Indoor path planning method and system based on multi-positioning fusion

Abstract

The invention relates to an indoor path planning method and system based on multi-positioning fusion, and the method comprises the steps: employing a plurality of sensor technologies to obtain indoor position information, the plurality of sensor technologies comprise a Bluetooth base station AOA technology and an inertial navigation technology, the Bluetooth base station AOA technology is based on a plurality of set Bluetooth base stations or Bluetooth beacons, and the inertial navigation technology is based on the Bluetooth base stations or Bluetooth beacons; estimating the current position of the object by measuring the angle of arrival of the signal; the inertial navigation technology is based on a built-in accelerometer and a gyroscope, the direction and the distance of an object are estimated, and the current position is obtained; fusing the current position estimated by the Bluetooth base station AOA technology and the current position estimated by the inertial navigation technology to obtain fused current position information; and calculating an optimal path for path navigation according to the target position of the user, the map information and the current position information of the object, and dynamically adjusting the optimal path according to the current position information acquired in real time. Compared with the prior art, the method has the advantages that the accuracy and stability of positioning and path planning are improved through fusion of multiple positioning technologies.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to an indoor path planning method and system based on multi-positioning fusion. Background Art

[0002] With the development of science and technology, indoor positioning technology and path planning technology are increasingly widely used in smart home, smart office, virtual reality and other fields. Indoor positioning technology mainly obtains the location information of indoor objects or people through various positioning devices and technologies, such as Bluetooth base station AOA, Bluetooth beacon, inertial navigation, etc. Path planning technology plans the optimal path from the starting point to the end point based on the positioning information to achieve the purpose of navigation. Multi-sensor fusion technology integrates and fuses the data of multiple sensors to improve the accuracy and stability of positioning.

[0003] Existing solutions mainly rely on a single positioning technology, such as Bluetooth base station AOA or Bluetooth beacons, or inertial navigation, to obtain indoor location information, and then plan paths based on this location information. For example, some shopping malls or office buildings use Bluetooth beacons for indoor positioning, and users can use mobile phone apps to check their location in the mall or office building, as well as find the nearest exit or toilet, etc.

[0004] However, existing technologies still have some problems in practical applications. First, since each positioning technology has its own accuracy and latency characteristics, it is a challenge to maintain accuracy in a real-time environment. For example, the positioning accuracy of Bluetooth beacons is affected by factors such as signal strength and environmental interference, and positioning errors may occur. Secondly, multi-positioning fusion requires processing a large amount of data and complex algorithms, and how to efficiently process and calculate data is also a difficult problem. In addition, how to seamlessly integrate multiple positioning technologies into a system and perform effective data fusion and coordination to provide stable and reliable services is also a problem that needs to be solved urgently. Summary of the invention

[0005] The purpose of the present invention is to provide an indoor path planning method and system based on multi-positioning fusion in order to overcome the defect that a single positioning technology in the above-mentioned prior art is difficult to maintain accuracy and low latency in a real-time environment.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] An indoor path planning method based on multi-positioning fusion includes the following steps:

[0008] A variety of sensor technologies are used to obtain indoor location information, including Bluetooth base station AOA technology and inertial navigation technology. The Bluetooth base station AOA technology estimates the current location of an object by measuring the signal arrival angle based on multiple Bluetooth base stations or Bluetooth beacons that are set up; the inertial navigation technology estimates the direction and distance of an object and obtains the current location based on a built-in accelerometer and gyroscope;

[0009] Fusing the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology to obtain fused current position information;

[0010] According to the user's target location, map information and the current location information of the object, an optimal path is calculated for path navigation, and the optimal path is dynamically adjusted according to the current location information obtained in real time.

[0011] Furthermore, the method also includes using multi-threading technology to perform parallel computing on the data processing processes of various sensor technologies.

[0012] Furthermore, the method measures the signal arrival angle of the Bluetooth base station or Bluetooth beacon through a two-station direction finding positioning algorithm to estimate the current position of the object.

[0013] Furthermore, the method uses a complementary filtering algorithm to estimate the direction and distance of the object according to the detection values ​​of the accelerometer and the gyroscope, and obtain the current position.

