A method and system for positioning an automatic driving vehicle in a port based on RFID

Abstract

The application discloses a port automatic driving vehicle positioning method and system based on RFID, which comprises the following steps: using the strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver to guide the AGV to reach the vicinity of the specified position, using the GPS navigation system to provide the direction information; when the AGV reaches the specified driving section guided by the GPS, the RFID transceiver sends the signal to the ground calibration to determine the accurate distance between the AGV and the ground calibration, and the AGV reaches the specified ground calibration position through the predetermined trajectory route, i.e. through the sequence of the ground calibration; the RFID transceiver determines the distance between the RFID label and the RFID ground calibration to complete the locking of the final position. The RFID system which is simple and easy to deploy is used to weaken or eliminate the negative influence of the equipment noise, the environmental noise, the signal reflection and the signal shielding on the positioning accuracy, so that the dependence of the system on the environment and the equipment is reduced while the positioning method accuracy is improved, and the practical application requirements of the port AGV positioning are met.

Description

Technical Field

[0001] This invention belongs to the field of autonomous vehicle positioning, and specifically relates to an RFID-based method and system for positioning autonomous vehicles in ports. Background Technology

[0002] In recent years, autonomous driving has developed rapidly due to continuous advancements in environmental perception and vehicle control technologies. Besides providing safety and convenience for daily driving, the application of autonomous driving technology is particularly prominent in industrial scenarios, especially in ports. The introduction of this technology can significantly improve transportation efficiency, reduce labor costs, and ultimately enhance the overall competitiveness of ports. Autonomous vehicles used in ports, namely Automated Guided Vehicles (AGVs), can complete the tasks of receiving and transporting goods and are one of the core units of a port. The scheduling and command execution of AGVs mainly rely on positioning technology to provide real-time location information, enabling AGVs to travel along optimized paths and arrive at predetermined locations on time and accurately. Common AGV positioning technologies are based on electromagnetic induction, vision, infrared, inertial navigation, and satellite technologies. The specific technologies used vary depending on the AGV's application scenario and equipment capabilities. It is also common to use a combination of multiple positioning technologies to mutually assist each other in improving positioning accuracy and completing the positioning task.

[0003] Existing positioning technologies have the following drawbacks and shortcomings: 1) Traditional positioning technologies are subject to strong constraints on the application environment. Outside of these restricted scenarios, positioning accuracy is low, and positioning failures may even occur. For example, vision-based positioning methods are highly dependent on lighting conditions and are not suitable for direct sunlight or dimly lit environments; satellite-based positioning methods require the target location to be in an open space, but containers stacked in ports or cranes can cause strong reflections or even blockages of satellite signals, severely reducing positioning accuracy. 2) Furthermore, some positioning methods require high deployment or maintenance costs. For instance, electromagnetic induction-based methods require extensive deployment of induction cables along the road surface so that AGVs can use electromagnetic induction to determine their location. Such methods require advance design and installation during road paving, resulting in high costs for later additions. While methods based on beacon nodes such as WiFi, Bluetooth, and ultra-wideband radar are easier to deploy, their subsequent maintenance costs are high, such as the need for regular battery replacements and equipment calibration. 3) Existing RFID-based positioning methods are problematic because the signals reflected by RFID tags are sensitive to environmental conditions. Signal reflectors or obstructions around the tags can affect signal strength or phase information, increasing noise and leading to significant positioning errors. This makes existing methods unsuitable for complex and dynamically changing positioning scenarios. 4) Finally, due to the large number and variety of AGVs and RFID positioning devices used in ports, existing methods often assume fixed device types, thus limiting their applicability to port scenarios. In conclusion, there is an urgent need for a low-cost, easy-to-deploy, environmentally compatible, universally applicable, and highly accurate positioning method to improve AGV positioning accuracy and promote the intelligent and efficient development of ports. Summary of the Invention

[0004] The purpose of this invention is to provide an RFID-based positioning method and system for automated guided vehicles (AGVs) in ports. This invention utilizes a simple and easily deployed RFID system to reduce or eliminate the negative impacts of equipment noise, environmental noise, signal reflection, and signal obstruction on positioning accuracy. While improving the accuracy of the positioning method, it reduces the system's dependence on the environment and equipment, meeting the practical application requirements of AGV positioning in ports.

[0005] This invention is achieved through the following technical solution:

[0006] A port autonomous driving vehicle positioning method based on RFID, comprising:

[0007] The AGV is guided to a designated location by using the strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver. This includes: using the GPS navigation system to provide directional information; after the AGV reaches the designated travel section by GPS guidance, the precise distance between the AGV and the ground calibration is determined by sending a signal to the ground calibration via the RFID transceiver; and the AGV reaches the designated ground calibration location by following a predetermined trajectory route, i.e., passing through the ground calibrations in sequence.

[0008] Based on the mutual coupling of RFID tags, the distance between the RFID tag and the RFID ground marker is determined, and the final location is locked.

[0009] As a further improvement of the present invention, the RFID transceiver and transceiver antenna are placed at the front of the AGV, and the RFID tags are placed on both sides of the front of the vehicle and at the bottom of the front of the vehicle. The tags on the front of the vehicle are covered by RFID tag covers, and the covers are open in both the top and bottom directions. The RFID ground marker is placed on the road surface on which the AGV travels, and the RFID ground marker contains RFID tags with known locations inside.

