Unmanned driving method and system in limited space, electronic equipment and medium

Abstract

The invention discloses an unmanned driving method and system in a limited space, electronic equipment and a medium, and the method comprises the steps: carrying out the path planning through a pre-marked UWB track point coordinate, and determining a target planning path; acquiring UWB position data and laser radar data of the unmanned equipment driving on the target planned path; determining the current position coordinate of the unmanned equipment according to the UWB position data and the laser radar data; determining a polar coordinate resolving angle according to the current position coordinate; determining two security boundaries based on the laser radar data; determining a safety boundary correction angle according to the two safety boundaries; a target control angle and a target control angular velocity are calculated based on the polar coordinate solution angle and the safety boundary correction angle. According to the invention, efficient operation in an underground narrow space can be met.

Description

Technical Field

[0001] The present application relates to the field of unmanned driving technology, and in particular to an unmanned driving method, system, electronic equipment and medium in a confined space. Background Art

[0002] As the global demand for mineral resources increases, many shallow ore bodies have been gradually depleted, causing mining to gradually shift to deep underground ore bodies. The harsh working environment of underground mines has led to a shortage of front-line workers, forcing mining companies to seek safer and more economical solutions. Therefore, the shift to a mining development model of "automation with fewer people, intelligence with no people" has become an inevitable trend in the advancement of underground mining technology.

[0003] In the field of underground mining transportation, articulated unmanned driving equipment has become a very suitable equipment for operation in narrow underground spaces due to its small turning radius and strong maneuverability. However, articulated unmanned driving equipment faces unique challenges in achieving unmanned driving. Due to its complex steering characteristics and the narrow and changeable underground tunnel environment, the application effect of conventional simultaneous localization and mapping (SLAM) algorithms and image recognition technologies in such environments is limited, and the research and development and implementation costs are high. These technologies often make it difficult for articulated unmanned driving equipment to adapt to the special environment of the underground, which is dim, narrow and full of various obstacles. Therefore, it is difficult for articulated unmanned driving equipment to meet the requirements of efficient operation in narrow underground spaces. Summary of the invention

[0004] The present application aims to propose an unmanned driving method, system, electronic equipment and medium in a confined space, which can meet the requirements of efficient operation in narrow underground spaces.

[0005] In a first aspect, an embodiment of the present application provides an unmanned driving method in a confined space, the method comprising: Path planning is performed through the coordinates of pre-marked UWB trajectory points to determine the target planning path; Acquire UWB position data and LiDAR data of the unmanned driving device traveling on the target planning path; Determine the current position coordinates of the unmanned driving device according to the UWB position data and the laser radar data; Determine a polar coordinate solution angle according to the current position coordinates; Based on the laser radar data, two safety boundaries are determined; Determining a safety boundary correction angle according to the two safety boundaries; Based on the polar coordinate solution angle and the safety margin correction angle, a target control angle and a target control angular velocity are calculated.

[0006] Compared with the prior art, the first aspect of the present application has the following beneficial effects: The method performs path planning through pre-marked UWB trajectory point coordinates to determine the target planning path, so that the unmanned driving device can travel on the optimal path as much as possible; obtains UWB position data and laser radar data of the unmanned driving device traveling on the target planning path, and determines the current position coordinates of the unmanned driving device based on the UWB position data and the laser radar data. The current position coordinates of the unmanned driving device are determined based on multiple data, which can improve the accuracy of the obtained current position coordinates; determines the polar coordinate solution angle based on the current position coordinates, determines two safety boundaries based on the laser radar data, determines the safety boundary correction angle based on the two safety boundaries, and calculates the target control angle and the target control angular velocity based on the polar coordinate solution angle and the safety boundary correction angle, so that the unmanned driving device can travel safely and meet the requirements of efficient operation in narrow underground spaces.

[0007] In some embodiments, performing path planning by using pre-marked UWB trajectory point coordinates to determine a target planning path includes: Obtaining the coordinates of the pre-marked UWB trajectory points, and calculating the measured distance and the actual distance between every two adjacent pre-marked UWB trajectory point coordinates, wherein the measured distance is the distance obtained by the UWB method, and the actual distance is the distance obtained by the actual measurement; Calculating an error between the measured distance and the actual distance; Performing path planning according to the abscissa of the pre-marked UWB trajectory point coordinates to obtain a plurality of planned paths; Based on the error, calculating the total error corresponding to the coordinates of all pre-marked UWB trajectory points in each planned path; The planned path corresponding to the minimum total error is selected as the target planning path.

[0008] In some implementations, determining the current position coordinates of the unmanned driving device according to the UWB position data and the laser radar data includes: Fusing the UWB position data and the laser radar data to obtain fused data; The current position coordinates of the unmanned driving device are determined based on the fused data.

