Non-satellite coordinate anchoring and map mapping method

Abstract

The invention provides a non-satellite coordinate anchoring and map mapping method, which is suitable for underground, indoor, closed or special environments without satellite signals or without allowing satellite signals to be used, and realizes map-level position identification and marking of space objects. The method comprises the following steps: establishing a local three-dimensional space coordinate system, and constructing a space point set based on scanning or modeling; selecting an anchor point in a map system, and establishing a coordinate mapping function in combination with the rotation matrix and the translation vector; and the geometric representative coordinate points of the target object in the space are mapped into the anchoring points in the map, so that bidirectional correspondence between the space coordinates and the map coordinates is realized. The method does not need to depend on a satellite positioning system, can be widely applied to warehouse logistics, tunnel facilities, rail transit, underground pipe galleries and other complex environments, and supports object marking, positioning management and scheduling control.

Description

Technical Field

[0001] This invention relates to the field of spatial positioning and coordinate mapping technology, and in particular to a method for mapping spatial coordinates to map coordinates through local anchor points without relying on a satellite navigation system. This method is applicable to positioning and spatial management scenarios in underground, enclosed, or special environments. Background Technology

[0002] While global positioning systems (GPS, BeiDou, etc.) are widely used for positioning and navigation, satellite signals are easily blocked in environments such as tunnels, underground parking garages, warehouses, factories, subway systems, and mines, making reliable positioning difficult. In these environments, auxiliary positioning methods such as RFID, UWB, LiDAR, and inertial navigation are commonly used, but most lack a unified spatial anchoring model, making it difficult to accurately correlate local coordinate systems with map systems.

[0003] Especially in situations involving spatial resource allocation, dynamic tracking, or map-level management, relying solely on local positioning systems makes it difficult to support unified coordinates or map-based display and operation across multiple regions.

[0004] Therefore, there is an urgent need for a coordinate anchoring and map mapping method that is independent of satellite signals, so as to realize the unified conversion between local spatial points and map coordinates and meet the needs of precise spatial management under non-satellite conditions. Summary of the Invention

[0005] This invention provides a non-satellite coordinate anchoring and map mapping method. By establishing a transformation relationship between a local spatial coordinate system and a map region, any spatial point can be uniquely represented on the map, achieving spatial anchoring, location management, and path support under non-satellite conditions. This method, through steps such as presetting anchor points, constructing a coordinate transformation matrix, point binding, and projection mapping, forms a spatial coordinate fusion mechanism suitable for multiple environments and systems, and provides visualization support.

[0006] To achieve the above objectives, the technical process includes the following steps:

[0007] (1) Construction of local spatial coordinate system

[0008] Using 3D scanning equipment or a known structural layout, point cloud computing is performed on the warehouse space to establish a local 3D spatial coordinate system W with a reference anchor point as the origin, forming a complete 3D coordinate set P(x, y, z). This coordinate system uses the anchor point as the origin and positive coordinate axes (X-axis pointing towards the main passageway inside the warehouse, Z-axis pointing upwards). The axial directions of this local coordinate system are set according to the actual structure of the site, for example, with the X-axis extending along the main passageway or main structure, the Z-axis pointing upwards, and the Y-axis forming a right-handed coordinate system. The constructed spatial coordinate system W is suitable for closed or semi-open environments with regular or irregular structures, and possesses consistency, scalability, and mappability.

[0009] (2) Establishment of coordinate mapping matrix

[0010] In the map system, select the anchor reference point G0(u0, v0, w0) corresponding to the target space. Combined with the spatial registration algorithm, construct a set of functional relationships M = R·P + T that map any point P in the local spatial coordinate system to a point M in the map coordinate system, where: R is a 2×3 rotation matrix, representing the rotation relationship between the local spatial coordinate axes and the map coordinate axes; T is a two-dimensional translation vector that defines the anchoring position of the local coordinate origin in the map coordinate system.

[0011] The rotation matrix R is constructed by calculating the angle between the local coordinate system's X-axis and the map reference direction (north), and is obtained by fitting multi-point registration using the minimum mean square error (LMSE).

