An unmanned driving method, system, electronic device and medium under a restricted space

Abstract

The present application discloses an unmanned driving method, system, electronic device and medium under a confined space. The method includes performing path planning through pre-marked UWB trajectory point coordinates to determine a target planned path; obtaining UWB position data and lidar data of an unmanned driving device traveling on the target planned path; determining the current position coordinates of the unmanned driving device according to the UWB position data and the lidar data; determining a polar coordinate solution angle according to the current position coordinates; determining two safety boundaries based on the lidar data; determining a safety boundary correction angle according to the two safety boundaries; and calculating a target control angle and a target control angular velocity based on the polar coordinate solution angle and the safety boundary correction angle. The present application can meet the efficient operation under an underground narrow space.

Description

Technical Field

[0001] This application relates to the field of driverless technology, and in particular, to a driverless method, system, electronic device, and medium in a restricted space. Background Art

[0002] With the increasing global demand for mineral resources, many shallow ore body resources have been gradually exhausted, leading to the gradual shift of mining operations to deep underground ore bodies. The harsh working environment in underground mines has resulted in a shortage of frontline workers, forcing mining enterprises to seek safer and more economical solutions. Therefore, the transformation towards a "less manned automated and unmanned intelligent" mining development model has become an inevitable trend in the technological progress of underground mines.

[0003] In the field of underground mine transportation, articulated driverless equipment has become a very suitable device for operating in narrow underground spaces due to its small turning radius and strong mobility. However, articulated driverless equipment faces unique challenges in achieving driverless operation. Due to its complex steering characteristics and the narrow and variable underground roadway environment, the application effects of conventional Simultaneous Localization and Mapping (SLAM) algorithms and image recognition technologies are limited in such environments, and the R & D and implementation costs are high. These technologies often make it difficult for articulated driverless equipment to adapt to the special underground environment of darkness, narrowness, and full of various obstacles. Therefore, articulated driverless equipment is difficult to meet the efficient operation in narrow underground spaces. Summary of the Invention

[0004] This application aims to propose a driverless method, system, electronic device, and medium in a restricted space, which can meet the efficient operation in narrow underground spaces.

[0005] In a first aspect, an embodiment of this application provides a driverless method in a restricted space, and the method includes:

[0006] Perform path planning through pre-marked UWB trajectory point coordinates to determine a target planned path;

[0007] Obtain UWB position data and lidar data of a driverless device traveling on the target planned path;

[0008] Determine the current position coordinates of the driverless device according to the UWB position data and lidar data;

[0009] Determine a polar coordinate solution angle according to the current position coordinates;

[0010] Determine two safety boundaries based on the lidar data;

[0011] Determine a safety boundary correction angle according to the two safety boundaries;

[0012] Calculate a target control angle and a target control angular velocity based on the polar coordinate calculation angle and the safety boundary correction angle.

[0013] Compared with the prior art, the first aspect of the present application has the following beneficial effects:

[0014] This method performs path planning through pre-marked UWB trajectory point coordinates to determine a target planned path, enabling the unmanned device to travel on the optimal path as much as possible; obtaining UWB position data and lidar data of the unmanned device traveling on the target planned path, determining the current position coordinates of the unmanned device according to the UWB position data and the lidar data, and determining the current position coordinates of the unmanned device according to multiple data can improve the accuracy of the obtained current position coordinates; determining a polar coordinate calculation angle according to the current position coordinates, determining two safety boundaries based on the lidar data, determining a safety boundary correction angle according to the two safety boundaries, and calculating a target control angle and a target control angular velocity based on the polar coordinate calculation angle and the safety boundary correction angle, enabling the unmanned device to travel safely and meet the efficient operation in narrow underground spaces.

[0015] In some embodiments, the performing path planning through pre-marked UWB trajectory point coordinates to determine a target planned path includes:

[0016] Obtain pre-marked UWB trajectory point coordinates, and calculate the measured distance and the actual distance between every two adjacent pre-marked UWB trajectory point coordinates, where the measured distance is the distance obtained by the UWB method, and the actual distance is the distance obtained by actual measurement;

[0017] Calculate the error between the measured distance and the actual distance;

[0018] Perform path planning according to the abscissas of the pre-marked UWB trajectory point coordinates to obtain multiple planned paths;

[0019] Calculate the total error corresponding to all pre-marked UWB trajectory point coordinates in each planned path according to the error;

[0020] Select the planned path corresponding to the minimum total error as the target planned path.