[0009] In some implementations, determining the polar coordinate solution angle according to the current position coordinates includes: Obtaining the target driving trajectory point coordinates corresponding to the current position coordinates from the target planned path; Convert the target driving trajectory point coordinates into a polar coordinate system trajectory direction; The angle formed by the trajectory direction of the polar coordinate system and the center line of the unmanned driving device is used as the polar coordinate solution angle.

[0010] In some embodiments, determining two safety boundaries based on the laser radar data includes: The laser radar data is input into the SLAM algorithm to obtain two safety boundaries.

[0011] In some implementations, determining the safety boundary correction angle according to the two safety boundaries includes: confirming a middle line between the two safety boundaries; The angle between the middle line and the center line of the unmanned driving device is used as the safety boundary correction angle.

[0012] In some embodiments, the calculating the target control angle and the target control angular velocity based on the polar coordinate solution angle and the safety margin correction angle includes: Calculating a safety margin correction angle difference between the safety margin correction angle and the polar coordinate solution angle; Calculating a target control angle according to the safety margin correction angle difference and the polar coordinate solution angle; According to the target control angle, a target control angular velocity is determined.

[0013] In a second aspect, an embodiment of the present application further provides an unmanned driving system in a confined space, the system comprising: A path planning unit is used to perform path planning through the coordinates of pre-marked UWB trajectory points to determine the target planning path; A data acquisition unit, used to acquire UWB position data and laser radar data of an unmanned driving device traveling on the target planning path; A position coordinate determination unit, used to determine the current position coordinates of the unmanned driving device according to the UWB position data and the laser radar data; A driving direction determination unit, used to determine a polar coordinate solution angle according to the current position coordinates; A safety boundary determination unit, configured to determine two safety boundaries based on the laser radar data; A correction angle determination unit, used to determine a safety boundary correction angle according to the two safety boundaries; A data calculation unit is used to calculate a target control angle and a target control angular velocity based on the polar coordinate solution angle and the safety margin correction angle.

[0014] In the third aspect, an embodiment of the present application also provides an electronic device, comprising at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute an unmanned driving method in a confined space as described above.

[0015] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the unmanned driving method in a confined space as described above.

[0016] It can be understood that the beneficial effects of the second to fourth aspects compared with the related art are the same as the beneficial effects of the first aspect compared with the related art. Please refer to the relevant description in the first aspect, and no further details will be given here. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 It is a flowchart of an embodiment of an unmanned driving method in a confined space provided by the present application; Figure 2 It is a flow chart of the best embodiment of the unmanned driving method in a confined space provided by the present application; Figure 3 It is a schematic diagram of path planning in the best embodiment of the unmanned driving method in a confined space provided by the present application; Figure 4 It is a schematic diagram of polar coordinate posture correction in a local confined space in the best embodiment of the unmanned driving method in a confined space provided by the present application; Figure 5 is a structural schematic diagram of an embodiment of an unmanned driving system in a confined space provided by the present application; Description of labels: 101. Safety boundary correction angle; 102. Polar coordinate solution angle; 103. Two safety boundaries; 104. Pre-marked UWB trajectory point coordinates; 105. Middle line; 106. Current driving direction; 107. Unmanned driving equipment; 108. Polar coordinate system trajectory line. DETAILED DESCRIPTION

[0018] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0019] In the description of this application, if there is a description of first, second, etc., it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0020] In the description of the present application, it should be understood that the descriptions involving orientation, such as the orientation or positional relationship indicated as up, down, etc., are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0021] In the description of this application, it should be noted that, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meaning of the above terms in this application based on the specific content of the technical solution.

[0022] In the field of underground mining transportation, articulated unmanned equipment has become a very suitable equipment for operation in narrow underground spaces due to its small turning radius and strong maneuverability. However, articulated unmanned equipment faces unique challenges in achieving unmanned driving. Due to its complex steering characteristics and the narrow and changeable underground tunnel environment, conventional SLAM (Simultaneous Localization and Mapping) and image recognition technologies have limited application effects in such environments, and the research and development and implementation costs are high. These technologies often make it difficult for articulated unmanned equipment to adapt to the special environment of the underground, which is dim, narrow and full of various obstacles. Therefore, it is difficult for articulated unmanned equipment to meet the requirements of efficient operation in narrow underground spaces.

[0023] In order to solve the above-mentioned problem that the existing articulated unmanned driving equipment is difficult to meet the requirements of efficient operation in narrow underground spaces, the present application proposes an unmanned driving method, system, electronic equipment and medium in confined spaces.