[0010] As a further improvement of the present invention, multiple RFID tags are arranged in an array at the bottom of the AGV front, and the distance between the tags should not be less than half the wavelength of their corresponding signals; the number of RFID tags satisfies the following condition:

[0011] When the number of RFID tags is The width of the bottom of the front of the car is , wavelength is At that time, we obtained:

[0012] .

[0013] As a further improvement of the present invention, the key dimensions of the RFID tag cover meet the following conditions:

[0014] The first Fresnel zone is located between the RFID transceiver antenna and the RFID tag and is elliptical in shape. The distance between the RFID tag and the upper edge of the RFID tag cover is... The distance between the RFID transceiver antenna and the RFID tag cover is ; distance is Position and corresponding ellipse radius is The first Fresnel zone does not coincide with the RFID tag cover space, i.e., the width of the RFID tag cover... , where the distance is The radius of the ellipse corresponding to the position The calculation formula is as follows:

[0015] .

[0016] As a further improvement of the present invention, before the AGV task begins, it also includes: compensating for the noise of the RFID transceiver device;

[0017] First, the AGV is driven to an open and interference-free area to conduct noise measurement. After the noise measurement is completed, the RFID transceiver performs noise compensation on the signal. The compensated signal is used as the true value of the collected signal for the positioning algorithm to use.

[0018] The signal received by the RFID transceiver can be represented as ,So ,in For RFID tag reflected signals, The measured signal change; based on Calculate the impact of equipment noise on the signal. ,in This represents the change in signal due to the transmission path under ideal conditions with no device noise; in an open, interference-free area, the corresponding... , Indicates signal amplitude. The signal phase can be represented by the following formula:

[0019]

[0020]

[0021] in This indicates the transmit power of the RFID transceiver. This indicates the antenna gain of the RFID transceiver antenna. This indicates the antenna gain of the RFID tag. Indicates the distance between the RFID transceiver and the RFID tag. As intermediate variables, these represent integer multiples of the wavelength corresponding to the signal propagation distance; all the above variable parameters are known quantities. The impact of equipment noise on the signal... pass Obtain;

[0022] While the AGV is in motion, the RFID transceiver acquires real-time signal changes by eliminating equipment noise. .

[0023] As a further improvement to the present invention, the measurement process also includes compensation for environmental noise of the RFID transceiver:

[0024] The RFID transceiver antenna communicates with the tag inside the RFID tag housing, receiving signals from two paths: the direct path and the road surface reflection path. The impact of these paths on the signal is expressed as follows: and The signal that has a path between the RFID transceiver antenna and the RFID ground calibration is... When the aforementioned covering exists on the ground, since the covering mainly affects signal strength but not signal transmission path length, it is represented as... and ,in , , and These represent the corresponding changes in signal strength values;

[0025] When the AGV travels on a road with unknown surface coverings, the signal changes observed by its RFID transceiver between the RFID transceiver antenna and the RFID tag are as follows: ,in This is noise that cannot be easily removed; it is determined by solving the following optimization equation. The possible values ​​of:

[0026]

[0027] The value of is a constant. When the AGV is equipped with multiple RFID tags, the voting algorithm is used to complete the process. Determining the value; when the number of RFID tags is The corresponding cover options are: ;exist and Once confirmed, the RFID transceiver can measure the... Restore ,Right now Used for vehicle positioning.

[0028] As a further improvement of the present invention, the measurement process also includes compensation for reflected signal interference in the environment:

[0029] Multiple RFID tags are deployed on both sides of the front of the AGV to detect the strength of the reflection path;

[0030] In the case of using RFID ground calibration on both sides for positioning strategy, only the RFID ground calibration signal from the side with no strong reflection path is used. In the case where there is no strong reflection path on both sides, the RFID ground calibration signals from both sides are used. The final positioning result is represented by the average value.

[0031] Strong reflection paths exist on both sides, so a fixed-point high-frequency sampling method is used:

[0032] Fixed-point sampling refers to the RFID transceiver determining the sampling interval based on the real-time travel speed of the AGV. The sampling interval is calculated every time the AGV travels. At a distance, the RFID transceiver sends a request signal towards the RFID ground marker; high frequency refers to the RFID transceiver sending a request signal with a significantly shorter period than in typical scenarios, specifically the sampling time interval. ,in This refers to the vehicle's speed.

[0033] As a further improvement of the present invention, the distance between the AGV and the ground is specified. The calculation method is as follows:

[0034] First, use intensity information for coarse-grained positioning, guiding the AGV to a range approximately equal to a wavelength calibrated on the ground, and then use this to determine the approximate distance. :

[0035]

[0036] Then, the phase information is used to determine the precise location information, that is, the precise distance is determined using the following formula. :

[0037]

[0038] Using the state update function in the Kalman filter to adjust the distance The update will be performed, and the specific calculation method is as follows:

[0039]

[0040] in This indicates the current distance calculation result. This is the value calculated from the previous distance. Determined by parameter value The degree of confidence in the current results. .