[0012] The translation vector T is calculated using the anchor point P0 and its corresponding map point M0:

[0013] (3) Object placement and coordinate binding

[0014] In practical application scenarios, when a target object (such as goods, equipment, facility components, etc.) is deployed to a designated location, the system first records the spatial coordinates P1(x1,y1,z1) of its location as the starting point of the object's space.

[0015] If the object has preset volume parameters (such as outer packaging specifications, floor space, etc.), the boundary of the three-dimensional space area it occupies can be automatically calculated based on these parameters, such as the termination point P2 (x2=x1+L,y2=y1+W,z2=z1+H), where L, W, and H are the length, width, and height of the object in space, respectively.

[0016] The system supports associating and binding this three-dimensional coordinate range (called the "bounding box") with the object's basic attributes (such as unique number, type, batch, entry time, etc.) to form a precise relationship between the object and its physical location coordinates, realizing spatial-level data anchoring and management infrastructure.

[0017] (4) Map location mapping

[0018] The system calls the aforementioned coordinate mapping function M to project a representative spatial point within the object's bounding box onto a point M(u,v) in the map coordinate system. This representative point can be selected based on the specific application strategy. If you want to emphasize control over the storage start point, you can choose the start point P1; If you want to emphasize the object's center of gravity or overall distribution, you can choose the geometric center point P of the bounding box. c ; If the direction of operation needs to be considered (such as guiding the movement at entrances and exits), the centerline point P of the enclosing plane can be selected. f .

[0019] The aforementioned representative points are transformed by a mapping function and projected onto the map area, establishing the correspondence between object space coordinates and map anchor coordinates. Based on this, the system supports functions such as static point labeling on the map, object space-map dual coordinate lookup in the database, and integration with subsequent visualization or path planning systems.

[0020] Compared with the prior art, the present invention has the following significant advantages:

[0021] 1. Implement coordinate-based map-level location display By accurately mapping spatial coordinates to map coordinates, the system can anchor and mark the true three-dimensional position of any object in map space, overcoming the problem that traditional warehouse management cannot reflect the true position by relying solely on a floor plan, and significantly improving the intuitiveness of positioning and operational efficiency.

[0022] 2. Supports coordinate-driven full-process management This method uses coordinates as the core data element to record the entire process of an object's placement, state changes, and location migration in three-dimensional space. It supports historical trajectory backtracking, precise location analysis, and spatial conflict judgment, thus building a more intelligent and traceable spatial management system.

[0023] 3. Compatible with multi-source heterogeneous data access The method of this invention supports the unified conversion of data from systems such as laser point cloud modeling, image scanning, and RFID / WMS into a standard three-dimensional coordinate format. It has high data compatibility and cross-system integration capabilities, and is suitable for various types of environments such as warehousing, industry, logistics, finance, judiciary, and mining.

[0024] 4. Adaptable to intelligent and flexible application scenarios This method is naturally applicable to modern intelligent warehousing scenarios such as unmanned warehouses, automated storage and retrieval systems, and human-machine hybrid operation areas. It can effectively support functions such as robot navigation, scheduling path planning, and spatial zoning management, providing core positioning support for intelligent logistics and flexible manufacturing.

[0025] 5. It has good expandability and visual operability. The map display interface can overlay different layers and supports various icon, perspective and interaction style configurations, which makes it easier for managers to carry out fine-grained monitoring, zoning management and graphical operation at different levels and spatial densities, greatly improving the system's usability and user experience. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the system structure of the present invention.

[0027] Figure 2 This is a schematic diagram illustrating the mapping relationship between the local spatial coordinate system and the map coordinate system in this invention.

[0028] Figure 3 This is a schematic diagram of the anchoring of objects in a map in this invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and beneficial effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. This invention is not limited to the specific embodiments described below; any equivalent substitutions or improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0030] Example 1: Establishment of Local Spatial Mapping to Map Coordinates

[0031] like Figure 1 and Figure 2 As shown in the figure, this embodiment takes an industrial plant as an example to illustrate how to construct a coordinate mapping method under non-satellite conditions.