[0024] Reference Figure 1 The present application embodiment provides an unmanned driving method in a confined space, and the method comprises the following steps: Step S100, performing path planning through pre-marked UWB trajectory point coordinates 104 to determine a target planning path; Step S200, obtaining UWB position data and laser radar data of the unmanned driving device 107 traveling on the target planned path; Step S300, determining the current position coordinates of the unmanned driving device 107 according to the UWB position data and the laser radar data; Step S400, determining the polar coordinate solution angle 102 according to the current position coordinates; Step S500, determining two safety boundaries 103 based on the laser radar data; Step S600, determining the safety boundary correction angle 101 according to the two safety boundaries 103; Step S700 , calculating a target control angle and a target control angular velocity based on the polar coordinate solution angle 102 and the safety margin correction angle 101 .

[0025] In this embodiment, path planning is performed through pre-marked UWB trajectory point coordinates 104 to determine the target planned path, so that the unmanned driving device 107 can travel on the optimal path as much as possible; UWB position data and laser radar data of the unmanned driving device 107 traveling on the target planned path are obtained, and the current position coordinates of the unmanned driving device 107 are determined based on the UWB position data and the laser radar data. The current position coordinates of the unmanned driving device 107 are determined based on multiple data, which can improve the accuracy of the obtained current position coordinates; based on the current position coordinates, the polar coordinate solution angle 102 is determined, based on the laser radar data, two safety boundaries 103 are determined, and based on the two safety boundaries 103, the safety boundary correction angle 101 is determined, and based on the polar coordinate solution angle 102 and the safety boundary correction angle 101, the target control angle and the target control angular velocity are calculated, so that the unmanned driving device 107 can travel safely and meet the requirements of efficient operation in narrow underground spaces.

[0026] The pre-marked UWB trajectory point coordinates 104 may be pre-set UWB markers, and the UWB trajectory point coordinates may be acquired using UWB technology.

[0027] The above-mentioned UWB technology is an ultra-wideband technology, which is a wireless carrier communication technology. It does not use a sinusoidal carrier, but uses nanosecond-level non-sinusoidal narrow pulses to transmit data, so it occupies a wide spectrum range.

[0028] The above-mentioned path planning is performed through the pre-marked UWB trajectory point coordinates 104 to determine the target planning path, which can be obtained by using a trajectory point planning algorithm and a route matching algorithm based on the pre-marked UWB trajectory point coordinates 104. It can also be obtained by using an existing path planning method.

[0029] The above-mentioned acquisition of UWB position data and lidar data of the unmanned driving device 107 traveling on the target planned path can be performed by installing a UWB identification card and a lidar on the unmanned driving device 107 traveling on the target planned path, and acquiring the UWB position data and lidar data of the unmanned driving device 107 through the UWB identification card and the lidar.

[0030] The above method of determining the current position coordinates of the unmanned driving device 107 based on the UWB position data and the laser radar data may be to use a SLAM algorithm to determine the current position coordinates of the unmanned driving device 107 based on the UWB position data and the laser radar data. Alternatively, the Kalman filter method may be used to first fuse the UWB position data and the laser radar data, and then determine the current position coordinates of the unmanned driving device 107.

[0031] The above-mentioned laser radar data may include surrounding environment data and more accurate data such as the current position of the unmanned driving device 107.

[0032] The polar coordinate solution angle 102 is determined according to the current position coordinates. The target position coordinates can be determined according to the current position coordinates, and then the polar coordinate solution angle 102 can be determined according to the current position coordinates and the target position coordinates.

[0033] The above-mentioned determination of the two safety boundaries 103 based on the laser radar data may be performed by inputting the laser radar data into the SLAM algorithm, and obtaining the two safety boundaries 103 through the safety obstacle avoidance calculation in the SLAM algorithm. For example, the current position of the unmanned driving device is obtained through the laser radar data, and then the safety obstacle avoidance in the SLAM algorithm is used to calculate two safety boundary lines that are relatively safe relative to the two sides of the road at the current position, and the two safety boundary lines are at a certain distance from the two sides of the road.

[0034] In some implementations, path planning is performed using pre-marked UWB trajectory point coordinates 104 to determine a target planning path, including: Obtaining pre-marked UWB trajectory point coordinates 104, and calculating the measured distance and the actual distance between every two adjacent pre-marked UWB trajectory point coordinates 104, wherein the measured distance is the distance measured by the UWB method, and the actual distance is the distance actually measured; Calculate the error between the measured distance and the actual distance; Performing path planning according to the horizontal coordinates of the pre-marked UWB trajectory point coordinates 104 to obtain a plurality of planned paths; Based on the error, the total error corresponding to all pre-marked UWB trajectory point coordinates 104 in each planned path is calculated; The planned path corresponding to the minimum total error is selected as the target planning path.

[0035] In this embodiment, by calculating the total error corresponding to all pre-marked UWB trajectory point coordinates 104 in each planned path based on the error, and then selecting the planned path corresponding to the minimum total error as the target planned path, the obtained target planned path can be optimized, and accurate path planning can provide a reliable driving route for the unmanned driving device 107.