[0014] Furthermore, the complementary filtering algorithm includes weighted averaging the detection data of the accelerometer and the gyroscope to obtain a fusion result, estimating the direction and distance of the object according to the fusion result, and obtaining the current position.

[0015] Furthermore, the complementary filtering algorithm compares the fusion result of the accelerometer and the gyroscope with the actual value, and uses a PI controller to adjust the fusion result to achieve tracking of the current position of the object.

[0016] Furthermore, the method adopts a Kalman filter fusion algorithm to fuse the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology.

[0017] Furthermore, the fusion process also includes: setting the priority of the Bluetooth base station AOA technology and the inertial navigation technology, and dynamically adjusting the fusion weight of the Bluetooth base station AOA technology and the inertial navigation technology according to the positioning accuracy and delay.

[0018] Furthermore, the method adopts an A* path planning algorithm to calculate an optimal path for path navigation according to the user's target location, map information and the current location information of the object.

[0019] The present invention also provides an indoor path planning system based on multi-positioning fusion, comprising:

[0020] A Bluetooth base station AOA positioning module is provided with multiple Bluetooth base stations or Bluetooth beacons, and is used to estimate the current position of the object by measuring the signal arrival angle based on the multiple Bluetooth base stations or Bluetooth beacons set;

[0021] An inertial navigation module, which is equipped with an accelerometer and a gyroscope, is used to estimate the direction and distance of an object and obtain the current position based on the measurements of the accelerometer and the gyroscope;

[0022] A data fusion module, used to fuse the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology to obtain the fused current position information;

[0023] A path planning module is used to calculate the optimal path for path navigation based on the user's target location, map information and the current location information of the object, and dynamically adjust the optimal path based on the current location information obtained in real time;

[0024] The computing processing module is used to realize parallel processing of data using multi-threading technology.

[0025] Compared with the prior art, the present invention has the following advantages:

[0026] (1) Improve positioning accuracy and stability: This technical solution integrates and fuses the data of multiple positioning technologies through multi-positioning fusion technology, thereby improving the accuracy and stability of positioning. Compared with the existing single positioning technology, multi-positioning fusion technology can provide more accurate and stable location information, thereby improving the accuracy of path planning.

[0027] (2) Optimized path planning: The present invention can calculate the optimal path according to the user's target location, and can effectively avoid obstacles and optimize the navigation path. This can not only save the user's time, but also improve the user experience and make indoor navigation more convenient and efficient.

[0028] (3) Efficient data processing and calculation: The present invention takes into account that multi-positioning fusion requires processing a large amount of data and complex algorithms, and therefore adopts efficient data processing and calculation methods. This can not only improve the efficiency of data processing, but also reduce the consumption of computing resources, making the system more efficient and stable.

[0029] (4) Seamless integration of multiple positioning technologies: This technical solution can seamlessly integrate multiple positioning technologies into one system and perform effective data fusion and coordination. This can not only provide stable and reliable services, but also flexibly select and switch different positioning technologies according to actual needs, thereby improving the adaptability and flexibility of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 A schematic diagram of a flow chart of an indoor path planning method based on multi-positioning fusion provided in an embodiment of the present invention;

[0031] Figure 2 A schematic diagram of the direction finding principle of a two-station direction finding positioning algorithm provided in an embodiment of the present invention;

[0032] Figure 3 A schematic diagram of a positioning effect provided in an embodiment of the present invention;

[0033] Figure 4 The figure is a schematic diagram of a positioning result obtained after data fusion provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0035] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0037] Example 1

[0038] like Figure 1 As shown, this embodiment provides an indoor path planning method based on multi-positioning fusion, including the following steps:

[0039] S1: Multiple sensor technologies are used to obtain indoor location information, including Bluetooth base station AOA technology and inertial navigation technology. Bluetooth base station AOA technology is based on multiple Bluetooth base stations or Bluetooth beacons, and estimates the current location of the object by measuring the signal arrival angle; inertial navigation technology estimates the direction and distance of the object and obtains the current location based on the built-in accelerometer and gyroscope;

[0040] S2: Fusing the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology to obtain the fused current position information;

[0041] S3: Calculate the optimal path for path navigation based on the user's target location, map information and the object's current location information, and dynamically adjust the optimal path based on the current location information obtained in real time.