[0041] As a further improvement of the present invention, the step of determining the distance between the RFID tag and the RFID ground marker based on the mutual coupling effect of RFID tags to complete the final location locking includes:

[0042] When the AGV determines that it has reached the target location range, it initiates final position locking. The AGV then begins searching for the target in the nearby area with the target location as the radius. During the search, the AGV moves its current position in small increments of centimeters, with the next movement direction being the direction of signal strength enhancement. When the RFID transceiver detects numerous signal strength changes, it determines that the AGV is within the set distance of the RFID ground calibration, and the final position locking is considered successful. If the AGV fails to achieve final locking after multiple moves, the maximum number of moves is limited to the target location, while maintaining positioning accuracy within the target location.

[0043] An RFID-based positioning system for automated driving vehicles in ports, comprising:

[0044] The guidance module is used to guide the AGV to a designated location by using the strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver. This includes: using the GPS navigation system to provide directional information; after the AGV reaches the designated travel section under GPS guidance, the precise distance between the AGV and the ground calibration is determined by sending a signal to the ground calibration via the RFID transceiver; and the AGV reaches the designated ground calibration position by following a predetermined trajectory route, i.e., passing through the ground calibrations in sequence.

[0045] The locking module is used to determine the distance between the RFID tag and the RFID ground marker based on the mutual coupling of the RFID tags, and to complete the final position locking.

[0046] Compared with the prior art, the present invention has the following beneficial technical effects:

[0047] This invention utilizes RFID technology for AGV positioning. The RFID-based AGV positioning system deployment scheme prioritizes low cost and ease of deployment, and is tailored to the practical application environment of ports. It proposes a positioning strategy combining AGV and RFID, improving positioning accuracy to the centimeter level, with optimal accuracy reaching 2 centimeters. The invention employs measurement and compensation strategies for equipment noise, environmental noise, and reflected signal interference in port application scenarios, fundamentally reducing the impact of complex port conditions on the positioning algorithm and ensuring accurate positioning. It does not increase the complexity of the method while maintaining vehicle positioning accuracy. This method reduces the dependence of the positioning method on the environment, enabling operation in adverse scenarios such as rain, snow, or low light conditions; reduces deployment and maintenance costs by using extremely low-cost RFID tags for location information acquisition; reduces the impact of environmental noise, making it suitable for application scenarios where the position and quantity of personnel, vehicles, equipment, and containers within ports change dynamically; reduces the impact of equipment noise, improving equipment adaptability and reducing reliance on specialized equipment; and comprehensively improves positioning accuracy, ultimately achieving centimeter-level high-precision positioning results. Attached Figure Description

[0048] Figure 1 Flowchart of a port autonomous vehicle positioning method based on RFID;

[0049] Figure 2 This is a schematic diagram of the application environment;

[0050] Figure 3 A schematic diagram showing the key dimensions of an RFID tag cover;

[0051] Figure 4 This is a schematic diagram of road surface reflection.

[0052] Figure 5 This is a diagram illustrating the reflection from roadside containers.

[0053] Figure 6 This is a diagram illustrating vehicle guidance and positioning.

[0054] Figure 7 Flowchart of a 100-positioning system for RFID-based automated driving vehicles in ports;

[0055] Among them, 100 is an autonomous vehicle; 101 is an RFID transceiver; 102 is an RFID transceiver antenna; 103 is an RFID tag; 104 is an RFID tag protective cover; 200 is an RFID ground tag; 201 is a left-side RFID ground tag; 202 is a right-side RFID ground tag; 2011 is a left-side first RFID ground tag; 2012 is a left-side second RFID ground tag; 2021 is a right-side first RFID ground tag; 2022 is a right-side second RFID ground tag; 300 is a roadside container; and 400 is the road surface on which the vehicle travels. Detailed Implementation

[0056] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0057] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0058] Vocabulary Explanation:

[0059] RFID: Radio-Frequency Identification, is a technology that typically consists of an identification tag and a reader (RFID transceiver 101). The identification tag is attached to the object being identified and has a globally unique identifiable code. The reader communicates with the identification tag wirelessly to obtain the identification code and complete the identification of the object.

[0060] AGV: Automated Guided Vehicle. Supported by autonomous driving technology, it is commonly used in industrial settings such as ports, factories, and warehouses to transport goods.

[0061] Assisted high-precision positioning: providing location information for the target being located. Port autonomous vehicles often use technologies such as electromagnetic induction, vision, infrared, inertial navigation, and satellite to provide relative or absolute position information of the target. Here, high precision refers to positioning error at the centimeter level.

[0062] like Figure 1 The first objective of this invention is to provide an RFID-based method for locating automated port vehicles 100, comprising:

[0063] The AGV is guided to a designated location by using the strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver 101. This includes: using the GPS navigation system to provide directional information; after the AGV reaches the designated travel section under GPS guidance, the precise distance between the AGV and the ground calibration is determined by sending a signal to the ground calibration via the RFID transceiver 101; and the AGV reaches the designated ground calibration location by following a predetermined trajectory route, i.e., passing through the ground calibrations in sequence.

[0064] Based on the mutual coupling of RFID tag 103, the distance between RFID tag 103 and the RFID ground calibration is determined, and the final position is locked.

[0065] This invention utilizes a simple and easily deployable RFID system to reduce or eliminate the negative impact of equipment noise, environmental noise, signal reflection, and signal blockage on positioning accuracy. While improving the accuracy of the positioning method, it reduces the system's dependence on the environment and equipment, thus meeting the practical application requirements of port AGV positioning.