[0036] In some implementations, determining the current position coordinates of the unmanned driving device 107 based on the UWB position data and the laser radar data includes: Fusing the UWB position data and the laser radar data to obtain fused data; According to the fused data, the current position coordinates of the unmanned driving device 107 are determined.

[0037] In this embodiment, the UWB position data and the laser radar data are fused to obtain fused data, and then the current position coordinates of the unmanned driving device 107 are determined based on the fused data, which can make the current position coordinates of the unmanned driving device 107 more accurate.

[0038] In some implementations, determining the polar coordinate solution angle 102 according to the current position coordinates includes: Obtain the target driving trajectory point coordinates corresponding to the current position coordinates from the target planning path; Convert the coordinates of the target driving trajectory point into the trajectory direction of the polar coordinate system; The angle formed by the polar coordinate system trajectory direction and the center line of the unmanned driving device 107 is used as the polar coordinate solution angle 102.

[0039] In this embodiment, the target driving trajectory point coordinates corresponding to the current position coordinates are obtained from the target planned path, the target driving trajectory point coordinates are converted into the polar coordinate system trajectory direction, and then the angle formed by the polar coordinate system trajectory direction and the center line of the unmanned driving device 107 is used as the polar coordinate solution angle 102. This can enable the unmanned driving device 107 to continuously approach the target driving trajectory point, allow the unmanned driving device 107 to travel in the target planned path as much as possible, and improve the efficient operation of the unmanned driving device 107.

[0040] In some implementations, based on the laser radar data, determining two safety boundaries 103 includes: The lidar data is input into the SLAM algorithm to obtain two safety boundaries 103.

[0041] In this embodiment, by inputting the laser radar data into the SLAM algorithm, two safety boundaries 103 are obtained, which can ensure the driving safety of the unmanned driving device 107.

[0042] In some implementations, determining the safety boundary correction angle 101 according to the two safety boundaries 103 includes: confirming a middle line 105 between two safety boundaries 103; The angle between the middle line 105 and the center line of the unmanned driving device 107 is used as the safety margin correction angle 101.

[0043] In this embodiment, the angle between the middle line 105 and the center line of the unmanned driving device 107 is used as the safety margin correction angle 101 to ensure the driving safety of the unmanned driving device 107 .

[0044] In some implementations, the target control angle and the target control angular velocity are calculated based on the polar coordinate solution angle 102 and the safety margin correction angle 101, including: Calculate the difference of the safety margin correction angle 101 degrees between the safety margin correction angle 101 and the polar coordinate solution angle 102; Calculate the target control angle according to the safety margin correction angle 101 degree difference and the polar coordinate solution angle 102; According to the target control angle, the target control angular velocity is determined.

[0045] In this embodiment, the safety boundary correction angle 101 degree difference between the safety boundary correction angle 101 and the polar coordinate solution angle 102 is calculated, and then the target control angle is calculated based on the safety boundary correction angle 101 degree difference and the polar coordinate solution angle 102. Based on the target control angle, the target control angular velocity is determined. By simplifying the complex control process into intuitive travel direction and steering angle outputs, the unmanned driving device 107 can be driven in the target direction while ensuring the driving safety of the unmanned driving device 107, and the unmanned driving device 107 can be driven in the target planned path as much as possible, and the convenience and efficiency of operation are improved.

[0046] To facilitate understanding by those skilled in the art, a set of best embodiments is provided below: Reference Figure 2 , Figure 2The direction determination of the two-dimensional map of the device refers to the determination of the driving direction obtained by coordinate conversion. This process usually involves comparing the current driving direction of the unmanned driving device 107 and the target direction obtained by polar coordinate conversion. If the two are consistent, the unmanned driving device 107 is in a forward driving state; if they are inconsistent, the unmanned driving device 107 may be in a reverse driving state. This embodiment proposes an unmanned driving method for confined space conditions, which is specially designed to improve the navigation accuracy and operating efficiency of articulated unmanned driving equipment, while reducing the complexity and cost of the system, and adapting to the special application scenario of underground mines. This method significantly improves the driving performance of articulated unmanned driving equipment in mine tunnels by integrating advanced environmental perception, precise path planning and dynamic control technology, and significantly reduces the implementation and deployment costs of unmanned driving in mines. Specifically include the following contents: 1. Description of the SLAM source in this embodiment.

[0047] (1) SLAM includes real-time positioning.

[0048] This embodiment combines the UWB precise positioning system and the production scheduling system to plan the expected trajectory points of the unmanned equipment and generate a plane minimalist map. The UWB precise positioning system provides real-time position feedback and realizes the instant positioning function within the working range, thereby ensuring the accurate navigation of the unmanned equipment.

[0049] (2) SLAM includes real-time composition and posture correction.

[0050] By using the collaborative work of LiDAR and UWB, this embodiment simplifies the traditional map matching method and uses UWB to instantly locate and correct the position of equipment in a confined space. This process provides real-time position and posture information of the equipment in the confined space without relying on complex map construction, ensuring high-precision environmental perception and rapid response.