[0042] Preferably, the method further comprises using multi-threading technology to perform parallel computing on the data processing processes of each sensor technology.

[0043] This solution includes the following processing steps:

[0044] 1) Fusion of multiple positioning technologies: First, indoor location information is obtained by using a variety of different technologies or sensors, including Bluetooth base station AOA or Bluetooth beacon, inertial navigation (using sensors such as accelerometers and gyroscopes to estimate the direction and distance of movement). Then, the data of the above multiple positioning technologies are integrated and fused to improve the accuracy and stability of positioning.

[0045] 2) Data processing and calculation: In view of the problem that multi-positioning fusion requires processing a large amount of data and complex algorithms, efficient data processing and calculation methods are adopted. This includes fusing the raw data of different positioning technologies, extracting and fusing the location features of different technologies, and using fusion algorithms to make decisions on location estimation and path planning.

[0046] 3) System integration and coordination: In order to seamlessly integrate multiple positioning technologies into one system and conduct effective data fusion and coordination to provide stable and reliable services, advanced system integration and coordination technologies are adopted. This includes designing and implementing a system platform that is compatible with multiple positioning technologies, and formulating effective data fusion and coordination strategies.

[0047] 4) Path planning and optimization: Calculate the best path based on the user's target location, avoid obstacles, optimize the navigation path, and improve the user's indoor navigation experience. This requires the use of advanced path planning and optimization algorithms, as well as path planning and optimization in combination with the actual environment.

[0048] The following is a detailed description of the process of this program:

[0049] 1. Data Collection

[0050] For Bluetooth base station AOA technology, optionally, the signal arrival angle of the Bluetooth base station or Bluetooth beacon is measured through a two-station direction finding positioning algorithm to estimate the current position of the object.

[0051] Optionally, in this embodiment, multiple Bluetooth base stations are set up, and the distance between each Bluetooth base station is 5 meters. The position of the mobile device object is estimated by measuring the signal arrival angle. In addition, the inertial navigation technology is used to estimate the direction and distance of the mobile device object through the built-in accelerometer and gyroscope.

[0052] The principle of the two-station direction finding positioning algorithm to obtain the AOA positioning coordinates is as follows:

[0053] like Figure 2 As shown, there are base stations S1 (x1, y1, z1), S2 (x2, y2, z2), and target T (x, y, z). The key angles in the figure can be expressed by the base station coordinates and the target coordinates as follows:

[0054]

[0055] The target coordinates can be inferred from three of the four corners combined with the base station coordinates as follows:

[0056] Step 1: The distance between two base stations L = (x1-x2) 2 +(y1-y2) 2 +(z1-z2) 2

[0057] Step 2: In △S1T′S2, according to the sine theorem:

[0058] Step 3: In △TT′S1, get the distance between T and S1

[0059] stpe4: Available: x=R′cosξ1cosβ1+x1; y=R′cosξ1sinβ1+y1; z=R′sinξ1+z1

[0060] The error derivation process is as follows:

[0061] Condition: S1(x1,y1,z1) S2(x2,y2,z2) T(x,y,z)

[0062] Performing total differential calculation, we can obtain:

[0063]

[0064] Where L is the distance from base station S1 or S2 to the target

[0065]

[0066] The first three of the above equations can be written in matrix form:

[0067] dA=Fdr+dX

[0068]

[0069] Therefore, the covariance matrix of dr can be written as:

[0070] P dr =(F T F) -1 F T (P dA +P X )F(F T F) -1

[0071] in,

[0072]

[0073] The positioning geometric accuracy is:

[0074] GDOP = tr(P dr )=Pd r( 1,1)+P dr (2,2)+P dr (3,3)

[0075] The MATLAB implementation of the positioning algorithm and its effect diagram are shown below: Figure 3 shown.