[0066] The present invention will be further described in detail below with reference to specific embodiments. These descriptions are for explanation purposes only and are not intended to limit the scope of the invention.

[0067] In one embodiment of the present invention, the RFID-based port autonomous driving vehicle 100 positioning method includes designing a high-precision positioning system for the port autonomous driving vehicle 100, the high-precision positioning system for the port autonomous driving vehicle 100 including an RFID transceiver 101, an RFID transceiver antenna 102, an RFID tag 103, and an RFID ground calibration.

[0068] The application environment involved in this invention is illustrated as follows: Figure 2 The system includes one automated guided vehicle (AGV) 100, which travels on port roads with metal containers stacked on the sides. The road surface is made of cement or asphalt. An RFID transceiver 101 and its antenna are located at the front of the vehicle. RFID tags 103 are placed on both sides of the front of the vehicle and at the bottom of the front. The tags on the front are enclosed in a protective cover that isolates external interference signals and prevents significant signal reflection from the tags. The cover is open both top and bottom, with no obstructions between the RFID transceiver antenna 102 and the RFID tags 103. An RFID ground marker is placed on the AGV's path. This marker is made of a specially designed pressure-resistant and waterproof material, and its interior contains RFID tags 103 with known locations. This invention provides the AGV with centimeter-level location information.

[0069] One embodiment of the present invention includes the following steps:

[0070] I. Determine the deployment location of the RFID tag 103 at the bottom of the AGV front and the key dimensions of the RFID tag 103 cover. This step relies primarily on the following two important theoretical and practical bases:

[0071] 1) When two RFID tags 103 are close together, the electromagnetic fields near the tags interfere with each other, i.e., mutual coupling occurs. Based on this, the RFID transceiver 101 can determine the distance between the RFID tag 103 and the RFID ground calibration by analyzing the occurrence of this phenomenon, achieving centimeter-level positioning accuracy. In specific deployments, the optimal distance between the RFID tag 103 and the ground is no more than 2 centimeters. Simultaneously, to increase the detection area and accuracy of the positioning system, multiple RFID tags 103 can be arranged in an array at the bottom of the vehicle. The number of tags is not necessarily better the more there are; the distance between any two tags is mainly determined by two factors: avoiding mutual coupling and ensuring the independence of tag signals. Therefore, the optimal distance between tags should be no less than half the wavelength of their respective signals.

[0072] Specifically, when the number of RFID tags is 103 The width of the bottom of the front of the car is , wavelength is At that time, we can obtain:

[0073]

[0074] For example, if the response signal frequency of RFID tag 103 is 920MHz, that is, the wavelength... If the distance is centimeters, then the corresponding label spacing is approximately 16 centimeters, which is for the width of the vehicle front. For AGVs of up to meters, up to 103 RFID tags.

[0075] 2) The line-of-sight range between the transmitting and receiving ends of the electromagnetic signal should be kept as open as possible to avoid interference with the signal and affecting positioning accuracy.

[0076] The aforementioned line-of-sight range is typically defined as the first Fresnel zone, such as... Figure 3 As shown, the first Fresnel zone is located between the RFID transceiver antenna 102 and the RFID tag 103 and is elliptical in shape. The distance between the RFID tag 103 and the upper edge of the RFID tag 103 cover can be defined as... The distance between the RFID transceiver antenna 102 and the protective cover of the RFID tag 103 is Therefore, it is necessary to ensure that... Figure 3 Mid-range is Position and corresponding ellipse radius is The first Fresnel zone does not coincide with the space of the RFID tag 103 cover, i.e., the width of the RFID tag 103 cover. , where the distance is The radius of the ellipse corresponding to the position The calculation formula is as follows:

[0077]

[0078] For example, if the distance between the RFID transceiver antenna 102 and the RFID tag 103... It is 3 meters. When it is 0.5 meters, If the width is in centimeters, then the width of the RFID tag's 103 shield can be obtained. It must be no less than centimeter.

[0079] II. Measurement and Compensation of RFID Transceiver 101 Equipment Noise. For commercial applications, RFID transceivers 101 and RFID tags 103 used in ports often employ low-cost equipment. However, the internal components of such equipment generate a certain amount of equipment noise, which affects signal characteristics. The equipment noise generated by different models of equipment varies. At the same time, low-cost equipment is more sensitive to changes in environmental conditions such as temperature and humidity, and the equipment noise will change with the environment, thereby reducing positioning accuracy.

[0080] To address the aforementioned issues, this invention introduces a noise measurement and compensation mechanism. Before the AGV begins its task, it must be driven to an open, interference-free area for noise measurement. After the noise measurement is completed, the RFID transceiver 101 performs noise compensation on the signal. The compensated signal can then be used as the true value of the acquired signal for the positioning algorithm. Ground environmental noise is not considered here; that is, it is assumed that the open area is clean and free of debris.

