Underground site modeling

Abstract

According to an example aspect of the present invention, there is provided a method comprising: receiving (410) a three-dimensional input model (24) of an underground tunnel system of a construction site (1), determining (420) an initial first position for a virtual probe (30) in the input model; determining (430) a distance between the first position and a tunnel wall based on the input model; determining (440) a tunnel orientation based on processing the determined distance; repositioning (450) the virtual probe at a second position in the input model with the determined tunnel orientation; and generating (460) a logical tunnel model (50) indicative of a path travelled by the virtual probe in the input model based on the determined position of the repositioned virtual probe in the input model.

Description

Technical Field

[0001] This invention relates to the modeling of underground construction sites. Background Technology

[0002] Underground construction sites, such as hard rock or soft rock mines, typically comprise various work areas accessible by different types of mobile work machinery (referred to herein as mobile vehicles). Underground mobile vehicles can be driverless, such as those remotely controlled from a control room, or manned mobile vehicles, operated by an operator seated in the driver's cab. Mobile vehicles operating on underground sites can be autonomous, i.e., automatic or semi-automatic mobile vehicles that operate independently in their normal operating mode without external control, but may be subject to external control in specific operating areas or under certain conditions, such as during emergencies. Many sites require location tracking of moving objects, such as mobile vehicles and personnel.

[0003] WO2015106799 discloses a system for scanning the environment surrounding a vehicle to generate data for determining the vehicle's position and orientation. The vehicle is equipped with mine reference point cloud data. A control unit is configured to match second point cloud data generated by the vehicle's scanning equipment with the reference point cloud data to determine the vehicle's position data. Other applications may also require 3D models, such as for visualization and location-based analysis. For example, a 3D model of an underground tunnel system could be a design model generated by underground system design software.

[0004] US9797247 relates to a control system for a machine configured to scan the walls of a mine, and discloses the use of a mine map showing a portion of the mine, the mine map including a route or vehicle path and mine walls. Virtual and temporary mine walls can be added to the mine map in response to user input. Machine operation is controlled based on the mine map to avoid collisions with the mine walls shown on the map. Summary of the Invention

[0005] This invention is defined by the features of the independent claims. Certain specific embodiments are defined in the dependent claims.

[0006] According to a first aspect of the invention, an apparatus is provided, comprising means configured to perform the following operations: receiving a three-dimensional input model of an underground tunnel system at a construction site; determining an initial first position of a virtual probe in the input model; determining a distance between the first position and a tunnel wall based on the input model; determining a tunnel orientation based on the determined distance; repositioning the virtual probe, together with the determined tunnel orientation, to a second position in the input model; generating a logical tunnel model indicating the path of the virtual probe in the input model based on the determined position of the repositioned virtual probe in the input model; and applying the logical tunnel model to determine the route between the starting point and the ending point of a vehicle in the tunnel system.

[0007] The device may include at least one processor and at least one memory including computer program code, the at least one memory and the computer program code being configured to enable the device to execute together with the at least one processor.

[0008] According to a second aspect of the present invention, a method for modeling an underground tunnel system is provided, comprising: receiving a three-dimensional input model of the underground tunnel system at a construction site; determining an initial first position of a virtual probe in the input model; determining a distance between the first position and a tunnel wall based on the input model; determining a tunnel orientation based on the determined distance; repositioning the virtual probe together with the determined tunnel orientation at a second position in the input model; generating a logical tunnel model indicating the path of the virtual probe in the input model based on the determined position of the repositioned virtual probe in the input model; and applying the logical tunnel model to determine the route between the starting point and the ending point of a vehicle in the tunnel system.

[0009] According to a third aspect, an apparatus is provided, comprising at least one processing core and at least one memory including computer program code, the at least one memory and the computer program code being configured to cause the apparatus to perform at least the method or an embodiment of the method using the at least one processing core.

[0010] In an embodiment according to any aspect, the virtual probe is repositioned in the virtual tunnel based on the input model without colliding with obstacles defined in the input model.

[0011] In an embodiment according to any aspect, a set of rays is projected from a first position along multiple directions, the distance is determined based on a measured distance to the ray intersection point with each ray, and the tunnel orientation is determined based on a comparison of these distances.

[0012] In any embodiment according to any aspect, the device is a server or is included in a control system that is also configured to visualize the logic tunnel model on at least one display device. Attached Figure Description

[0013] Figure 1 An example of an underground construction site is shown;

[0014] Figure 2a and 2c A 3D model of the underground construction site is shown. Figure 2b The mesh used for the mesh model is shown;

[0015] Figure 3 A virtual probe according to at least some embodiments is shown;

[0016] Figure 4 A method according to at least some embodiments is shown;

[0017] Figure 5 The input 3D model and the resulting logical tunnel model are shown.