[0051] (3) SLAM includes orientation and trajectory planning.

[0052] In response to the safety and collision avoidance requirements in confined spaces, this embodiment converts the posture planning of the plane Cartesian coordinate system into the direction planning described by the polar coordinate system. The vector direction and steering amplitude are accurately calculated through laser radar and UWB data, where the boundary angle of the confined space is used as a passive factor and the driving direction is used as an active factor to ensure that the unmanned driving equipment always drives in the correct target direction.

[0053] 2. The independence and simplicity of data sources.

[0054] (1) LiDAR data: used for preliminary environment perception and position correction.

[0055] (2) UWB data: provides precise location information and minimalist trajectory points for real-time positioning and path constraints, simplifying map creation.

[0056] (3) Polar coordinate data: The position coordinates are extracted from the lidar and UWB data and then converted into polar coordinates for path planning and direction determination.

[0057] The data sources are independent and complementary. By combining UWB data with LiDAR data, efficient and accurate SLAM functions can be achieved. UWB data provides basic positioning, and LiDAR data is used for detail correction to ensure efficient operation of the system in confined spaces.

[0058] 3. Low storage rate characteristics of computing data.

[0059] (1) Data storage optimization: Utilize the minimalist track points provided by UWB to reduce the storage requirements of large-scale map data. Only key track points and necessary location information need to be stored, which greatly reduces the amount of data storage.

[0060] (2) Real-time processing: Simplified data structure and storage method enable the system to achieve real-time processing and rapid response under low storage rate conditions, ensuring efficient operation in complex dynamic environments.

[0061] 4. Constraint characteristics of contour safety control and path planning of unmanned driving equipment in confined spaces.

[0062] (1) Contour safety control: Based on the SLAM output results, the driving direction and position of the equipment are corrected in real time to ensure safe operation in confined spaces. LiDAR data and UWB data are used to accurately perceive environmental boundaries and obstacles, and dynamic obstacle avoidance and path correction are achieved.

[0063] (2) Path planning constraints: In a confined space, local path planning is performed using a polar coordinate system, and effective constraints are imposed by combining the actual contour and boundary information of the equipment. The minimalist SLAM algorithm (i.e., the unmanned driving method in a confined space of this embodiment) gives priority to safety and driving efficiency when planning the path, and ensures the efficient operation of the equipment in a complex environment by dynamically adjusting the driving path.

[0064] In summary, the minimalist SLAM algorithm for unmanned driving in confined space conditions makes full use of lidar data and UWB data, describes path planning through polar coordinates, and achieves efficient and accurate environmental perception and positioning. This algorithm simplifies the map creation and data storage of traditional SLAM, and provides efficient contour safety control and path planning constraints.

[0065] The specific technical solution of this embodiment includes the following steps: Step S1: Production task path planning.

[0066] When the unmanned driving system is started, the actual equipment operation route is issued through the production scheduling system based on the actual production task. Figure 3 This route (i.e., path) is planned using the UWB pre-marked track point coordinates (i.e., pre-marked UWB track point coordinates 104), where the track point coordinates are measured as In order to reduce the UWB positioning error, the UWB positioning error model is adopted as , Indicates the error, Indicates the coordinates of the actual measured trajectory points, which can be the distance obtained by actual measurement. Represents the preset UWB trajectory point coordinates and the distance measured by the UWB method. The trajectory point planning algorithm is ,in , The path matching algorithm is based on the weight obtained by minimizing the variance, and the semivariance function is used to evaluate the correlation of spatial data. , ensuring that the task path sequence is unique to the production plan. The task trajectory point coordinates and the UWB tags involved in this embodiment are measured during deployment to provide initial navigation data, establishing a reference point for real-time position monitoring in step S2.

[0067] Step S2: Real-time position feedback.

[0068] The UWB identification card and laser radar installed on the equipment monitor the equipment position in real time, and transmit the position data to the edge computer through the underground wireless network. The Kalman filter method or other existing methods capable of data fusion in the edge computer fuses the UWB data and the laser radar data, and updates the real-time position coordinate data of the unmanned equipment based on the fused data. The updated position coordinate data provides the necessary input for step S3 to ensure the accurate calculation and real-time adjustment of the driving direction.

[0069] Step S3: Determine the driving direction.