[0032] The steps are as follows:

[0033] 1. Construction of Local Spatial Coordinate System Using a 3D scanning device, 3D point data within the spatial structure of the factory area is acquired, and a local spatial coordinate system W is established. The origin of the local coordinate system is set as P0 = (0,0,0), and the main channel direction is used as the X-axis, with the vertical direction as the Z-axis, forming an orthogonal 3D coordinate system.

[0034] 2. Anchoring map reference points In a geographic information system map, the anchor point M0 = (u0, v0) of the area where the space is located is selected as the mapping target of the local coordinate origin.

[0035] 3. Calculation of rotation and translation matrices The rotation matrix is ​​obtained by measuring the angle θ = 30° between the X-axis of the spatial coordinate system and the north direction of the map using a registration algorithm:

[0036] Where the anchor point P0=(0,0,0) corresponds to the map coordinates M0=(100,200), then T=(100,200).

[0037] 4. Coordinate mapping function generation Based on the rotation matrix R and the translation vector T, the system can transform any point P in space into M=R⋅P+T, thus completing the unique anchoring from spatial coordinates to map coordinates. If a device selects P(10,5,0) as the representative point placed in the target space, after transformation by the mapping function M=R⋅P+T, its identifier in the geographic coordinate system is the location M(138,230).

[0038] Example 2: Object Map Anchoring and Information Binding

[0039] like Figure 3 As shown, based on the above coordinate mapping relationship, this embodiment is used to realize the location anchoring and basic information management of multiple spatial objects in the map system.

[0040] The process is as follows:

[0041] 1. The system assigns a unique representative point P in the spatial coordinate system to each managed object (such as goods, machines, sensing devices, etc.) through sensors, input interfaces, or automatic binding methods.

[0042] 2. The system converts the coordinates P of the point into a map point M through a mapping function, and then displays it on the map with anchorage.

[0043] 3. Each object is bound to its attribute information in the system, including number, category, status, deployment time, etc., and associated with its map anchor point.

[0044] 4. The map system can perform the following on all anchored objects: Single sign-on query; Regional statistics; Layout planning and other operations.

[0045] This method does not rely on satellite positioning signals and is suitable for underground spaces, enclosed areas, and scenarios where there are no satellite signals or satellite positioning is not permitted (such as underground warehouses, subway stations, data centers, high-density workshops, and confidential spaces). By constructing a stable space-map mapping mechanism, it achieves non-satellite location calibration and map-level positioning management of spatial entities, providing accurate spatial references for intelligent management systems.

Claims

1. A method for non-satellite coordinate anchoring and map mapping, characterized in that, Includes the following steps: (1) Local coordinate system construction steps: collect point cloud data in the target space, construct a three-dimensional coordinate system W inside the space, and form a spatial point set containing multiple three-dimensional coordinate points P(x, y, z); (2) Steps for establishing the coordinate mapping matrix: Select the anchor point G0(u0, v0) corresponding to the space in the map system, and combine the spatial registration algorithm to establish the coordinate mapping function M = R·P + T, where R is a two-dimensional rotation matrix and T is a two-dimensional translation vector, which is used to map any point P in the spatial coordinate system W to map coordinates M(u, v); (3) Target object placement and binding steps: Place any target object in a specific location in the space, record its spatial coordinates, such as the starting point, center point or geometric representative point P0(x0, y0, z0), and bind and store the coordinates with the object's identification information; (4) Map anchoring step: Based on the aforementioned mapping function, the spatial representative point coordinates P0 of the target object are mapped to the point M0 in the map, thereby realizing its position anchoring and unique identification in the map space.

2. The method according to claim 1, wherein the rotation matrix R is calculated based on the angle θ between the principal axis of the spatial coordinate system and the specified direction axis of the map, and R is a two-dimensional rotation matrix:

3. The method according to claim 1, wherein the selection strategy for representative points includes, but is not limited to: storage starting point, geometric center point, front end midpoint or user-defined coordinate point.

4. The method according to claim 1, wherein the mapped map point M0 can be used to implement object labeling, location query or distribution analysis on the map interface.

Images