[0018] Figure 6 and Figure 7 The operation of the virtual probe is shown; and

[0019] Figure 8 A device capable of supporting at least some of the embodiments is shown. Detailed Implementation

[0020] Figure 1 A simplified example of an underground mine including an underground tunnel network 2 is shown. Multiple mobile objects or devices, such as people or pedestrians 3 and / or mine vehicles 4, 5, 6, 7, may exist in different areas or operating zones of the site 1 and move between these different areas or operating zones.

[0021] The term "vehicle" in this document refers broadly to mobile machinery suitable for use in various types of mining and / or construction excavation site operations, such as trucks, dump trucks, vans, mobile rock drills or milling machines, mobile reinforcement machines, bucket loaders, or other types of mobile machinery applicable to various types of surface and / or underground excavation sites. Therefore, the term "mine vehicle" is not in any way limited to vehicles used only in ore mines, but rather can refer to any mobile machinery used on an excavation site. Mine vehicles can be autonomous mobile vehicles. The term "autonomous mobile vehicle" here refers to automated or semi-automated mobile vehicles that can be operated / driven independently in their autonomous operating mode without continuous user control, but may be externally controlled, for example, during emergency situations.

[0022] Site 1 includes a communication system, such as a wireless access system comprising a wireless local area network (WLAN) and / or a cellular communication network, which includes multiple wireless access nodes 8. Access nodes 8 can communicate with wireless communication units and other communication devices (not shown), wherein the wireless communication units are included in mining vehicles or mobile devices carried by pedestrians, and the other communication devices are, for example, network devices configured to facilitate communication with a control system 9, wherein the control system 9 can be an on-site (underground or above-ground) control system and / or a remote control system via an intermediate network. For example, the server of system 9 can be configured to manage at least some operations at the site, such as providing an operator UI to remotely monitor and, when necessary, control the automated operation of mining vehicles and / or assign work tasks to the fleet, and update and / or monitor task performance and status.

[0023] System 9 can connect to other networks and systems, such as site management systems, cloud services, intermediary communication networks, such as the Internet. The system may include or connect to other devices or control units, such as handheld user units, vehicle units, site management devices / systems, remote control and / or monitoring devices / systems, data analysis devices / systems, sensor systems / devices, etc.

[0024] Site 1 may also include various other types of mining operation devices 10 that can be connected to control system 9, for example, via access node 8, not in Figure 1 These mine operation devices are illustrated in detail. Examples of such additional mine operation devices 10 include various devices for power supply, ventilation, air condition analysis, safety, communication, and other automation. For example, the site may include a access control system that includes access control units (PCUs) 11 that separate operating areas, some of which may be equipped for autonomously operating mine vehicles. The access control system and associated PCUs can be configured to allow or prevent one or more mine vehicles and / or pedestrians from moving between areas.

[0025] A 3D model of an underground tunnel system can be applied to one or more applications, such as mine visualization applications, operations monitoring applications, and / or location applications. Such a 3D model can also be referred to as an environment model or a tunnel model. Figure 2a An example of a 3D model 20 of an underground construction site and its tunnel is shown, which shows the tunnel roof 21, tunnel walls 22, and tunnel top 23. The 3D model may include point cloud data generated from scanning or formed based on such point cloud data.

[0026] In some embodiments, reference Figure 2b and Figure 2cA 3D model is a mesh model that includes vertices, edges, and faces.24

[0027] In other embodiments, the 3D model can be a design model or can be generated based on: a design model such as a CAD model created by mine design software, or a 3D model created based on tunnel lines and tunnel cross-sections designed in drilling and blasting design software. Therefore, the same analysis or processing can be performed on the measured or initially planned model of the tunnel environment.

[0028] 3D models can be stored in a database accessible by one or more modules of a computing device, such as a mine model processing module, a user interface or visualization module, a route planning module, and / or a location service module.

[0029] Mesh models can be converted into mathematical graphs using algorithms that approximate the mesh geometry to create simpler models. However, these methods often fail to provide satisfactory results for representing underground mine sites. Underground site models are typically large and consist of several source files and site model sections that are not always seamlessly connected. Therefore, a model can be "broken" because the tunnel end segment of one model section does not match the tunnel start segment of another. Mathematical algorithms struggle to connect these model sections together. Sites also often have special tunnel shapes, such as passageways that are wider tunnel sections. Algorithms may have difficulty detecting these types of special shapes.