[0021] In some embodiments, the determining the current position coordinates of the unmanned device according to the UWB position data and the lidar data includes:

[0022] Fuse the UWB position data and the lidar data to obtain the fused data;

[0023] Determine the current position coordinates of the driverless device according to the fused data.

[0024] In some embodiments, the determining the polar coordinate solution angle according to the current position coordinates includes:

[0025] Obtain the target driving trajectory point coordinates corresponding to the current position coordinates from the target planned path;

[0026] Convert the target driving trajectory point coordinates into the trajectory direction in the polar coordinate system;

[0027] Use the included angle formed by the trajectory direction in the polar coordinate system and the midline of the driverless device as the polar coordinate solution angle.

[0028] In some embodiments, the determining two safety boundaries based on the lidar data includes:

[0029] Input the lidar data into the SLAM algorithm to obtain two safety boundaries.

[0030] In some embodiments, the determining the safety boundary correction angle according to the two safety boundaries includes:

[0031] Confirm the intermediate line between the two safety boundaries;

[0032] Use the included angle between the intermediate line and the midline of the driverless device as the safety boundary correction angle.

[0033] 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 boundary correction angle includes:

[0034] Calculate the safety boundary correction angle difference between the safety boundary correction angle and the polar coordinate solution angle;

[0035] Calculate the target control angle according to the safety boundary correction angle difference and the polar coordinate solution angle;

[0036] Determine the target control angular velocity according to the target control angle.

[0037] In a second aspect, an embodiment of the present application further provides a driverless system in a confined space, and the system includes:

[0038] A path planning unit, configured to perform path planning through pre-marked UWB trajectory point coordinates to determine a target planned path;

[0039] A data acquisition unit, configured to acquire UWB position data and lidar data of an unmanned device traveling on the target planned path;

[0040] A position coordinate determination unit, configured to determine the current position coordinates of the unmanned device according to the UWB position data and the lidar data;

[0041] A traveling direction determination unit, configured to determine a polar coordinate solution angle according to the current position coordinates;

[0042] A safety boundary determination unit, configured to determine two safety boundaries based on the lidar data;

[0043] A correction angle determination unit, configured to determine a safety boundary correction angle according to the two safety boundaries;

[0044] A data calculation unit, configured to calculate a target control angle and a target control angular velocity based on the polar coordinate solution angle and the safety boundary correction angle.

[0045] In a third aspect, an embodiment of the present application further provides an electronic device, including at least one control processor and a memory communicatively connected to the at least one control processor; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor to enable the at least one control processor to execute an unmanned driving method in a restricted space as described above.

[0046] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores computer-executable instructions for causing a computer to execute an unmanned driving method in a restricted space as described above.

[0047] It can be understood that the beneficial effects of the above second aspect to the fourth aspect compared with the related art are the same as those of the first aspect compared with the related art. For details, please refer to the relevant descriptions in the first aspect, and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and / or additional aspects and advantages of the present application will become apparent and easy to understand from the following description of the embodiments in conjunction with the accompanying drawings, where:

[0049] Figure 1 is a flowchart of an embodiment of an unmanned driving method in a restricted space provided by the present application;

[0050] Figure 2 is a flowchart of the best embodiment of an unmanned driving method in a restricted space provided by the present application;

[0051] Figure 3 It is a schematic diagram of path planning in the best embodiment of the driverless method under a restricted space provided by this application;

[0052] Figure 4 It is a schematic diagram of local restricted space polar coordinate pose correction in the best embodiment of the driverless method under a restricted space provided by this application;

[0053] Figure 5 It is a schematic structural diagram of an embodiment of the driverless system under a restricted space provided by this application;

[0054] Label description:

[0055] 101. Safety boundary correction angle; 102. Polar coordinate calculation angle; 103. Two safety boundaries; 104. Coordinates of pre-marked UWB trajectory points; 105. Intermediate line; 106. Current driving direction; 107. Driverless device; 108. Polar coordinate system trajectory line. Detailed implementation manners

[0056] The embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for explaining the present application and should not be construed as limiting the present application.

[0057] In the description of the present application, if the first, second, etc. are described only for the purpose of distinguishing technical features, they should not be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0058] In the description of the present application, it should be understood that for the orientation description, such as up, down, etc., the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying 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 construed as limiting the present application.

[0059] In the description of the present application, it should be noted that unless otherwise clearly defined, words such as setting, installing, connecting, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present application in combination with the specific content of the technical solution.

