviation calculation, and geometric correction based on the deviation range and correction ratio, this solution enables gradual and controlled adjustments to the current pose. This adjustment mechanism avoids system oscillations or overshoot that may be caused by a single large-scale correction, ensuring the smoothness and convergence of the positioning process.

[0161] The following is a specific example to illustrate this.

[0162] Assuming the coal shuttle is traveling in the tunnel, and the ranging signal collected by its ultra-wideband ranging device is deemed unreliable, the system enters a second positioning mode. At this point, the shuttle's inertial measurement unit calculates a current pose, for example, its position is (X, Y, Z), and its attitude is (Roll, Pitch, Yaw). The system then determines a spatial query range, for example, with a radius of 5 meters, centered on this current pose. Subsequently, it selects all reference features located within this 5-meter query range from pre-constructed tunnel environment structural reference information (e.g., a 3D point cloud map containing geometric features such as tunnel walls, supports, and corners).

[0163] Next, the system matches the laser scan data corresponding to the current pose (or the local environmental features derived from the current pose) with the selected reference features and calculates the geometric deviation between them. For example, using the Iterative Closest Point (ICP) algorithm, a positional deviation of 0.2 meters and a heading angle deviation of 3 degrees are calculated between the current pose and the reference features. If the preset deviation range is 0.1 meters for positional deviation and 1 degree for heading angle deviation, the calculated deviation exceeds the preset range. The system will then calculate the geometric correction amount according to a preset correction ratio (e.g., 0.5). Specifically, the positional correction is 0.2 meters * 0.5 = 0.1 meters, and the heading angle correction is 3 degrees * 0.5 = 1.5 degrees. Finally, based on these geometric corrections, the shuttle's current pose is adjusted to more accurately align with the environmental structure reference information, and the adjusted high-precision positioning result is output.

[0164] like Figure 2 As shown, this application also discloses a high-precision positioning system 200 for a coal shuttle car, comprising:

[0165] The environmental information construction module 210 is used to construct environmental structure reference information based on the tunnel structure data collected by the laser scanning device installed on the shuttle car;

[0166] The ranging signal evaluation module 220 is used to evaluate the reliability of the ranging signal collected by the ultra-wideband ranging device installed on the shuttle in real time and obtain the evaluation result.

[0167] The positioning strategy adjustment module 230 is used to select the positioning strategy of the shuttle car between the first positioning mode and the second positioning mode based on the evaluation result.

[0168] The internal sensing and positioning module 240 is used to calculate the current pose of the shuttle car from the motion parameters collected by the inertial measurement device installed on the shuttle car when the first positioning mode is selected, correct the current pose based on the ranging signal, and output the positioning result.

[0169] The external auxiliary positioning module 250 is used to obtain the current pose, query the environmental structure reference information to obtain the reference features corresponding to the current pose, adjust the current pose based on the reference features, and output the positioning result when the second positioning mode is selected.

[0170] The environmental information construction module 210 can be a standalone processor or a software module integrated into the main control unit. It is configured to receive tunnel structure data collected by a laser scanning device mounted on the shuttle. This module processes the raw tunnel structure data into structured environmental reference information by executing specific algorithms, such as point cloud registration, feature extraction, and map building algorithms. For example, the environmental information construction module 210 can fit the laser point cloud data into a geometric model of the tunnel walls, roof, and floor, or extract stable geometric feature points, lines, and surfaces, storing them in memory or a database for subsequent positioning. As a preferred implementation, the environmental information construction module 210 can employ a SLAM (Simultaneous Localization and Mapping)-based mapping method to construct a high-precision tunnel environment map during the initial shuttle run.

[0171] The ranging signal evaluation module 220 can be a standalone signal processing unit or integrated into a microcontroller within the ultra-wideband ranging device. It is configured to receive and analyze the ranging signals acquired by the ultra-wideband ranging device mounted on the shuttle in real time. The ranging signal evaluation module 220 evaluates the reliability of the ranging signal by executing signal quality analysis algorithms, such as calculating signal strength, signal-to-noise ratio, and fluctuations in time of arrival (ToA). For example, if the ranging signal strength is below a preset threshold or the signal-to-noise ratio is too low, the module can determine that the ranging signal is unreliable. In some embodiments, the ranging signal evaluation module 220 can also compare the ranging value with the motion prediction information of the shuttle to determine whether the ranging value is within a reasonable range, thereby outputting the evaluation result of the ranging signal.