[0030] An improved method and system for processing underground construction site models are now provided, capable of generating seamless logical tunnel models based on a predefined 3D (input) model, which may include multiple imperfectly matched sections. (Reference) Figure 3 The system generates a virtual vehicle or probe 30 to travel within a virtual 3D tunnel system defined by a 3D input model. The virtual probe 30 can be a software entity and is configured to analyze the 3D input model, such as a mesh model 24. Based on the movement of the virtual probe 30 within the virtual tunnel system, the system or process generates a logical tunnel model indicating the path the virtual probe has traveled within the model.

[0031] Therefore, instead of using a mathematical algorithm to approximate the model, virtual probes are "sent" to a "virtual mine," which is modeled as a 3D mesh or point cloud. The virtual probes navigate through the virtual mine while simultaneously mapping it. The virtual probes (or vehicles) can navigate within the 3D mine model using the same principles as many real-world autonomous vehicles: obstacle detection. Through obstacle detection, the virtual probes can avoid collisions with tunnel walls, detect the pit floor, and determine the tunnel's orientation.

[0032] Figure 4 A method for generating a model is illustrated, which indicates an underground construction site and can be used as input to control operations at the site. The method can be implemented by equipment configured to process the model of the underground construction site, such as a server, site operator, designer or controller workstation, mobile unit, vehicle-mounted control unit, or other appropriately configured data processing device. The equipment can be configured to execute a model generation algorithm that performs model processing or generation procedures.

[0033] The device receives a 3D input model of the underground tunnel system at site 410, such as a mesh or point cloud 3D model as shown above. The input model can be received from a database or memory connected to or included by the device, or from another device, for example, via a communication connection.

[0034] Determine an initial first position 420 in the model for the virtual probe (e.g., probe 30). For example, the initial position could be a predetermined starting point, a randomly selected location within the tunnel system, or based on user input from the user interface.

[0035] The distance between the first position 430 and the tunnel wall is determined based on the input model. The tunnel orientation 440 is then determined based on the distance determined by the processing.

[0036] The virtual probe, along with the determined tunnel orientation, is repositioned 450 to a second position in the input model. An obstacle detection function can be configured to reposition the virtual probe within the virtual tunnel based on the input model without colliding with obstacles such as tunnel walls, tunnel tops, tunnel bottoms, or other types of obstacles defined in the input model (e.g., large rocks). Boxes 450 (and 430, 440) may be part of the obstacle detection function and / or may include further operations of the obstacle detection function, some exemplary embodiments of which are described below.

[0037] Based on the determined positions of the virtual probes repositioned in the input model, a logical tunnel model is generated that indicates the path of the virtual probes traveling in the input model. Therefore, consecutive positions form the path of the virtual probes in the input 3D model.

[0038] The term "logic tunnel model" as used herein generally refers to a model that represents the tunnel structure of an input 3D model in a simplified form, generated and representing the path of the virtual probes. The logical tunnel model may include a list of connection points indicating (recorded) positions of the virtual probes within the virtual tunnel based on the 3D input model. Thus, in some embodiments, the coordinates of a first and second position in the Cartesian coordinate system (x, y, z coordinates) may be initially stored and used to generate entries in the logical tunnel model in box 460. This method may be repeated, whereby in the next iteration, the second position is used as the initial (or current) first position, and the virtual probes are repositioned to subsequent positions based on boxes 430-450. In some embodiments, directions between the adjacent positions of the repositioned virtual probes in the input model are determined. These directions may be defined in the logical tunnel model and / or included in the visualization of the logical tunnel model.

[0039] Figure 5 A logic tunnel model 50 is shown, which can be applied... Figure 4 The method is based on the input 3D model 24. The 3D mesh model 24 can be converted into a graph consisting of vertices and edges, where the edges consist of paths to points 52 in 3D space. As the virtual probe 30 moves through the tunnel, it can create a graph edge that can include the paths to points 52. The default distance between points can be configurable, for example, one meter. Therefore, each time the probe travels one meter, it can add its current position X, Y, Z as path points to the current graph edge. Thus, the logical tunnel model can be a 3D model, but for some applications, generating a 2D representation may be sufficient.

[0040] It should be understood that Figure 4 Some of the available features are shown, which are related to generating a logical tunnel model based on a virtual probe traveling in a 3D input model. Various additions and modifications can be applied, and some additional embodiments are shown below.

[0041] The method may include projecting a set of rays 31 in multiple directions from a first or current position of the virtual probe 30. The rays may be sent in different directions in 3D space. However, the rays do not necessarily need to be projected over a 360° range in the horizontal and / or vertical planes, but may be projected at finite angles in the horizontal and / or vertical planes.