[0060] In the field of underground mine transportation, articulated driverless equipment has become a very suitable device for operating in narrow underground spaces due to its small turning radius and strong mobility. However, articulated driverless equipment faces unique challenges in achieving driverless operation. Due to its complex steering characteristics and the narrow and variable underground roadway environment, the application effects of conventional SLAM (Simultaneous Localization and Mapping) and image recognition technologies are limited in such environments, and the R & D and implementation costs are high. These technologies often make it difficult for articulated driverless equipment to adapt to the special underground environment of dimness, narrowness and full of various obstacles. Therefore, articulated driverless equipment is difficult to meet the efficient operation in narrow underground spaces.

[0061] To solve the problem that the articulated driverless equipment mentioned above is difficult to meet the efficient operation in narrow underground spaces, this application proposes a driverless method, system, electronic device and medium in a restricted space.

[0062] Refer to Figure 1 , an embodiment of this application provides a driverless method in a restricted space. This method includes the following steps:

[0063] Step S100: Perform path planning through the pre-marked UWB trajectory point coordinates 104 to determine the target planned path;

[0064] Step S200: Obtain the UWB position data and lidar data of the driverless device 107 traveling on the target planned path;

[0065] Step S300: Determine the current position coordinates of the driverless device 107 according to the UWB position data and lidar data;

[0066] Step S400: Determine the polar coordinate solution angle 102 according to the current position coordinates;

[0067] Step S500: Determine two safety boundaries 103 based on the lidar data;

[0068] Step S600: Determine the safety boundary correction angle 101 according to the two safety boundaries 103;

[0069] Step S700: Calculate the target control angle and target control angular velocity based on the polar coordinate solution angle 102 and the safety boundary correction angle 101.

[0070] In this embodiment, path planning is performed based on the pre-marked UWB trajectory point coordinates 104 to determine the target planned path, enabling the unmanned device 107 to travel on the optimal path as much as possible; the UWB position data and lidar data of the unmanned device 107 traveling on the target planned path are obtained, and based on the UWB position data and lidar data, the current position coordinates of the unmanned device 107 are determined. Determining the current position coordinates of the unmanned device 107 based on multiple types of data can improve the accuracy of the obtained current position coordinates; based on the current position coordinates, the polar coordinate solution angle 102 is determined, and based on the lidar data, two safety boundaries 103 are determined. 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 target control angular velocity are calculated, enabling the unmanned device 107 to not only travel safely but also meet the efficient operation requirements in narrow underground spaces.

[0071] The above-mentioned pre-marked UWB trajectory point coordinates 104 can be pre-set UWB marks, and the UWB trajectory point coordinates can be obtained using UWB technology.

[0072] The above-mentioned UWB technology is ultra-wideband technology, which is a wireless carrier communication technology. It does not use a sine carrier but uses nanosecond-level non-sine wave narrow pulses to transmit data, so the occupied spectrum range is very wide.

[0073] The above-mentioned path planning based on the pre-marked UWB trajectory point coordinates 104 to determine the target planned path can be to obtain the target planned path according to the pre-marked UWB trajectory point coordinates 104 using a trajectory point planning algorithm and a route matching algorithm. It can also be to obtain the target planned path using an existing path planning method.

[0074] The above-mentioned obtaining of the UWB position data and lidar data of the unmanned device 107 traveling on the target planned path can be to install a UWB identification card and a lidar on the unmanned device 107 traveling on the target planned path, and obtain the UWB position data and lidar data of the unmanned device 107 through the UWB identification card and the lidar.

[0075] The above-mentioned determining of the current position coordinates of the unmanned device 107 based on the UWB position data and lidar data can be to use the SLAM algorithm to determine the current position coordinates of the unmanned device 107 based on the UWB position data and lidar data. It can also be to first fuse the UWB position data and lidar data using the Kalman filtering method and then determine the current position coordinates of the unmanned device 107.

[0076] The above lidar data may include data such as surrounding environment data and the current position of the more precise driverless device 107.

[0077] The above-mentioned determination of the polar coordinate solution angle 102 based on the current position coordinates may be to determine the driving target position coordinates according to the current position coordinates, and then according to the current position coordinates and the driving target position coordinates, the polar coordinate solution angle 102 can be determined.

[0078] The above-mentioned determination of the two safety boundaries 103 based on the lidar data may be to input the lidar data into the SLAM algorithm, and obtain the two safety boundaries 103 through the safety obstacle avoidance calculation in the SLAM algorithm. For example, the current position of the driverless device is obtained through the lidar data, and then the two relatively safe safety boundary lines on both sides of the current position are calculated through the safety obstacle avoidance in the SLAM algorithm. These two safety boundary lines have a certain distance from both sides of the road.