[0070] According to the real-time position coordinate data (i.e., current position coordinates) provided in step S2, the current required driving direction in the edge calculator involved in this embodiment is obtained by the UWB solution result obtained by the UWB positioning system and edge computing during the equipment's travel, and the two-dimensional Cartesian coordinate system target travel direction (i.e., target driving trajectory point coordinates) is converted into the polar coordinate system trajectory direction required for the current position of the equipment, and the polar coordinate conversion formula is: , the polar coordinate system trajectory line 108 can be referred to Figure 4The polar coordinate solution angle 102 is formed by the real-time calculated polar coordinate system trajectory direction and the center line of the unmanned equipment. The trajectory target algorithm can effectively guide the equipment toward the angle target path point of the next trajectory. The trajectory target algorithm is , Indicates the angle corresponding to the current position coordinates (i.e. the current driving direction 106), represents the expected path (i.e., the polar coordinate system trajectory direction corresponding to the coordinates of the target driving trajectory point), Q and R represent weight factors, represents the initial time, Indicates the next moment. According to the angle corresponding to the polar coordinate solution angle 102 and the current position coordinate, the driving direction of the unmanned driving device 107 is calculated, and the driving direction is calculated by the formula: ,in Indicates the angle adjusted according to real-time data (i.e. polar coordinate solution angle 102), Indicates the target driving direction of the unmanned driving device 107.

[0071] Step S4: safety margin correction.

[0072] Reference Figure 4 This embodiment involves a safety boundary correction angle 101 formed by the lane center line (i.e., the middle line 105) formed by the unmanned driving equipment contour safety control line (i.e., the two safety boundaries 103) and the equipment's actual direction center line. The safety boundary correction angle 101 is calculated as: ,in, represents the coordinates on the centerline of the lane, Indicates the current position coordinates, Indicates the angle adjustment required for safety margin correction as correction feedback. By comparing the preset trajectory and the real-time calculated trajectory, the polar coordinate solution angle 102 and the safety margin correction angle 101 in step S3 are fed back to each other to form the angle and angular velocity output by the equipment control. The equipment dynamically adjusts the driving angle and speed to adapt to the lane contour and maintain a safe distance. The specific calculation method of the angle and angular velocity is as follows: (1) Combining the polar coordinate solution angle 102 and the safety margin correction angle 101, the angle of the final control output is calculated using the following formula: , in, Indicates the angle of the final control output, represents the safety margin correction factor, The difference between the safety margin correction angle 101 and the polar coordinate solution angle 102 is represented by the safety margin correction angle 101 degree.

[0073] (2) Use the first-order dynamic response model to determine the angular velocity: , in, represents the proportional control gain, Represents angular velocity.

[0074] In order to ensure the stability and responsiveness of the system, closed-loop feedback control is used to dynamically adjust and , specifically: , in, express The proportional control gain at time, express The proportional control gain at time, and represents the adjustment factor, represents the error between the target position and the actual position, that is , express The safety margin correction factor at the moment, express Safety margin correction factor at the moment.

[0075] The output of step S4 directly affects the generation of control instructions in step S5.

[0076] Step S5: Control output simplification.

[0077] By integrating the analysis results of the above-mentioned steps S1, S2, S3 and S4 of this embodiment to simplify the output of the control instruction, the control output formula may be: ,in, , and They represent proportional gain, integral gain and differential gain respectively, directly converting the unmanned driving control output of confined space equipment into the output of the direction of travel, steering angle and angular velocity under the guidance of UWB, which greatly simplifies the unmanned driving control process of the equipment, thereby improving the simplicity of operation and execution efficiency. The output methods of steering angle and angular velocity include the following: (1) Steering angle calculation.

[0078] Define the target direction and the current direction angle , the steering angle difference is : .if If it exceeds 180°, adjust to (corresponding positive adjustment) to ensure the shortest rotation distance, where .

[0079] (2) Angular velocity output.

[0080] The angular velocity is calculated using a proportional-derivative controller (PD controller) as: , in, and They represent proportional gain and differential gain respectively, which are used to adjust response speed and stability. Indicates the rate of change of the angle difference, calculated in real time.

[0081] (3) Angular velocity smoothing and limiting.

[0082] In order to prevent the rapid change of angular velocity from damaging the mechanical system, a limiting function is introduced to smooth the angular velocity: , in, Indicates the preset maximum angular velocity.

[0083] (4) Real-time dynamic adjustment.

[0084] Adaptive rules to adjust and Based on the system performance index error and error rate of change : , , in, and represents a positive adaptation rate parameter that determines the speed and response of parameter adjustment, Express Seeking guidance, Express Derivative.

[0085] Parameter update mechanism and The value of is updated in real time according to the above adaptive method, with the minimum error and optimize the response, update the step size Choose based on system processing capability: , , in, express The proportional gain at time, express The proportional gain at time, express The differential gain at time, express The differential gain at time.

[0086] In this embodiment, the present application has the following beneficial effects: 1. Efficient and accurate real-time positioning.

[0087] This embodiment provides more accurate real-time positioning capabilities than traditional technologies by combining UWB data obtained by UWB (ultra-wideband) positioning technology with laser radar data. This is particularly critical in complex environments such as confined spaces such as mine tunnels, and can significantly improve the accuracy and reliability of navigation.