[0042] For example, such as Figure 3As shown, there may be a set of rays pointing towards the virtual probe in the forward direction or the map drawing direction (i.e., away from the generated location). These rays can be specific tunnel orientation detection rays to execute boxes 430 and 440. The number and angular deviation of the rays should be configured to provide sufficiently accurate detection of at least the tunnel orientation. The angular difference between tunnel orientation rays can be selected in the range of 1°–10°, for example, 2°–6°, and for example, a detection of 3° has provided very good results.

[0043] In addition to having different horizontal (x, y) directions, such tunnel orientation detection rays can also have different vertical (z) directions. There should be enough rays to ensure proper probe repositioning when connecting ramps with different tunnel horizontal levels. For example, a vertical plane difference between rays can be selected within the range of 5°–15°, and it has been found that applying a 10° difference provides very good results.

[0044] It should be noted that the plane can be adjusted according to the applied coordinate system, such as relative to the mobile device or the construction site. Ray casting operations typically refer to calculating ray-surface cross-tests.

[0045] The distance to the wall can be determined in box 430 based on the measured distance to the ray's intersection point (i.e., the point where the ray strikes the 3D surface of the tunnel). Ray projection can result in intersections, which can be x, y, and z coordinates in 3D space, and the corresponding distances can be determined based on these intersections. Based on the comparison of these distances, the tunnel orientation (440) can be determined. Therefore, the ray direction providing the furthest distance to the wall can be selected as the tunnel orientation (or line). Thus, the orientation of the virtual probe can be changed according to the tunnel orientation.

[0046] Then, the virtual probe 30 can be moved a predetermined distance (in the x, y, z directions) toward the tunnel orientation, and the resulting (x, y, z) position is selected as the probe's new position. However, in an alternative embodiment, also as described above, the virtual probe is moved (in shorter steps) toward the tunnel orientation direction (distance can also be measured during the movement). After reaching a pre-configured pathpoint distance threshold, a new pathpoint position is recorded for the logical tunnel model (as the second position in box 450).

[0047] In some embodiments, the number of rays and / or the width of a fan-shaped area (or ray projection coverage area / beam) of a group of rays are dynamically adjusted. For example, the width of the fan-shaped area can be narrowed by removing the outermost ray from the group of rays, and widened by adding the outermost ray. Processing resources can be reduced by increasing the angle between projected rays in non-critical map-drawing areas (e.g., by removing one ray from every three rays in the group of rays).

[0048] This dynamic adjustment can be particularly useful for the set of tunnel orientation rays to optimize between system performance and the accuracy required for different tunnel properties. The dynamic adjustment can be applied based on the current environment, or in one embodiment based on one or more previous ray projection events. In one embodiment, the number of rays and / or the fan width is adjusted according to the length of one or more tunnel orientation rays. For example, when the tunnel line is shortened and below a threshold, the fan width can be increased to ensure proper detection of dead ends or T-junctions. For example, rays can be projected in directions of -24, -18, -12, -6, 0 (tunnel orientation), 6, 12, 18, 24 degrees, while in the case of long tunnel lines, the number of rays and the fan width may be reduced, even, for example, to three rays in directions of -3, 0, and 3.

[0049] This method can be repeated until a termination criterion is met, such as detecting the end of the tunnel. In some embodiments, the following steps are performed:

[0050] The tunnel end is detected based on the distance determined from the (fourth) position of the virtual probe to the wall in the input model. Further checks for tunnel ends may be performed after box 440. Therefore, the tunnel end is detected if a tunnel end threshold condition or value is met (e.g., the longest ray is below a threshold).

[0051] In response to detecting the end of a tunnel, an indicator of the tunnel's end is stored in the logical tunnel model. This can be performed instead of box 440.

[0052] In response to the detection of the end of a tunnel, the virtual probe is repositioned to the previously detected node location (e.g., a tunnel branch) in the model. Alternatively, in response to the absence of any remaining tunnel branches not yet mapped, the generation of the logical tunnel model is terminated.

[0053] Therefore, whenever the virtual probe 30 reaches a dead end, it terminates the currently recorded edge of the graph.

[0054] This set of rays may include wall detection rays and / or branch detection rays. Wall detection rays may be projected onto both sides of the virtual probe 30 to detect the (shortest) distance to the walls on either side of the probe. Based on the distance determined by the processing, the virtual probe 30 may be centered between the walls at the tunnel location. The location determined for the logical tunnel model includes the position of the virtual probe centered between the tunnel walls.