[0079] In some embodiments, path planning is performed through the pre-marked UWB trajectory point coordinates 104 to determine the target planned path, including:

[0080] Obtain the pre-marked UWB trajectory point coordinates 104, and calculate the measured distance and the actual distance between every two adjacent pre-marked UWB trajectory point coordinates 104, where the measured distance is the distance measured by the UWB method, and the actual distance is the actually measured distance;

[0081] Calculate the error between the measured distance and the actual distance;

[0082] Perform path planning according to the abscissa of the pre-marked UWB trajectory point coordinates 104 to obtain multiple planned paths;

[0083] According to the error, calculate the total error corresponding to all the pre-marked UWB trajectory point coordinates 104 in each planned path;

[0084] Select the planned path corresponding to the minimum total error as the target planned path.

[0085] In this embodiment, by calculating the total error corresponding to all the pre-marked UWB trajectory point coordinates 104 in each planned path according to 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 driverless device 107.

[0086] In some embodiments, determining the current position coordinates of the driverless device 107 according to the UWB position data and the lidar data includes:

[0087] Fuse the UWB position data and the lidar data to obtain the fused data;

[0088] Determine the current position coordinates of the driverless device 107 according to the fused data.

[0089] In this embodiment, fusing the UWB position data and the lidar data to obtain the fused data, and then determining the current position coordinates of the driverless device 107 according to the fused data can make the obtained current position coordinates of the driverless device 107 more accurate.

[0090] In some embodiments, determining the polar coordinate solution angle 102 according to the current position coordinates includes:

[0091] Obtain the target driving trajectory point coordinates corresponding to the current position coordinates from the target planned path;

[0092] Convert the target driving trajectory point coordinates into the trajectory direction in the polar coordinate system;

[0093] Take the included angle formed by the trajectory direction in the polar coordinate system and the midline of the driverless device 107 as the polar coordinate solution angle 102.

[0094] In this embodiment, obtaining the target driving trajectory point coordinates corresponding to the current position coordinates from the target planned path, converting the target driving trajectory point coordinates into the trajectory direction in the polar coordinate system, and then taking the included angle formed by the trajectory direction in the polar coordinate system and the midline of the driverless device 107 as the polar coordinate solution angle 102 can make the driverless device 107 continuously approach the target driving trajectory point, enable the driverless device 107 to travel in the target planned path as much as possible, and improve the efficient operation of the driverless device 107.

[0095] In some embodiments, determining two safety boundaries 103 based on the lidar data includes:

[0096] Input the lidar data into the SLAM algorithm to obtain two safety boundaries 103.

[0097] In this embodiment, by inputting the lidar data into the SLAM algorithm to obtain two safety boundaries 103, the driving safety of the driverless device 107 can be ensured.

[0098] In some embodiments, determining the safety boundary correction angle 101 according to the two safety boundaries 103 includes:

[0099] Confirm the intermediate line 105 between the two safety boundaries 103;

[0100] Take the included angle between the intermediate line 105 and the midline of the driverless device 107 as the safety boundary correction angle 101.

[0101] In this embodiment, the angle between the intermediate line 105 and the center line of the driverless device 107 is used as the safety boundary correction angle 101, which can ensure the driving safety of the driverless device 107.

[0102] In some embodiments, based on the polar coordinate solution angle 102 and the safety boundary correction angle 101, calculating the target control angle and the target control angular velocity includes:

[0103] Calculating the degree difference of the safety boundary correction angle 101 between the safety boundary correction angle 101 and the polar coordinate solution angle 102;

[0104] Calculating the target control angle according to the degree difference of the safety boundary correction angle 101 and the polar coordinate solution angle 102;

[0105] Determining the target control angular velocity according to the target control angle.

[0106] In this embodiment, calculating the degree difference of the safety boundary correction angle 101 between the safety boundary correction angle 101 and the polar coordinate solution angle 102, then calculating the target control angle according to the degree difference of the safety boundary correction angle 101 and the polar coordinate solution angle 102, and determining the target control angular velocity according to the target control angle. By simplifying the complex control process into an intuitive output of the traveling direction and the steering angle, it can ensure the driving safety of the driverless device 107 while enabling the driverless device 107 to travel in the target direction, enabling the driverless device 107 to travel in the target planned path as much as possible, and improving the convenience and efficiency of the operation.