[0088] 2. Simplified environmental perception and driving direction determination.

[0089] By using a polar coordinate system to determine the direction of travel, this embodiment simplifies the traditional complex map matching and environment perception process. This method reduces the reliance on high-performance processing hardware, reduces the overall cost of the system, and speeds up the decision-making process.

[0090] 3. Dynamic obstacle avoidance and safety enhancement.

[0091] The method of this embodiment can calculate and update the trajectory in real time to cope with dynamic obstacles and changing environmental conditions. The safety margin correction mechanism further ensures the safety of the device during driving and reduces the risk of collision and accidents.

[0092] 4. Low-cost deployment and high adaptability.

[0093] The use of a minimalist SLAM algorithm has greatly reduced the complexity and deployment cost of the unmanned driving system. As the cost of UWB equipment gradually decreases, the economic benefits of this unmanned driving system are more significant and suitable for a wide range of industrial scenarios, especially in mining areas with limited resources.

[0094] 5. Enhanced control output simplifies operation.

[0095] By simplifying the complex control process into an intuitive output of travel direction and steering angle, the present embodiment improves the convenience and efficiency of operation. This intuitive control mechanism enables the operator to easily control the unmanned device 107 even in extreme environments.

[0096] 6. Safety and driving stability.

[0097] This embodiment pays special attention to safe driving in confined spaces, and ensures safe operation of the vehicle in narrow environments by real-time monitoring of the vehicle's outline and safety boundaries. Dynamic obstacle avoidance and path correction functions further enhance the safety of the system, and can effectively avoid collisions and other safety accidents. Compared with traditional technologies, this embodiment provides higher safety guarantees.

[0098] In summary, this embodiment significantly improves the navigation and control capabilities of the unmanned driving system in complex and restricted environments through a simplified SLAM algorithm, precise UWB positioning, dynamic path planning and obstacle avoidance technology. Compared with the existing technology, this embodiment has multiple advantages such as high efficiency, low storage, high precision, safety and reliability, and easy deployment, and has important application value and broad market prospects.

[0099] The minimalist SLAM algorithm for unmanned driving in confined space conditions of this embodiment is particularly suitable for complex and narrow environments such as underground mines. This method provides an efficient navigation solution for various types of articulated equipment such as articulated transport vehicles. These application scenarios are usually characterized by harsh environments, large space restrictions, and extremely high requirements for the accuracy and reliability of the machine navigation system. This method ensures that unmanned equipment can perform tasks safely and effectively by providing accurate environmental perception and real-time navigation updates.

[0100] The minimalist SLAM method for unmanned driving in confined space conditions solves multiple problems of unmanned driving equipment navigation in confined spaces, including low environmental perception accuracy, poor navigation reliability, and high implementation costs. This system integrates efficient sensors such as lidar and millimeter-wave radar to achieve high-precision measurement and analysis of complex environments, and effectively identify and avoid obstacles. At the same time, the use of advanced data fusion processing and polar coordinate path planning algorithms enhances the stability and response speed of navigation and reduces dependence on external conditions (such as temperature and dust). In addition, the system design focuses on cost control, so that it can reduce the economic burden of technology implementation while maintaining high efficiency.

[0101] Reference Figure 5 The embodiment of the present application also provides an unmanned driving system in a confined space, the system includes a path planning unit 100, a data acquisition unit 200, a position coordinate determination unit 300, a driving direction determination unit 400, a safety boundary determination unit 500, a correction angle determination unit 600 and a data calculation unit 700, wherein: A path planning unit 100 is used to perform path planning through pre-marked UWB trajectory point coordinates 104 to determine a target planning path; The data acquisition unit 200 is used to acquire UWB position data and laser radar data of the unmanned driving device 107 traveling on the target planning path; A position coordinate determination unit 300, for determining the current position coordinates of the unmanned driving device 107 according to the UWB position data and the laser radar data; A driving direction determination unit 400, for determining a polar coordinate solution angle 102 according to the current position coordinates; A safety boundary determination unit 500, configured to determine two safety boundaries 103 based on the laser radar data; A correction angle determination unit 600, configured to determine a safety boundary correction angle 101 according to two safety boundaries 103; The data calculation unit 700 is used to calculate the target control angle and the target control angular velocity based on the polar coordinate solution angle 102 and the safety margin correction angle 101.

[0102] It should be noted that since the unmanned driving system in a confined space in this embodiment and the unmanned driving method in a confined space mentioned above are based on the same inventive concept, the corresponding contents in the method embodiment are also applicable to the system embodiment and will not be described in detail here.

[0103] An embodiment of the present application also provides an electronic device, comprising: at least one control processor and a memory for communicating with the at least one control processor.