[0055] This set of ray projection operations may include one or more pit bottom detection rays 33 to detect the distance from the virtual probe 30 to the horizontal height of the tunnel bottom or the pit bottom point. The pit bottom detection rays can be configured to point directly downwards in the vertical plane (z) to detect the pit bottom. It can be used to position the virtual probe at a predetermined distance, such as 1 meter or 2 meters above the horizontal height of the pit bottom. In addition to using pit bottom detection rays, or as an alternative, pit top detection rays can also be applied.

[0056] implement Figure 4 The device for this method can also be configured to perform a tunnel branch detection process, which may include:

[0057] In response to the determination at the (third) location of the virtual probe that two or more tunnel orientations exceed the branching threshold, a tunnel branch is detected, and

[0058] For this (third) position, an indicator of the tunnel branch is stored in the logical tunnel model.

[0059] The process may also include:

[0060] Select a first tunnel orientation from the two or more determined tunnel orientations for surveying, and

[0061] Perform a set of virtual probe relocation events in the input model to store the path of the virtual probe with the first tunnel orientation selected (where the tunnel orientation can be naturally updated at each relocation event).

[0062] Therefore, the virtual probe 30 can perform a repositioning event until the end of a tunnel in a tunnel branch facing the selected first tunnel is detected. Then, after storing the path facing the first tunnel and drawing a second branch map onto the second tunnel direction, the virtual probe can be repositioned to the tunnel branch (third) location. Tunnel or tunnel line / branch prospect or candidate list (or other types of records) can be maintained in the memory of the device performing the current virtual probe operation. Each prospect in the list has a start point and direction.

[0063] After tunnel detection is complete, the virtual probe 30 is repositioned or transported to the starting point of the next unmapped expected tunnel (if any) in the list. As described above, the virtual probe can be controlled in a specific direction (affecting the direction of the ray group), allowing it to be steered towards the detected expected tunnel orientation and begin mapping the expected tunnel. The expected tunnel line is then removed from the list of expected tunnel lines. If there is no graphical vertex at the starting point of the new tunnel line, a new graphical vertex can be created at that starting point.

[0064] exist Figure 3 In a simple example, four rays for branch detection point to the side, two to the left, and two to the right. These rays can be used to detect walls and branch tunnels. If the length of these rays is less than a branch detection threshold, the virtual probe may deflect away from the wall. If the length exceeds the branch detection threshold, such as 8 meters, a tunnel branch is detected. The threshold can be configured.

[0065] Figure 6 An example is shown where the length of the wall detection ray 61 has exceeded a pre-configured branch detection threshold (the limit is shown by element 62). Therefore, the virtual probe 30 has detected a tunnel branch, and thus the expected tunnel line in the direction of ray 61 can be defined.

[0066] Figure 7 This shows the situation after the tunnel on the right has been mapped and path 70 has been generated for the logical tunnel model. Virtual probe 30 has detected the tunnel branch on the left. The virtual probe is ready to begin mapping the tunnel branch on the left and can add new edges and new vertices to the logical tunnel model.

[0067] It should be understood that the execution of distance measurements or ray projection operations based on virtual probes... Figure 4 The device used in this method can be configured to detect various other tunnel characteristic information used in or to be identified within a logical tunnel model. For example, passageway locations can be detected (based on tunnel width) and indicated in the logical tunnel model. Another example is a ramp detection function, where a ramp is a horizontal connection between tunnels of different depths.

[0068] In some embodiments, the 3D input model includes 3D point cloud data generated based on a scanned tunnel. In box 430, the distance to the tunnel wall (or pit top or bottom) in the ray projection direction can be determined based on a set of nearest / neighboring points. Intersections can be simulated by measuring the distances to neighboring points at different points on the ray (i.e., at different ray distances) (e.g., every 10 cm). Based on the density of the point cloud model, a threshold distance for recording a hit can be configured. When at least one point (potentially multiple points) is closer than the threshold distance, a hit can be recorded at a ray point / distance, and thus an intersection is recorded. For example, if the maximum point density of the point cloud is 2 cm, a threshold distance of 10 cm already detected provides good results.

[0069] In some embodiments, only a subset of points from the 3D model is applied as the input data set for box 430. Therefore, there may be additional preprocessing or filtering steps prior to box 430. For example, using a reduced resolution or number of points may be sufficient, in which case the subset based on sufficient resolution can be uniformly selected for box 430, for example, selecting only points from a predetermined portion of the 3D model.

[0070] In another example embodiment, the model processing algorithm can be configured to, for example, detect and exclude specific portions of the 3D tunnel (input) model that are unrelated to boxes 440 and 450, based on the already determined locations of the virtual probes.