[0107] For the convenience of those skilled in the art to understand, the following provides a set of best embodiments:

[0108] Refer to Figure 2 , Figure 2 In, the discrimination of the two-dimensional map direction of the device refers to the discrimination of the traveling direction obtained through coordinate conversion. This process usually involves comparing the current traveling direction of the driverless device 107 and the target direction obtained through polar coordinate conversion. If the two are the same, the driverless device 107 is in the forward driving state; if they are different, the driverless device 107 may be in the reverse driving state. This embodiment proposes a driverless method for restricted space conditions, which is specifically designed to improve the navigation accuracy and operation efficiency of articulated driverless 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 driverless equipment in mine roadways and significantly reduces the implementation and deployment costs of mine driverless by integrating advanced environmental perception, precise path planning, and dynamic control technologies. The specific contents are as follows:

[0109] 1. Description of the source of SLAM in the solution of this embodiment.

[0110] (1) SLAM includes instant positioning.

[0111] In this embodiment, combined with the UWB precise positioning system and the production scheduling system, the expected trajectory points of the unmanned equipment are planned to generate a plane minimalist map. The UWB precise positioning system provides real-time position feedback to achieve the instant positioning function within the operation area, thus ensuring the accurate navigation of the unmanned equipment.

[0112] (2) SLAM includes real-time mapping and pose correction.

[0113] By using the collaborative work of lidar and UWB, this embodiment simplifies the traditional map matching method, uses UWB for instant positioning and corrects the position of the equipment in the restricted space. This process provides the real-time position and attitude information of the equipment in the restricted space, without relying on complex map construction, ensuring high-precision environmental perception and fast response.

[0114] (3) SLAM includes azimuth and trajectory planning.

[0115] In this embodiment, aiming at the safety anti-collision requirements in the restricted space, the pose planning in the plane Cartesian coordinate system is transformed into the direction planning described in the polar coordinate system. Through the lidar and UWB data, the vector direction and steering amplitude are accurately calculated, where the boundary angle of the restricted space is used as a passive factor, and the driving direction is used as an active factor to ensure that the unmanned equipment always drives towards the correct target direction.

[0116] 2. Independence and minimalist features of data sources.

[0117] (1) Lidar data: Used for preliminary environmental perception and position correction.

[0118] (2) UWB data: Provides accurate position information and minimalist trajectory points for real-time positioning and path constraint, simplifying map creation.

[0119] (3) Polar coordinate data: Extracts position coordinates from lidar and UWB data and then transforms them into polar coordinates for path planning and direction determination.

[0120] The data sources are independent and complementary. By combining UWB data with lidar data, an efficient and accurate SLAM function is achieved. UWB data provides basic positioning, and lidar data is used for detail correction to ensure the efficient operation of the system in the restricted space.

[0121] 3. Feature of low storage rate of operation data.

[0122] (1)Data storage optimization: Utilize the minimal trajectory points provided by UWB to reduce the storage requirements for large-scale map data. Only store key trajectory points and necessary location information, significantly reducing the data storage volume.

[0123] (2)Real-time processing: The 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.

[0124] 4. Constraint characteristics of contour safety control and path planning for unmanned equipment in restricted spaces.

[0125] (1)Contour safety control: Based on the output results of SLAM, rectify the driving direction and position of the equipment in real time to ensure safe operation in restricted spaces. Utilize lidar data and UWB data to accurately perceive environmental boundaries and obstacles, achieving dynamic obstacle avoidance and path correction.

[0126] (2)Path planning constraints: In restricted spaces, use the polar coordinate system for local path planning, combined with the actual contour and boundary information of the equipment for effective constraints. When the minimalist SLAM algorithm (i.e., the unmanned driving method in restricted spaces in this embodiment) conducts path planning, it gives priority to safety and driving efficiency, and ensures the efficient operation of the equipment in complex environments by dynamically adjusting the driving path.

[0127] In summary, the minimalist SLAM algorithm for unmanned driving under restricted space conditions makes full use of lidar data and UWB data, describes path planning through the polar coordinate system, and realizes 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.

[0128] The specific technical solution of this embodiment includes the following step process:

[0129] Step S1: Production task path planning.