[0172] The positioning strategy adjustment module 230 can be a central control unit or decision module, configured to receive the evaluation results output by the ranging signal evaluation module. Based on preset logic or rules, such as a threshold based on the proportion of reliable ranging signals, the positioning strategy adjustment module 230 dynamically selects the shuttle's positioning strategy between a first positioning mode and a second positioning mode. For example, when the proportion of reliable ranging signals is higher than a certain preset value, the positioning strategy adjustment module 230 instructs the system to enter the first positioning mode; otherwise, it switches to the second positioning mode. The intelligent decision-making of the positioning strategy adjustment module 230 ensures that the positioning system can adaptively adjust its operating mode according to environmental changes.

[0173] The internal sensing and positioning module 240 can be a fusion processor configured to operate when a first positioning mode is selected. The internal sensing and positioning module 240 receives motion parameters collected by an inertial measurement unit (IMU) mounted on the shuttle and calculates the shuttle's current pose. Simultaneously, the internal sensing and positioning module 240 also receives ranging signals from an ultra-wideband ranging device. By executing data fusion algorithms, such as Kalman filtering, extended Kalman filtering, or particle filtering, the internal sensing and positioning module 240 uses the pose calculated by the IMU as a prediction value and the position information calculated from the reliable ranging signal as an observation value to perform real-time correction of the current pose and output a high-precision positioning result.

[0174] The external auxiliary localization module 250 can be a feature matching processor, configured to operate when the second localization mode is selected. The external auxiliary localization module 250 acquires the current pose calculated by the internal perception localization module and queries the environmental structure reference information provided by the environmental information construction module based on this pose to obtain reference features corresponding to the current pose. Subsequently, the external auxiliary localization module 250 calculates the geometric deviation between the two by executing a feature matching algorithm. Finally, the current pose is adjusted based on this geometric deviation, and the localization result is output.

[0175] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0176] The foregoing has provided a detailed description of the preferred embodiments of this application. However, this application is not limited to the above-described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined in this application.

Claims

1. A high-precision positioning method for a coal transport shuttle car, characterized in that, Includes the following steps: Based on the tunnel structure data collected by the laser scanning device installed on the shuttle car, environmental structure reference information is constructed. The reliability of the ranging signal collected by the ultra-wideband ranging device installed on the shuttle car is evaluated in real time, and the evaluation results are obtained. Based on the evaluation results, the positioning strategy of the shuttle is selected between the first positioning mode and the second positioning mode; When the first positioning mode is selected, the current pose of the shuttle car is calculated from the motion parameters collected by the inertial measurement device installed on the shuttle car. Based on the ranging signal, the current pose is corrected and the positioning result is output. When the second positioning mode is selected, the current pose is obtained, the environmental structure reference information is queried to obtain the reference features corresponding to the current pose, the current pose is adjusted based on the reference features, and the positioning result is output.

2. The high-precision positioning method for a coal shuttle car according to claim 1, characterized in that, The step of constructing environmental structure reference information based on the tunnel structure data collected by the laser scanning device installed on the shuttle car includes: Based on the tunnel structure data collected by the laser scanning device installed on the shuttle car, multiple reference features distributed in different structural parts of the tunnel area are identified and extracted. Based on the aforementioned reference features, environmental structure reference information is constructed.

3. The high-precision positioning method for a coal shuttle car according to claim 2, characterized in that, The step of identifying and extracting multiple reference features distributed in different structural parts of the roadway area based on the roadway structure data collected by the laser scanning device installed on the shuttle car includes: Based on the laser scanning device installed on the shuttle car, the same tunnel area is scanned multiple times to obtain tunnel structure data; Based on the tunnel structure data, multiple geometric features distributed in different structural parts of the tunnel area are identified and extracted; Calculate the positional deviation of the geometric feature during multiple scans; Geometric features whose positional deviation is less than a preset stability threshold are determined to be stable features.

4. The high-precision positioning method for a coal shuttle car according to claim 1, characterized in that, The steps for evaluating the reliability of the ranging signal acquired by the ultra-wideband ranging device installed on the shuttle car in real time and obtaining the evaluation result include: Based on the motion prediction of the shuttle car by the inertial measurement device installed on the shuttle car, the predicted position range of the shuttle car after a preset short time is obtained; Based on the known coordinates of the positioning anchor point and the predicted location range, the expected ranging range of the positioning anchor point is calculated. The positioning anchor point is pre-deployed in the roadway and used to communicate with the ultra-wideband ranging device installed on the shuttle car. Based on the ranging signal collected by the ultra-wideband ranging device over the preset short time, a real-time ranging value is obtained. The reliability assessment result of the ranging signal is obtained by comparing the real-time ranging value with the expected ranging range.