[0071] At least a portion of the logical tunnel model and points of that logical tunnel model (as and / or path locations based on virtual probes) can be used to plan, monitor, visualize, and / or control operations in the tunnel system 2 of site 1. Some examples are provided below.

[0072] Logical tunnel models can be applied to route planning or navigation of mobile devices (e.g., mobile vehicles 4 or mobile devices carried by people 3). For example, a logical tunnel model can thus be stored in a database accessible through a positioning unit or application, or a route planning unit or application for a site server or mining vehicle, to determine the route between the start and end points in a tunnel system. The most common route planning algorithms require mathematical graphs composed of vertices and edges. Visualization of underground tunnel systems, mobile device positioning, and / or route generation can now be achieved using considerably simpler models.

[0073] As another example, logical tunnel models are used in tunnel safety or evacuation applications or functions, and are configured to identify, for example, the nearest exit or shortest route for people located in the model to leave. Statistical information can be generated from logical tunnel models, such as the total tunnel length, the number of tunnel intersections, the average gradient, etc.

[0074] In yet another example embodiment, a logical tunnel model is applied to a traffic management application. The traffic management application can be configured to guide or control moving vehicles to their target locations based on route planning. The traffic management application can be configured to perform collision avoidance features, such as reserving a route and controlling the vehicle to wait or steer away when a higher-priority vehicle approaches.

[0075] The logical tunnel model can be converted into another type of 3D model. It should also be noted that the 3D input model can be updated repeatedly. For example, a drilling rig or loading and transport vehicle can be configured to scan its working area in the tunnel every round to update the tunnel model as excavation progresses. In some embodiments, the logical tunnel model is updated in response to detecting an update to the 3D input model.

[0076] Control system 9 may include a server, which may include one or more above-ground or underground computing units. The server may be configured to perform... Figure 4 The method provides the generated logical tunnel model as input to an additional module for controlling operations at site 1. In some embodiments, this additional module is a location service module or a visual GUI module.

[0077] System 9 or the server may include a task manager or management module configured to manage at least some operations at the work site through an application logic tunneling model. For example, the task manager may be configured to assign work tasks to the fleet and update and / or monitor task performance and status, as indicated in the task management GUI.

[0078] The server may include a model processing module that can maintain one or more models of the underground site, such as a 3D input model and a logical tunnel model. In some embodiments, the model processing module is configured to generate a logical tunnel model and store it in a database or memory of the system or server.

[0079] The visualizer GUI module can be configured to generate at least some display views for the operator (locally and / or remotely). In some embodiments, the visualizer GUI module is configured to generate 3D (and / or 2D) views indicating the current position of a moving object in a tunnel based on the (input) 3D model and / or logical tunnel model.

[0080] The server may include additional modules, such as remote monitoring processes and a user interface, and / or a cloud scheduler component configured to provide selected site information, such as a logical tunnel model, to the cloud service. The system and server may connect to other systems and / or networks, such as site management systems, cloud services, intermediary communication networks, such as the Internet. The system may also include or connect to other devices or control units, such as handheld user units, vehicle units, site management devices / systems, remote control and / or monitoring devices / systems, data analysis devices / systems, sensor systems / devices, etc.

[0081] Electronic devices including electronic circuits can be used to implement at least some embodiments of the present invention (such as combining...). Figure 4 The device (shown as the main operating device). The device may be included in at least one computing device that is connected to or integrated into a control system, which may be part of a site control or automation system.

[0082] Figure 8 Example devices capable of supporting at least some embodiments of the present invention are shown. A device 80 is shown, which can be configured to perform at least some of the embodiments related to the above-described moving object position tracking. In some embodiments, such as in a control system 9 at a construction site, device 80 includes or implements a server and / or model processing module.

[0083] Processor 81 is included in device 80. For example, processor 81 may include a single-core or multi-core processor. Processor 81 may include more than one processor. The processor may include at least one application-specific integrated circuit (ASIC). The processor may include at least one field-programmable gate array (FPGA). The processor may be configured to perform actions at least in part by computer instructions.

[0084] Device 80 may include memory 82. The memory may include random access memory and / or permanent memory. The memory may be at least partially accessible by processor 81. The memory may be at least partially included in processor 81. The memory may be at least partially external to device 80 but accessible to the device. Memory 82 may be a means for storing information, such as parameters 84 that affect the operation of the device. Specific parameter information may include, for example, parameter information affecting the generation of a logic tunnel model and virtual probe operation applications, such as thresholds.