[0130] When the unmanned system starts, first, based on the actual production task, the actual equipment operation route is issued through the production scheduling system, as shown in Figure 3 This route (i.e., the path) is planned using the trajectory point coordinates pre-marked by UWB (i.e., the pre-marked UWB trajectory point coordinates 104), where the trajectory point coordinates are measured as To reduce the UWB positioning error, the UWB positioning error model is adopted as , represents the error, represents the actually measured trajectory point coordinates, which can be the distance obtained by actual human measurement, Represents the pre-set UWB trajectory point coordinates and the distances measured by the UWB method. The trajectory point planning algorithm is used for , where , is the weight obtained based on minimizing the variance, and the semi-variance function is used to evaluate the correlation of spatial data. The path matching algorithm is , ensuring that the task path sequence has the uniqueness of the production plan. The task trajectory point coordinates and the UWB markers involved in this embodiment provide initial navigation data when deployed, establishing a reference point for the real-time position monitoring in step S2.

[0131] Step S2: Real-time position feedback.

[0132] The position of the equipment is real-time monitored by the UWB identification card and lidar installed on the equipment, and the position data is transmitted to the edge calculator through the underground wireless network. The Kalman filtering method or other existing methods capable of data fusion in the edge calculator are used to fuse the UWB data and lidar data, and the real-time position coordinate data of the driverless equipment is updated according to 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.

[0133] Step S3: Determination of the driving direction.

[0134] According to the real-time position coordinate data provided in step S2 (i.e., the current position coordinates), the current required driving direction in the edge calculator involved in this embodiment is obtained from the UWB positioning system during the equipment's movement and the UWB solution result calculated by the edge calculation, and the target traveling direction in the two-dimensional Cartesian coordinate system (i.e., the target driving trajectory point coordinates) is converted into the trajectory direction in the polar coordinate system required for the current position of the equipment. The polar coordinate conversion formula is , and the polar coordinate trajectory line 108 can refer to Figure 4 . By forming a polar coordinate solution angle 102 between the trajectory direction in the polar coordinate system calculated in real-time and the midline of the driverless equipment, the trajectory target algorithm can effectively guide the equipment towards the angle target path point of the next trajectory. The trajectory target algorithm is , represents the angle corresponding to the current position coordinates (i.e., the current driving direction 106), represents the desired path (i.e., the trajectory direction in the polar coordinate system corresponding to the target driving trajectory point coordinates), Q and R represent the weight factors, represents the initial moment, represents the next moment. According to the polar coordinate solution angle 102 and the angle corresponding to the current position coordinates, the driving direction of the driverless device 107 is calculated. The driving direction calculation is through the formula: , where Represents the angle adjusted according to real-time data (i.e., the polar coordinate solution angle 102), which represents the target driving direction of the driverless device 107.

[0135] Step S4: Safety boundary correction.

[0136] Referring to Figure 4 , this embodiment involves the safety boundary correction angle 101 formed by the roadway center line (i.e., the middle line 105) formed by the safety control lines of the driverless equipment profile (i.e., the two safety boundaries 103) and the center line of the actual orientation of the equipment. The safety boundary correction angle 101 is calculated as: , where represents the coordinates on the roadway center line, represents the current position coordinates, represents the angle adjustment required for safety boundary correction, which is fed back as a correction amount. By comparing the preset trajectory and the trajectory calculated in real time, based on the polar coordinate solution angle 102 and the safety boundary correction angle 101 in step S3 being mutually feedback, the angle and angular velocity of the equipment control output are formed, and the equipment dynamically adjusts the driving angle and speed to adapt to the roadway profile and maintain a safe distance. The specific calculation methods of the angle and angular velocity are as follows:

[0137] (1) Combining the polar coordinate solution angle 102 and the safety boundary correction angle 101, calculate the final control output angle through the following formula:

[0138] ,

[0139] where represents the final control output angle, represents the safety boundary correction factor, represents the degree difference of the safety boundary correction angle 101 between the safety boundary correction angle 101 and the polar coordinate solution angle 102.

[0140] (2) Use a first-order dynamic response model to determine the angular velocity as:

[0141] ,

[0142] where represents the proportional control gain, represents the angular velocity.

[0143] To ensure the stability and responsiveness of the system, closed-loop feedback control is used to dynamically adjust and , specifically:

[0144] ,

[0145] where represents The proportional control gain at a moment denotes the proportional control gain at a moment and denotes the adjustment coefficient denotes the error between the target position and the actual position, that is , denotes the safety margin correction factor at a moment denotes the safety margin correction factor at a moment

[0146] The output of step S4 directly affects the generation of the control instruction in step S5

[0147] Step S5: Simplify the control output

[0148] Integrate the analysis results of the content of the foregoing steps S1, S2, S3, and S4 in this embodiment to simplify the output of the control instruction. The control output formula can be used as follows , where , and respectively denote the proportional gain, integral gain, and derivative gain, and directly convert the unmanned control output of the confined space equipment into the travel direction output, steering angle, and angular velocity output under the UWB guidance condition, greatly simplifying the unmanned control process of the equipment, thereby improving the simplicity and execution efficiency of the operation. The steering angle and angular velocity output methods include the following

[0149] (1) Steering angle calculation

[0150] Define the target direction angle and the current direction angle , and the steering angle difference is :[[]] . If exceeds 180°, it is adjusted to (the corresponding positive value adjustment) to ensure the shortest rotation distance, where .