[0104] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0105] The non-transient software program and instructions required to implement the unmanned driving method in a confined space of the above embodiment are stored in the memory. When executed by the processor, the unmanned driving method in a confined space of the above embodiment is executed, for example, the above described Figure 1 The method comprises steps S100 to S700.

[0106] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] The present application also provides a computer-readable storage medium storing computer-executable instructions, which are executed by one or more control processors to enable the one or more control processors to execute an unmanned driving method in a confined space in the above method embodiment, for example, to execute the above described Figure 1 The functions of method steps S100 to S700 in the method.

[0108] It will be appreciated by those skilled in the art that all or some of the steps and systems in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0109] The above is a specific description of the preferred implementation of the embodiments of the present application, but the embodiments of the present application are not limited to the above-mentioned implementation methods. Technical personnel familiar with the field can also make various equivalent modifications or substitutions without violating the spirit of the embodiments of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the embodiments of the present application.

Claims

1. An unmanned driving method in a confined space, characterized in that: The method comprises: Path planning is performed through the coordinates of pre-marked UWB trajectory points to determine the target planning path; Acquire UWB position data and LiDAR data of the unmanned driving device traveling on the target planning path; Determine the current position coordinates of the unmanned driving device according to the UWB position data and the laser radar data; Determine a polar coordinate solution angle according to the current position coordinates; Based on the laser radar data, two safety boundaries are determined; Determining a safety boundary correction angle according to the two safety boundaries; Based on the polar coordinate solution angle and the safety margin correction angle, a target control angle and a target control angular velocity are calculated.

2. The unmanned driving method in a confined space according to claim 1, characterized in that: The method of performing path planning by using the pre-marked UWB trajectory point coordinates to determine the target planning path includes: Obtaining the coordinates of the pre-marked UWB trajectory points, and calculating the measured distance and the actual distance between every two adjacent pre-marked UWB trajectory point coordinates, wherein the measured distance is the distance obtained by the UWB method, and the actual distance is the distance obtained by the actual measurement; Calculating an error between the measured distance and the actual distance; Performing path planning according to the abscissa of the pre-marked UWB trajectory point coordinates to obtain a plurality of planned paths; Based on the error, calculating the total error corresponding to the coordinates of all pre-marked UWB trajectory points in each planned path; The planned path corresponding to the minimum total error is selected as the target planning path.

3. The unmanned driving method in a confined space according to claim 1, characterized in that: Determining the current position coordinates of the unmanned driving device according to the UWB position data and the laser radar data includes: Fusing the UWB position data and the laser radar data to obtain fused data; The current position coordinates of the unmanned driving device are determined based on the fused data.

4. The unmanned driving method in a confined space according to claim 1, characterized in that: Determining the polar coordinate solution angle according to the current position coordinates includes: Obtaining the target driving trajectory point coordinates corresponding to the current position coordinates from the target planned path; Convert the target driving trajectory point coordinates into a polar coordinate system trajectory direction; The angle formed by the trajectory direction of the polar coordinate system and the center line of the unmanned driving device is used as the polar coordinate solution angle.

5. The unmanned driving method in a confined space according to claim 1, characterized in that: Determining two safety boundaries based on the laser radar data includes: The laser radar data is input into the SLAM algorithm to obtain two safety boundaries.

6. The unmanned driving method in a confined space according to claim 1, characterized in that: The step of determining the safety boundary correction angle according to the two safety boundaries includes: confirming a middle line between the two safety boundaries; The angle between the middle line and the center line of the unmanned driving device is used as the safety boundary correction angle.

7. The unmanned driving method in a confined space according to claim 1, characterized in that: The calculating the target control angle and the target control angular velocity based on the polar coordinate solution angle and the safety margin correction angle includes: Calculating a safety margin correction angle difference between the safety margin correction angle and the polar coordinate solution angle; Calculating a target control angle according to the safety margin correction angle difference and the polar coordinate solution angle; According to the target control angle, a target control angular velocity is determined.

8. An unmanned driving system in a confined space, characterized in that: The system comprises: A path planning unit is used to perform path planning through the coordinates of pre-marked UWB trajectory points to determine the target planning path; A data acquisition unit, used to acquire UWB position data and laser radar data of an unmanned driving device traveling on the target planning path; A position coordinate determination unit, used to determine the current position coordinates of the unmanned driving device according to the UWB position data and the laser radar data; A driving direction determination unit, used to determine a polar coordinate solution angle according to the current position coordinates; A safety boundary determination unit, configured to determine two safety boundaries based on the laser radar data; A correction angle determination unit, used to determine a safety boundary correction angle according to the two safety boundaries; A data calculation unit is used to calculate a target control angle and a target control angular velocity based on the polar coordinate solution angle and the safety margin correction angle.

9. An electronic device, characterized in that: It includes at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the unmanned driving method in a confined space as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the unmanned driving method in a confined space as described in any one of claims 1 to 7.

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