5. The high-precision positioning method for a coal shuttle car according to claim 4, characterized in that, The step of comparing the real-time ranging value with the expected ranging range to obtain the reliability assessment result of the ranging signal includes: If the real-time ranging value is within the expected ranging range, then the reliability assessment result of the ranging signal is determined to be reliable. If the real-time ranging value exceeds the expected ranging range, the reliability assessment result of the ranging signal is determined to be unreliable.

6. The high-precision positioning method for a coal shuttle car according to claim 5, characterized in that, The step of selecting the shuttle's positioning strategy between the first positioning mode and the second positioning mode based on the evaluation result includes: Obtain evaluation results of multiple ranging signals corresponding to multiple positioning anchor points; If the proportion of reliable ranging signals is greater than or equal to a preset determination proportion, the positioning strategy of the shuttle car is the first positioning mode, and the operating frequency of the ultra-wideband ranging device is adjusted to the preset first frequency. If the proportion of ranging signals deemed reliable is less than the determined proportion, the positioning strategy of the shuttle car is the second positioning mode, and the operating frequency of the ultra-wideband ranging device is adjusted to a preset second frequency, which is lower than the first frequency.

7. The high-precision positioning method for a coal shuttle car according to claim 5, characterized in that, When the first positioning mode is selected, the steps of calculating the current pose of the shuttle car from the motion parameters collected by the inertial measurement device installed on the shuttle car, correcting the current pose based on the ranging signal, and outputting the positioning result include: The current pose of the shuttle car is calculated from the motion parameters collected by the inertial measurement unit installed on the shuttle car; Based on the ranging signal, a pose correction amount is obtained to correct the current pose. The current pose is corrected based on the pose correction amount, and the positioning result is output.

8. The high-precision positioning method for a coal shuttle car according to claim 7, characterized in that, The step of obtaining the pose correction amount for correcting the current pose based on the ranging signal includes: Based on the evaluation results, multiple fusion weights are assigned to the ranging signals corresponding to multiple positioning anchor points; Based on the fusion weights and the pre-stored coordinates of multiple positioning anchors, the multiple ranging signals are weighted and the positioning solution is calculated to obtain the estimated pose of the shuttle car. The pose deviation between the current pose and the estimated pose is calculated to obtain the pose correction amount.

9. A high-precision positioning method for a coal shuttle car according to claim 1, characterized in that, The steps of obtaining the current pose, querying the environmental structure reference information to obtain reference features corresponding to the current pose, adjusting the current pose based on the reference features, and outputting the positioning result when the second positioning mode is selected include: Obtain the current pose and determine the spatial query range based on the current pose; From the environmental structure reference information, select reference features that are within the spatial query range; Calculate the geometric deviation between the current pose and the reference feature; If the geometric deviation exceeds a preset deviation range, a geometric correction amount proportional to the geometric deviation is calculated. The geometric correction amount is equal to the product of the geometric deviation and a preset correction ratio, where the correction ratio is less than 1. Based on the geometric correction, the current pose is adjusted, and the positioning result is output.

10. A high-precision positioning system for a coal transport shuttle car, characterized in that, include: The environmental information construction module is used to construct environmental structure reference information based on the tunnel structure data collected by the laser scanning device installed on the shuttle car; The ranging signal evaluation module is used to evaluate the reliability of the ranging signal collected by the ultra-wideband ranging device installed on the shuttle in real time and obtain the evaluation result. The positioning strategy adjustment module is used to select the positioning strategy of the shuttle car between the first positioning mode and the second positioning mode based on the evaluation results. The internal sensing and positioning module is used to calculate the current pose of the shuttle car from the motion parameters collected by the inertial measurement device installed on the shuttle car when the first positioning mode is selected, correct the current pose based on the ranging signal, and output the positioning result. An external auxiliary positioning module is used to obtain the current pose, query the environmental structure reference information to obtain reference features corresponding to the current pose, adjust the current pose based on the reference features, and output the positioning result when the second positioning mode is selected.

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