[0151] (2) Angular velocity output

[0152] Use a proportional-derivative controller (PD controller) to calculate the angular velocity as

[0153] ,

[0154] where and respectively denote the proportional gain and derivative gain, which are used to adjust the response speed and stability It represents the rate of change of the angular difference and is calculated in real time.

[0155] (3) Angular velocity smoothing and limitation.

[0156] To prevent damage to the mechanical system caused by sudden changes in angular velocity, a limiting function is introduced to smooth the angular velocity as:

[0157] ,

[0158] where, represents the preset maximum angular velocity.

[0159] (4) Real-time dynamic adjustment.

[0160] The adaptive rule is used to adjust and based on the system performance index error and the error rate of change :

[0161] ,

[0162] ,

[0163] where, and represent positive adaptation rate parameters to determine the speed and response of parameter adjustment, represents the derivative of , represents the derivative of .

[0164] The parameter update mechanism and are updated in real time according to the above adaptation to minimize the error and optimize the response. The update step size is selected according to the system processing capacity:

[0165] ,

[0166] ,

[0167] where, represents the proportional gain at time, represents the proportional gain at time, represents the derivative gain at time, represents the derivative gain at time.

[0168] In this embodiment, the present application has the following beneficial effects:

[0169] 1. High-precision and efficient real-time positioning.

[0170] In this embodiment, by combining UWB (Ultra-Wideband) positioning data with lidar data, it provides more accurate real-time positioning capabilities than traditional technologies. This is particularly crucial in complex environments such as mine roadways in confined spaces, which can significantly improve the accuracy and reliability of navigation.

[0171] 2. Simplified environmental perception and determination of driving direction.

[0172] By using a polar coordinate system to determine the driving direction, this embodiment simplifies the traditional complex map matching and environmental perception processes. This method reduces the dependence on high-performance processing hardware, reduces the overall cost of the system, and accelerates the decision-making process.

[0173] 3. Dynamic obstacle avoidance and enhanced safety.

[0174] 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 boundary correction mechanism further ensures the safety of the device during driving, reducing the risk of collisions and accidents.

[0175] 4. Low-cost deployment and high adaptability.

[0176] The use of the minimalist SLAM algorithm significantly reduces the complexity and deployment cost of the unmanned driving system. Due to the gradually decreasing cost of UWB devices, the economic benefits of this unmanned driving system are more significant, and it is applicable to a wide range of industrial scenarios, especially in mining areas with limited resources.

[0177] 5. Enhanced control output simplifies operation.

[0178] By simplifying the complex control process into an intuitive output of the driving direction and steering angle, this 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.

[0179] 6. Safety and driving stability.

[0180] This embodiment particularly focuses on safe driving in confined spaces. By real-time monitoring the vehicle profile and safety boundary, it ensures the safe operation of the vehicle in narrow environments. The dynamic obstacle avoidance and path correction functions further enhance the safety of the system, effectively avoiding collisions and other safety accidents. Compared with traditional technologies, this embodiment provides higher safety guarantees.

[0181] In summary, through the extremely simplified SLAM algorithm, precise UWB positioning, dynamic path planning, and obstacle avoidance technology, this embodiment significantly improves the navigation and control capabilities of the unmanned driving system in complex and restricted environments. Compared with the prior art, 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.

[0182] An extremely minimalist SLAM algorithm for unmanned driving under restricted space conditions in this embodiment is particularly suitable for complex and narrow environments such as underground mines. This method provides an efficient navigation solution for various articulated equipment such as articulated transport vehicles. These application scenarios are usually characterized by harsh environments, large space limitations, and extremely high requirements for the accuracy and reliability of the machine navigation system. By providing precise environmental perception and real-time navigation updates, this method ensures that unmanned equipment can perform tasks safely and effectively.