[0081] Specifically, the signal received by RFID transceiver 101 can be represented as ,So ,in The signal reflected by RFID tag 103 The measured signal change. From this point on, we can... Calculate the impact of equipment noise on the signal. ,in This represents the change in signal due to the transmission path under ideal conditions with no device noise. In an open, interference-free area, the corresponding... , Indicates signal amplitude. The signal phase can be represented by the following formula:

[0082]

[0083]

[0084] in This indicates the transmit power of the RFID transceiver 101. This indicates the antenna gain of the RFID transceiver antenna 102. This indicates the antenna gain of RFID tag 103. This indicates the distance between the RFID transceiver 101 and the RFID tag 103. As an intermediate variable representing an integer multiple of the wavelength corresponding to the signal propagation distance, all the above variable parameters are known quantities. So, what is the impact of device noise on the signal? It is possible Acquisition. While the AGV is in motion, the RFID transceiver 101 can acquire real-time signal changes by eliminating equipment noise. This is to serve the positioning algorithm.

[0085] It should be noted that for port conditions where temperature and humidity changes are not significant, such as a temperature difference of no more than 5°C and a humidity change of no more than 20%, the noise measurement of the RFID transceiver 101 device can be performed every 3-5 hours. However, for port conditions where temperature and humidity changes are significant, the measurement interval should be reduced to 1-2 hours.

[0086] III. Measurement and Compensation of Environmental Noise for RFID Transceiver 101. In port application environments, the ground where AGVs travel is not always clean; it is often covered by rain, snow, ice, oil, dust, etc. These coverings significantly affect wireless signals, mainly through signal attenuation. Therefore, to reduce the impact of this environmental noise on positioning accuracy, it is necessary to measure the noise and propose a compensation mechanism.

[0087] Road surface reflection conditions such as Figure 4 As shown, the RFID transceiver antenna 102 communicates with the tag in the RFID tag 103 housing and can receive signals from two paths: the direct path and the road surface reflection path. The effect of these paths on the signal can be expressed as follows: and The RFID transceiver antenna 102 and the RFID ground calibration have a signal that has a path between them. When the aforementioned covering exists on the ground, the aforementioned... and The signal will be significantly affected, and its corresponding value will change accordingly. Since the covering mainly affects the signal strength but not the signal transmission path length, the changed variable can be expressed as follows: and ,in , , and These represent the corresponding signal strength value changes. It is worth noting that this invention primarily focuses on the impact of the physical properties of the covering material on the signal in real-world scenarios, without considering the influence of material thickness; that is, a natural assumption of a covering thickness of 1-3 cm is made. This invention does not consider scenarios where the covering material is excessively thick, such as when there is heavy snow cover, AGV vehicles typically cannot operate safely. Based on the above analysis, the following information regarding the signal strength can be established by manually adding and removing covering material during measurement. and Table showing the correspondence between numerical relationships:

[0088] Table 1. Comparison of Signal Attenuation by Coverage

[0089]

[0090] After the relation table is established, when the AGV travels on a road with unknown road surface covering, the signal changes of the RFID transceiver antenna 102 and RFID tag 103 that can be observed by its RFID transceiver 101 are as follows: ,in For noise that cannot be easily eliminated, such as thermal noise from equipment, it can be determined by solving the following optimization equation. The possible values ​​of:

[0091]

[0092] Then, referring to Table 1, we can obtain... The value can be determined by a voting algorithm when the AGV is equipped with multiple RFID tags 103. Determining the value enhances The accuracy. That is, when the number of RFID tags is 103... The corresponding cover options are: For each tag, a corresponding cover can be selected from Table 1. The vote for that cover is incremented by 1. The option with the most votes in the end is... A definite value. In and Once confirmed, the RFID transceiver 101 can detect the measured data. Restore ,Right now This value can be used for more accurate vehicle positioning. It is worth noting that this method uses formula (5) as the classification method for the corresponding cover. In the method extension, algorithms such as k-means can also be used to improve the classification accuracy. However, it should also be recognized that such algorithms will significantly increase the algorithm complexity, which may make them unsuitable for application scenarios based on low-cost devices.

[0093] IV. Measurement and Compensation for Environmental Reflection Signal Interference. When the AGV travels along port roads, the metal containers stacked on both sides of the road can significantly affect RFID signals. A diagram illustrating the reflection from the roadside containers is shown below. Figure 5 The RFID transceiver antenna 102 and the line-of-sight communication paths between the tags carried on the AGV and the RFID ground markings are all affected by reflected signals, impacting positioning accuracy. In particular, the port environment is highly variable, with the location and quantity of stacked containers changing dynamically, further leading to diverse variations in RFID-related signals and making positioning accuracy difficult to control.

[0094] To address the aforementioned issues, the present invention employs the following method to measure and compensate for the interference of reflected signals caused by the roadside container 300: First, for the area covered by the reflected signal, the signal received by the RFID transceiver 101 is a combination of multiple signals that are superimposed in space, resulting in signal enhancement or weakening.

[0095] Based on this, the present invention deploys multiple RFID tags 103 on both sides of the front of the AGV to detect the strength of the reflection path and thus implement corresponding strategies. Specifically, when the AGV travels from an open area to the area to be located, the signal strength values ​​of the signals returned from the left and right RFID tags 103 received by the RFID transceiver 101 can be observed. Without loss of generality, when the change in strength value reaches 30%, it can be determined that a strong reflection path has appeared on the left or right side of the AGV; correspondingly, when the change in the signal strength value returned from the RFID tags 103 on both sides is within 30%, there is no strong reflection path on either side; finally, when the change in strength value on both sides is greater than 30%, there is a strong reflection path on both sides.