[0076] The corresponding settlement code is as follows:

[0077]

[0078]

[0079] For the inertial navigation technology, optionally, a complementary filtering algorithm is used to estimate the direction and distance of the object based on the detection values ​​of the accelerometer and the gyroscope to obtain the current position.

[0080] The complementary filtering algorithm includes weighted averaging the detection data of the accelerometer and the gyroscope to obtain a fusion result, estimating the direction and distance of the object based on the fusion result, and obtaining the current position.

[0081] The complementary filtering algorithm compares the fusion results of the accelerometer and gyroscope with the actual value, and uses a PI controller to adjust the fusion results to track the current position of the object.

[0082] The details are as follows:

[0083] Complementary filtering is a simple and intuitive filtering method that fuses gyroscope and accelerometer data by weighted averaging, where the accelerometer is mainly used for long-term attitude stability and the gyroscope is mainly used for short-term attitude response. This weighted average method can provide relatively accurate estimation results without introducing too many complex calculations. The algorithm is as follows:

[0084]

[0085]

[0086]

[0087] 2. Data processing and calculation

[0088] Optionally, the method adopts a Kalman filter fusion algorithm to fuse the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology.

[0089] The fusion process also includes: setting the priority of the Bluetooth base station AOA technology and the inertial navigation technology, and dynamically adjusting the fusion weight of the Bluetooth base station AOA technology and the inertial navigation technology according to the positioning accuracy and delay.

[0090] Specifically, in the previous step, for the Bluetooth base station AOA data, the two-station direction finding positioning algorithm is used to obtain the position. For the inertial navigation data, a complementary filter is used to reduce noise interference and obtain attitude and position estimation. In this step, the Kalman filter fusion algorithm and the extended Kalman filter algorithm are used to perform AOA and inertial navigation fusion positioning to obtain a more accurate position.

[0091] 2.1. Kalman filter fusion process of Bluetooth AoA and inertial navigation:

[0092]

[0093]

[0094]

[0095] The effect after fusion is as follows Figure 4 shown.

[0096] 3. System integration and coordination

[0097] Mainly use multi-threading technology to achieve parallel processing of data;

[0098] In this embodiment, a system platform that is compatible with multiple positioning technologies is designed and implemented. Specifically, the system platform uses the Linux operating system, uses C++ language for programming, and uses multi-threading technology to achieve parallel data processing. At the same time, an effective data fusion and coordination strategy is formulated, for example, setting priorities, dynamically adjusting the weight of data according to the accuracy and delay characteristics of the positioning technology, to achieve optimal data fusion and coordination.

[0099] 4. Path planning and optimization

[0100] Optionally, an A* path planning algorithm is used to calculate the optimal path for path navigation based on the user's target location, map information, and the object's current location information.

[0101] Specifically, the A* path planning algorithm is used to calculate the shortest path from the current location to the target location based on the map information and the current location information. Then, based on the real-time positioning information, the path is dynamically adjusted to avoid obstacles and optimize the navigation path. The above are the specific implementation steps of this embodiment. In this way, high-precision, low-latency indoor positioning, as well as efficient path planning and optimization can be achieved, thereby improving the user's indoor navigation experience.

[0102] 5. Application prospects

[0103] This solution can be widely used in smart home, smart office, virtual reality and other application fields. With the development of science and technology, people's demand for indoor positioning and path planning is increasing, especially in large shopping malls, office buildings, hospitals, underground parking lots and other places. Indoor positioning and path planning technology can provide users with more convenient and accurate navigation services, greatly improving the user experience. At the same time, the application of multi-sensor fusion technology can further improve the accuracy and stability of positioning, making path planning more reasonable and efficient. Therefore, this technical solution has broad market demand and good application prospects.

[0104] The above is an introduction to a method embodiment. The following is a further explanation of the solution of the present invention through a system embodiment.