[0183] The extremely minimalist SLAM method for unmanned driving under restricted space conditions solves multiple problems in the navigation of unmanned equipment in restricted spaces, including low environmental perception accuracy, poor navigation reliability, and high implementation costs. This system integrates sensors such as high-efficiency lidar and millimeter-wave radar to achieve high-precision measurement and analysis of complex environments, effectively identify and avoid obstacles. At the same time, by adopting advanced data fusion processing and polar coordinate path planning algorithms, the stability and reaction speed of navigation are enhanced, and the dependence on external conditions (such as temperature and dust) is reduced. In addition, the system design focuses on cost control, which reduces the economic burden of technology implementation while maintaining high performance.

[0184] Refer to Figure 5 , this embodiment of the application also provides an unmanned driving system under restricted space. This 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, where:

[0185] The path planning unit 100 is used to perform path planning through the pre-marked UWB trajectory point coordinates 104 to determine the target planned path;

[0186] The data acquisition unit 200 is used to acquire the UWB position data and lidar data of the unmanned driving device 107 traveling on the target planned path;

[0187] The position coordinate determination unit 300 is used to determine the current position coordinates of the unmanned driving device 107 according to the UWB position data and lidar data;

[0188] The driving direction determination unit 400 is configured to determine the polar coordinate calculation angle 102 according to the current position coordinates;

[0189] The safety boundary determination unit 500 is configured to determine two safety boundaries 103 based on the lidar data;

[0190] The correction angle determination unit 600 is configured to determine the safety boundary correction angle 101 according to the two safety boundaries 103;

[0191] The data calculation unit 700 is configured to calculate the target control angle and the target control angular velocity based on the polar coordinate calculation angle 102 and the safety boundary correction angle 101.

[0192] It should be noted that since the driverless system in a restricted space in this embodiment and the above-mentioned driverless method in a restricted space are based on the same inventive concept, the corresponding content in the method embodiment is equally applicable to the system embodiment of the present application, and will not be elaborated here.

[0193] An embodiment of the present application also provides an electronic device, including: at least one control processor and a memory for communicatively connecting with the at least one control processor.

[0194] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely provided with respect to the processor, and these remote memories may be connected to the processor through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0195] The non-transitory software programs and instructions required to implement the driverless method in a restricted space of the above embodiment are stored in the memory, and when executed by the processor, execute the driverless method in a restricted space of the above embodiment. For example, execute the Figure 1 method steps S100 to step S700 described above.

[0196] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to 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.

[0197] The embodiments of the present application further provide a computer-readable storage medium storing computer-executable instructions, which are executed by one or more control processors, enabling the one or more control processors to execute an unmanned driving method in a confined space in the above method embodiments. For example, execute the functions of method steps S100 to S700 described above. Figure 1 The functions of steps S100 to S700 in the method described above.

[0198] Those of ordinary skill in the art can understand that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and their appropriate combinations. Some physical components or all physical components can 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 can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill 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 technologies, CD-ROM, digital versatile disk (DVD), or other optical disk storage, magnetic cassette, tape, magnetic disk storage, or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, a communication medium typically contains computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0199] The above is a specific description of the preferred embodiments of the present application, but the embodiments of the present application are not limited to the above embodiments. Those skilled in the art can make various equivalent deformations or substitutions without departing from the spirit of the embodiments of the present application, and these equivalent deformations or substitutions are all included within 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: The path planning is performed through the pre-marked UWB trajectory point coordinates to determine the target planning path, specifically: 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; Select the planned path corresponding to the minimum total error as the target planning path; Acquire UWB position data and LiDAR data of the unmanned driving device traveling on the target planning path; According to the UWB position data and the laser radar data, the current position coordinates of the unmanned driving device are determined, specifically: Fusing the UWB position data and the laser radar data to obtain fused data; Determining the current position coordinates of the unmanned driving device according to the fused data; According to the current position coordinates, the polar coordinate solution angle is determined, specifically: 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 a polar coordinate solution angle; 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: 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.

3. 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.

4. 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.

5. An unmanned driving system in a confined space, characterized in that: The system comprises: The path planning unit is used to plan the path through the pre-marked UWB trajectory point coordinates and determine the target planning path, specifically: 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; Select the planned path corresponding to the minimum total error as 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; The position coordinate determination unit is used to determine the current position coordinates of the unmanned driving device according to the UWB position data and the laser radar data, specifically: Fusing the UWB position data and the laser radar data to obtain fused data; Determining the current position coordinates of the unmanned driving device according to the fused data; The driving direction determination unit is used to determine the polar coordinate solution angle according to the current position coordinates, specifically: 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 a polar coordinate solution angle; 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.

6. 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 4.

7. 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 4.

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