[0096] For the above scenarios, when using RFID ground calibration on both sides for positioning, this method can utilize only the RFID ground calibration signal from the side without a strong reflection path. If there are no strong reflection paths on either side, both RFID ground calibration signals can be used simultaneously, and the final positioning result is represented as the average. For the most challenging scenario, where strong reflection paths exist on both sides, this method proposes a fixed-point high-frequency sampling approach to solve this problem. "Fixed-point" means that the RFID transceiver 101 determines the sampling interval based on the AGV's real-time travel speed; the sampling interval is equal to the time it takes for the AGV to travel... When the distance is specified, the RFID transceiver 101 sends a request signal towards the RFID ground calibration; the corresponding so-called high frequency refers to the RFID transceiver 101 sending a signal request with a period significantly shorter than the usual scenario (1 second), specifically the sampling time interval is... ,in This refers to the vehicle's speed. For example, when the vehicle's speed is 10 km / h (approximately 3 m / s), then... This method allows for the use of high sampling rate requests only in specific scenarios, i.e., dynamically adjusting the sampling rate. While ensuring positioning accuracy, it reduces data packet collisions caused by excessive data packets in space, thus improving system operating efficiency from a macro perspective.

[0097] V. Vehicle Guidance and Positioning Based on Signal Strength and Phase. Through the preceding steps, this invention has effectively eliminated multiple interferences and noises in complex positioning scenarios. Subsequently, this invention utilizes the strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver 101 to guide the AGV to the vicinity of a designated location. Generally, AGVs have built-in GPS (Global Positioning System) navigation systems, but the accuracy of such navigation systems decreases significantly under port conditions. Based on this reality, this invention can utilize the GPS navigation system to provide approximate location information, such as the direction of travel and a rough travel path, while the positioning and guidance method proposed in this invention provides centimeter-level high-precision positioning information.

[0098] Specifically, such as Figure 6 As shown, after the AGV arrives at the designated travel section guided by GPS, the precise distance between the AGV and the ground marker can be determined by sending a signal to the ground marker via the RFID transceiver 101. Then, following the predetermined trajectory route, i.e., passing through the ground markers in sequence, the AGV can accurately reach the designated ground marker position. The distance between the AGV and the ground marker is shown here. The judgment formula can be obtained based on the variations of formulas 3 and 4. As can be seen from formulas 3 and 4, the distance information is directly related to both the signal strength and phase. However, after actual research on RFID systems, it was found that the distance information given by the strength information is coarser than that given by the phase information, that is, the position information based on the signal strength is less accurate. At the same time, although the phase information is more accurate, the phase information is ambiguous, that is, the phase information can only describe the positioning information within a wavelength distance, but cannot accurately describe how many wavelength intervals exist in the actual distance. Therefore, this invention first uses the strength information for coarse-grained positioning, guides the AGV to a range of approximately one wavelength length calibrated on the ground, and then uses formula (6) to judge the coarse distance. Then, phase information can be used to determine more accurate location information, that is, the precise distance can be determined using formula (7). .

[0099]

[0100]

[0101] As mentioned in the preceding steps, the sampling rate of the RFID transceiver 101 varies with environmental changes. To improve positioning accuracy by utilizing high sampling information, this invention employs the state update function in a Kalman filter to adjust the distance. This update method fully utilizes the sampled information and, due to its single-step execution and low complexity, does not significantly increase computational or storage complexity. The specific calculation method is as follows:

[0102]

[0103] in This indicates the current distance calculation result. This is the value calculated from the previous distance. Determined by parameter value The degree of confidence in the current results. For scenarios with large measurement errors, it can be Moving closer to 0 can be beneficial for scenarios with small measurement errors. To approach a value of 1 without loss of generality, we can... As The default value.

[0104] VI. Final Position Locking. By executing the above steps, the AGV can travel to the expected location area, with a positioning accuracy expected to reach approximately 10 cm. To further improve the positioning accuracy to approximately 2 cm, this method utilizes the aforementioned mutual coupling phenomenon of RFID tags 103 to achieve final position locking. Specifically, when the AGV determines that it has reached within 10 cm of the target location, final position locking can be initiated. The AGV begins searching for the target in the nearby area with a radius of 10 cm. During the search process, the AGV moves its current position slightly in centimeters, with the next movement direction being the direction of signal strength enhancement. When the RFID transceiver 101 detects a signal strength change exceeding 3 dB, it is determined that the AGV is within 2 cm of the RFID ground calibration, thus confirming the successful final position locking. In the worst-case scenario, if the AGV fails to achieve final locking after multiple moves, a maximum attempt limit of 10 moves is set, still maintaining a positioning accuracy within 10 cm.

[0105] like Figure 7 As shown, the present invention also provides an RFID-based positioning system for automated port vehicles 100, comprising:

[0106] The guidance module is used to guide the AGV to a designated location by using the strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver 101. This includes: using the GPS navigation system to provide orientation information; after the AGV reaches the designated travel section by GPS guidance, the precise distance between the AGV and the ground calibration is determined by sending a signal to the ground calibration via the RFID transceiver 101; and the AGV reaches the designated ground calibration position by following a predetermined trajectory route, i.e., passing through the ground calibration in sequence.