[0105] This embodiment also provides an indoor path planning system based on multi-positioning fusion, including:

[0106] A Bluetooth base station AOA positioning module is provided with multiple Bluetooth base stations or Bluetooth beacons, and is used to estimate the current position of the object by measuring the signal arrival angle based on the multiple Bluetooth base stations or Bluetooth beacons set;

[0107] An inertial navigation module, which is equipped with an accelerometer and a gyroscope, is used to estimate the direction and distance of an object and obtain the current position based on the measurements of the accelerometer and the gyroscope;

[0108] A data fusion module, used to fuse the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology to obtain the fused current position information;

[0109] A path planning module is used to calculate the optimal path for path navigation based on the user's target location, map information and the current location information of the object, and dynamically adjust the optimal path based on the current location information obtained in real time;

[0110] The computing processing module is used to realize parallel processing of data using multi-threading technology.

[0111] It should be noted that the specific content and beneficial effects of the system of the present application can be found in the above-mentioned method embodiment, which will not be repeated here.

[0112] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. An indoor path planning method based on multi-positioning fusion, characterized in that: The following steps are involved: A variety of sensor technologies are used to obtain indoor location information, including Bluetooth base station AOA technology and inertial navigation technology. The Bluetooth base station AOA technology estimates the current location of an object by measuring the signal arrival angle based on multiple Bluetooth base stations or Bluetooth beacons that are set up; the inertial navigation technology estimates the direction and distance of an object and obtains the current location based on a built-in accelerometer and gyroscope; Fusing the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology to obtain fused current position information; According to the user's target location, map information and the current location information of the object, an optimal path is calculated for path navigation, and the optimal path is dynamically adjusted according to the current location information obtained in real time.

2. The indoor path planning method based on multi-positioning fusion according to claim 1 is characterized in that: The method also includes using multi-threading technology to perform parallel computing on the data processing processes of each sensor technology.

3. The indoor path planning method based on multi-positioning fusion according to claim 1 is characterized in that: The method measures the signal arrival angle of a Bluetooth base station or a Bluetooth beacon through a two-station direction finding positioning algorithm to estimate the current position of the object.

4. The indoor path planning method based on multi-positioning fusion according to claim 1 is characterized in that: The method adopts a complementary filtering algorithm to estimate the direction and distance of an object according to the detection values ​​of an accelerometer and a gyroscope, and obtains the current position.

5. The indoor path planning method based on multi-positioning fusion according to claim 4 is characterized in that: The complementary filtering algorithm includes weighted averaging the detection data of the accelerometer and the gyroscope to obtain a fusion result, estimating the direction and distance of the object based on the fusion result, and obtaining the current position.

6. The indoor path planning method based on multi-positioning fusion according to claim 5 is characterized in that: The complementary filtering algorithm compares the fusion result of the accelerometer and the gyroscope with the actual value, and uses a PI controller to adjust the fusion result to achieve tracking of the current position of the object.

7. The indoor path planning method based on multi-positioning fusion according to claim 1 is characterized in that: The method adopts a Kalman filter fusion algorithm to fuse the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology.

8. The indoor path planning method based on multi-positioning fusion according to claim 1, characterized in that: The fusion process also includes: setting the priority of the Bluetooth base station AOA technology and the inertial navigation technology, and dynamically adjusting the fusion weight of the Bluetooth base station AOA technology and the inertial navigation technology according to the positioning accuracy and delay.

9. The indoor path planning method based on multi-positioning fusion according to claim 1, characterized in that: The method adopts the A* path planning algorithm to calculate the optimal path for path navigation according to the user's target location, map information and the current location information of the object.

10. An indoor path planning system based on multi-positioning fusion, characterized in that: include: A Bluetooth base station AOA positioning module is provided with multiple Bluetooth base stations or Bluetooth beacons, and is used to estimate the current position of the object by measuring the signal arrival angle based on the multiple Bluetooth base stations or Bluetooth beacons set; An inertial navigation module, which is equipped with an accelerometer and a gyroscope, is used to estimate the direction and distance of an object and obtain the current position based on the measurements of the accelerometer and the gyroscope; A data fusion module, used to fuse the current position estimated by the Bluetooth base station AOA technology and the inertial navigation technology to obtain the fused current position information; A path planning module is used to calculate the optimal path for path navigation based on the user's target location, map information and the current location information of the object, and dynamically adjust the optimal path based on the current location information obtained in real time; The computing processing module is used to realize parallel processing of data using multi-threading technology.

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