[0085] Memory 82 may include computer program code 83 comprising computer instructions, to which processor 81 is configured to execute said computer instructions. When computer instructions configured to cause the processor to perform a specific action are stored in memory, and the apparatus is generally configured to operate under the guidance of the processor using computer instructions from memory, the processor and / or at least one of its processing cores may be considered configured to perform said specific action. The processor, together with the memory and computer program code, may form means for performing at least some of the above-described method steps within the apparatus.

[0086] The device 80 may include a communication unit 85, which includes a transmitter and / or a receiver. The transmitter and receiver may be configured to transmit and receive information according to at least one cellular or non-cellular standard. For example, the transmitter and / or receiver may be configured to operate according to Global System for Mobile Communications (GSM), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), 3GPP New Radio Access Technology (N-RAT), Wireless Local Area Network (WLAN), and / or Ethernet.

[0087] Device 80 may include or be connected to a UI. The UI may include at least one of a display 86, a speaker, and an input device 87 (such as a keyboard, joystick, touchscreen, and / or microphone). The UI may be configured to display views based on a site model and moving object position indicators. Users can operate the device and control at least some aspects of the currently disclosed features, such as tunnel model visualization. In some embodiments, users can control vehicles 4-7 and / or the server through the UI to, in response to user authentication and sufficient permissions associated with the user, for example, change the operating mode, change the displayed view, or modify parameter 84.

[0088] Device 80 may also include and / or be connected to other units, devices 88 and systems, such as one or more sensor devices 88 that sense the environment of device 80.

[0089] The processor 81, memory 82, communication unit 85, and UI can be interconnected in various ways via electrical leads within the device 80. For example, each of the above-described devices can be individually connected to the main bus within the device to allow the devices to exchange information. However, as those skilled in the art will understand, this is merely an example, and depending on the embodiment, various ways of interconnecting at least two of the above-described devices can be selected without departing from the scope of the invention.

[0090] It should be understood that the disclosed embodiments of the invention are not limited to the specific structures, processes, or materials disclosed herein, but rather are equivalent examples of the embodiments that will be recognized by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0091] References to an embodiment or an embodiment throughout the specification mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in at least one embodiment of the invention. Therefore, the phrases “in one embodiment” or “in an embodiment” appearing in various places throughout the specification do not necessarily refer to the same embodiment. Where numerical values ​​are mentioned using terms such as, for example, approximately or substantially, the exact numerical value is also disclosed.

[0092] As used herein, multiple items, structural elements, constituent elements, and / or materials may be presented in a common list for convenience. However, these lists should be interpreted as each member of the list being individually identified as a separate and unique member. Therefore, without indication to the contrary, no single member in such a list should be construed as being substantially equivalent to any other member in the same list solely based on its presentation in a common group. Furthermore, various embodiments and examples of the invention, along with alternatives to its various components, are mentioned herein. It should be understood that these embodiments, examples, and alternatives should not be construed as de facto equivalents of each other, but should be regarded as separate and autonomous representations of the invention.

[0093] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details, such as examples of length, width, shape, etc., have been provided in the foregoing description to provide a thorough understanding of embodiments of the invention. However, those skilled in the art will recognize that the invention can be practiced without one or more of the stated specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations have not been shown or described in detail to avoid obscuring aspects of the invention.

[0094] While the foregoing examples illustrate the principles of the invention in one or more specific applications, it will be apparent to those skilled in the art that many modifications in form, use, and implementation details may be made without exercising inventive capacity and without departing from the principles and concept of the invention. Therefore, the invention is not intended to be limited except as defined by the appended claims.

[0095] The verbs “to comprise” and “to include” are used in this document as open-ended restrictions, neither excluding nor requiring the presence of any unlisted features. Unless otherwise expressly stated, the features recited in the dependent claims may be freely combined with each other. Furthermore, it should be understood that the use of “a” or “an” in this document, i.e., the singular form, does not exclude a plurality.

Claims

1. An apparatus comprising means configured to perform: -Receive (410) the three-dimensional input model (24) of the underground tunnel system of the construction site (1), - Determine the initial first position of the virtual probe (30) in the input model (420). - Determine the distance between the first position and the tunnel wall (22) based on the input model; -The tunnel orientation (440) is determined based on the distance determined by the processing. - Reposition the virtual probe (450) together with the determined tunnel orientation at the second position in the input model. - Tunnel branch is detected in response to determining that there are two or more tunnel orientations based on the ray length used for branch detection exceeding the branch threshold at the third position of the virtual probe (30); - Store the indicator for the tunnel branch at the third location in the logical tunnel model (50); - The end of the tunnel is detected based on the determined distance from the fourth position of the virtual probe (30) in the input model (24) to the tunnel wall (22); - Store the indicator at the end of the tunnel in the logical tunnel model; - In response to detecting the end of the tunnel, the virtual probe is repositioned to the previously detected tunnel branch in the model; -Based on the determined position of the virtual probe repositioned in the input model, generate (460) a logical tunnel model (50) indicating the path the virtual probe travels in the input model, and - The logical tunnel model (50) is applied to determine the route of the vehicle (4) between the start and end points in the tunnel system. Determining the tunnel orientation includes: projecting a set of rays (31) from the first position along multiple directions, determining the distance based on a measured distance to the ray intersection point with each ray, and determining the tunnel orientation based on a comparison of the distances.