[0107] The locking module is used to determine the distance between the RFID tag 103 and the RFID ground calibration based on the mutual coupling of the RFID tag 103, and to complete the final position locking.

[0108] The present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the RFID-based port automated driving vehicle 100 positioning method.

[0109] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the RFID-based port automated driving vehicle 100 positioning method.

[0110] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for positioning an RFID-based port automated guided vehicle, characterized in that, Comprise: Before the AGV task starts, it also includes compensating for the noise of the RFID transceiver device; Firstly, the AGV is driven to an open and undisturbed area to carry out noise measurement, and after the noise measurement is completed, the RFID transceiver compensates for the noise of the signal, and the compensated signal is used as the true value of the collected signal for the positioning algorithm; The signal received by the RFID transceiver can be represented as Then where is the signal reflected by the RFID tag, is the measured signal change; based on the effect of the device noise on the signal is calculated where represents the change in the signal caused by the transmission path in an ideal situation without device noise; in an open, interference-free area, the corresponding , represents the signal amplitude, represents the signal phase, which can be obtained from the following equation: wherein represents the transmission power of the RFID transceiver, represents the antenna gain of the RFID transceiver antenna, represents the antenna gain of the RFID tag, represents the distance between the RFID transceiver and the RFID tag, as an intermediate variable represents the signal propagation distance corresponding to an integer multiple of the wavelength, the above variable parameter configurations are all known quantities; the influence of the device noise on the signal by acquisition; When the AGV is running, the RFID transceiver acquires real-time signal change conditions by eliminating equipment noise, that is ; During the noise measurement process, the noise of the RFID transceiver environment is also compensated: The RFID transceiver antenna communicates with the tag in the RFID tag shield receiving signals from two paths, i.e. direct path and road surface reflection path, whose effects on the signals are represented as and ; the RFID transceiver antenna communicates with the RFID ground tag receiving signals from one path, i.e. ; when the ground has a cover, since the cover mainly affects the signal strength but not the signal transmission path length, it is represented as and , where , , and represent the corresponding signal strength value changes, respectively. When the AGV travels on a road with unknown road coverings, the signal changes observed by the RFID transceiver of the AGV between the RFID transceiver antenna and the RFID tags are: ; wherein is noise that is not easily removed; the value of is determined by solving the optimization equation is constant, when the AGV is equipped with multiple RFID tags, the value of is determined by voting algorithm ; when the number of RFID tags is , the optional items corresponding to the cover are ; after and are determined, the RFID transceiver can restore from the measured , i.e. , for vehicle positioning; During the noise measurement process, the reflected signal interference in the environment is also compensated: Multiple RFID tags are deployed on both sides of the front body of the AGV to detect the strength of the reflection path; For the case of using two-sided RFID ground calibration to carry out positioning strategy, only the RFID ground calibration signal from the side without strong reflection path is used, and for the case of both sides without strong reflection path, the two-sided RFID ground calibration signal is used, and the final positioning result is expressed in the form of average value; For the case of both sides having strong reflection path, the fixed high-frequency sampling method is adopted: The fixed point refers to that the RFID transceiver determines the sampling interval according to the real-time driving speed of the AGV, and the sampling time interval is AGV every driving distance, the RFID transceiver faces the RFID ground calibration and sends a request signal; the high frequency refers to that the RFID transceiver sends a signal request obviously lower than the commonly used scene, and the specific sampling time interval is , wherein is the driving speed of the vehicle; The strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver are used to guide the AGV to reach the specified position, including: using the azimuth information provided by the GPS navigation system; when the AGV reaches the specified driving section guided by the GPS, the accurate distance between the AGV and the ground calibration is determined by sending a signal from the RFID transceiver to the ground calibration, and the AGV reaches the specified ground calibration position through the predetermined trajectory route, that is, through the sequence of the ground calibration in turn. Based on the mutual coupling effect of the RFID tags, the distance between the RFID tags and the RFID ground calibration is determined to complete the final position locking.

2. The RFID-based port automated guided vehicle positioning method according to claim 1, wherein, The RFID transceiver and the transceiving antenna are placed at the front of the AGV, the RFID tags are placed on both sides of the front body and the bottom of the front of the AGV, wherein the front body tags are wrapped by an RFID tag shield, and the upper and lower directions of the shield are open; the RFID ground calibration is placed on the AGV driving surface, and the inside of the RFID ground calibration is a RFID tag with known position.

3. The RFID-based port automated guided vehicle positioning method according to claim 2, wherein, The AGV front bottom is arranged in an array form with multiple RFID tags, and the distance between the tags should be no less than half the wavelength of the corresponding signal; the number of RFID tags satisfies the following conditions: When the number of RFID tags is , the width of the bottom of the vehicle head is , and the wavelength is , the following is obtained: 。 4. The RFID-based port automated guided vehicle positioning method according to claim 2, wherein, The key size of the RFID tag shield satisfies the following conditions: The first field is located between the RFID transceiver antenna and the RFID tag and is elliptical, the distance between the RFID tag and the upper side edge of the RFID tag shield is , the distance between the RFID transceiver antenna and the RFID tag shield is ; the distance is , the position and the corresponding elliptical radius is The first field with the distance of , wherein the distance is , the position corresponding to the elliptical radius The calculation formula is as follows: 。 5. The RFID-based port automated guided vehicle positioning method according to claim 1, wherein, The AGV and the ground calibrated distance The calculation method is as follows: First, the intensity information is used to perform coarse positioning, and the AGV is guided to a ground mark within an approximate wavelength length range, and the following judgment is used to determine the rough distance : After that, the phase information is used to determine the accurate position information, i.e. to determine the accurate distance by using the following formula : The distance is updated using the state update function in the Kalman filter as follows: d = d + K (z - H d) wherein, is the wavelength, denotes the current distance calculation result, is the previous distance calculation value, is the parameter value decision the degree of trust in the current result, .