2. The device according to claim 1, wherein, The device includes an obstacle detection device configured to reposition the virtual probe (30) in a virtual tunnel based on the input model without colliding with obstacles defined in the input model.

3. The device according to claim 1, wherein, The device also includes means configured to perform the following: - Select a first tunnel orientation from the two or more determined tunnel orientations for investigation, and - A set of virtual probe repositioning events are executed in the input model (24) to store the path of the virtual probe (30) toward the selected first tunnel orientation.

4. The device according to any one of claims 1-3, wherein, The device includes means configured to perform the following: - The generation of the logical tunnel model is terminated in response to the absence of any remaining tunnel branches that have not been mapped.

5. The device according to claim 3, wherein, The device includes means configured to perform the following: - After storing the path toward the first tunnel orientation, the virtual probe (30) is repositioned together with the second tunnel orientation in one of the determined two or more tunnel orientations at the fifth position in the input model (24), and - Execute a set of virtual probe repositioning events to store the path of the virtual probe toward the second tunnel.

6. The device according to any one of claims 1-3, wherein, Based on the distance determined by the processing, the virtual probe (30) is centered at the tunnel location, and the determined location includes the position of the virtual probe centered between the tunnel walls (22).

7. The device according to any one of claims 1-3, wherein, The set of rays includes: 1) wall detection rays and / or branch detection rays; 2) tunnel orientation detection rays; and 3) one or more pit bottom detection rays for detecting the distance from the virtual probe (30) to the horizontal height of the tunnel pit bottom or the pit bottom point.

8. The device according to any one of claims 1-3, wherein, The input model (24) is a mesh model that includes vertices, edges and faces, and the logical tunnel model includes vertices connected by edges.

9. The device according to any one of claims 1-3, wherein, The input model includes three-dimensional point cloud data generated based on scanning the tunnel, and the device is configured to determine the distance to the tunnel wall in the ray projection direction based on a set of neighboring points.

10. The device according to any one of claims 1-3, wherein, The device also includes means configured to perform the following: further apply the logical tunnel model (50) to one or more of the following: generate a visualization of the structure of the tunnel system for a user, or calculate statistics of the tunnel system.

11. A computer-implemented method, comprising: -Receive (410) the three-dimensional input model (24) of the underground tunnel system of the construction site (1), - Determine the initial first position of the virtual probe (30) in the input model (420). - Determine the distance between the first position and the tunnel wall (22) based on the input model; -The tunnel orientation (440) is determined based on the distance determined by the processing. - Reposition the virtual probe together with the determined tunnel orientation at a second location in the input model (450). - Tunnel branch is detected in response to determining that there are two or more tunnel orientations based on the ray length used for branch detection exceeding the branch threshold at the third position of the virtual probe (30); - Store the indicator for the tunnel branch at the third location in the logical tunnel model (50); - The end of the tunnel is detected based on the determined distance from the fourth position of the virtual probe (30) in the input model (24) to the tunnel wall (22); - Store the indicator at the end of the tunnel in the logical tunnel model; - In response to detecting the end of the tunnel, the virtual probe is repositioned to the previously detected tunnel branch in the model; -Based on the determined position of the virtual probe repositioned in the input model, generate (460) a logical tunnel model (50) indicating the path the virtual probe travels in the input model, and - The logical tunnel model (50) is applied to determine the route of the vehicle (4) between the start and end points in the tunnel system. Determining the tunnel orientation includes: projecting a set of rays (31) from the first position along multiple directions, determining the distance based on a measured distance to the ray intersection point with each ray, and determining the tunnel orientation based on a comparison of the distances.

12. The method of claim 11, further comprising: - The generation of the logical tunnel model is terminated in response to the absence of any remaining tunnel branches that have not been mapped.

13. A computer program product comprising code, said code being configured to, when executed in a data processing apparatus, cause the method according to claim 11 or 12 to be performed.

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