6. The RFID-based port automated guided vehicle positioning method according to claim 1, wherein, Based on the mutual coupling effect of the RFID tags, the distance between the RFID tags and the RFID ground calibration is determined to complete the final position locking, including: When the AGV determines that it has reached the target position range, the final position locking is started, and the AGV starts to search for the target position in the nearby area with the target position as the radius; during the search process, the AGV moves the current position by a small amplitude in centimeters, and the next moving direction is the direction with enhanced signal strength; when the RFID transceiver detects that the signal strength changes more than the set value, it is determined that the RFID ground calibration is within the set distance, and the final position locking result is determined; if the AGV fails to achieve the final locking through multiple movements, the maximum attempt limit is the target number of movements, and the positioning accuracy within the target position is still retained.

7. An RFID-based port automated guided vehicle positioning system, characterized by, Comprise: The guiding module is used for guiding the AGV to reach the vicinity of the specified position by using the strength and corresponding phase information of the RFID ground calibration signal received by the RFID transceiver, and comprises: providing the orientation information by using the GPS navigation system; when the AGV reaches the specified travel section by the GPS guidance, judging the accurate distance between the AGV and the ground calibration by the signal transmission mode of the RFID transceiver to the ground calibration, and guiding the AGV to reach the specified ground calibration position by the predetermined trajectory route, i.e. sequentially passing through the sequence of the ground calibration; The locking module is used for determining the distance between the RFID tag and the RFID ground calibration based on the mutual coupling effect of the RFID tag, and completing the locking of the final position; Before the AGV task starts, it further comprises: compensating the noise of the RFID transceiver device; The AGV is first driven to the open and undisturbed area to carry out the noise measurement, after the noise measurement is completed, the RFID transceiver compensates the signal, and the compensated signal is used as the true value of the collected signal for the positioning algorithm; The signal received by the RFID transceiver can be represented as Then where is the reflected signal from the RFID tag, is the measured signal change; based on the effect of the device noise on the signal is calculated where represents the change in the signal due to the transmission path in an ideal situation without device noise; in an open, interference-free area, the corresponding , represents the signal amplitude, represents the signal phase, which can be obtained from the following equation: wherein represents the transmission power of the RFID transceiver, represents the antenna gain of the RFID transceiver antenna, represents the antenna gain of the RFID tag, represents the distance between the RFID transceiver and the RFID tag, as an intermediate variable represents the signal propagation distance corresponding to an integer multiple of the wavelength, the above variable parameter configurations are all known quantities; the influence of the device noise on the signal by acquisition; When the AGV is running, the RFID transceiver acquires real-time signal change conditions by eliminating equipment noise, that is ; The noise measurement process further comprises compensating the environmental noise of the RFID transceiver: The RFID transceiver antenna communicates with the tag in the RFID tag shield receiving signals from two paths, i.e. direct path and road surface reflection path, whose effects on the signals are represented as and ; the RFID transceiver antenna communicates with the RFID ground tag receiving signals from one path, i.e. ; when the ground has a cover, since the cover mainly affects the strength of the signal but not the transmission path length of the signal, it is represented as: and wherein , , and represent the corresponding signal strength value changes, respectively. When the AGV travels on a road with unknown road coverings, the signal changes of the RFID transceiver antenna and the RFID tag observed by the RFID transceiver of the AGV are: ; wherein, is noise that is not easily removed; the value of is determined by solving the following optimization equation: is a constant, when the AGV is equipped with multiple RFID tags, the value of is determined by voting algorithm ; when the number of RFID tags is , the optional items corresponding to the cover are ; after and are determined, the RFID transceiver can restore from the measured , that is , for vehicle positioning; The noise measurement process further comprises compensating the reflected signal interference in the environment: A plurality of RFID tags are arranged on both sides of the front body of the AGV to detect the strength of the reflected path; For the positioning strategy using the RFID ground calibration on both sides, only the RFID ground calibration signal from the side without strong reflected path is used, for the case without strong reflected path on both sides, the RFID ground calibration signals on both sides are used, and the final positioning result is expressed in the form of mean value; For the case that there are strong reflected paths on both sides, the fixed-point high-frequency sampling mode is adopted: The fixed point refers to that the RFID transceiver determines the sampling interval according to the real-time driving speed of the AGV, and the sampling time interval is AGV every driving distance, the RFID transceiver faces the RFID ground calibration and sends a request signal; the high frequency refers to that the RFID transceiver sends a signal request obviously lower than the commonly used scene, and the specific sampling time interval is , wherein is the driving speed of the vehicle.

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