Electric vehicle identity recognition and multiple positioning method for charging robot

Abstract

The invention discloses an electric vehicle identity recognition and multiple positioning method for a charging robot, and belongs to the technical field of intelligent charging. The method comprises the following steps: S1, carrying out identity recognition and Bluetooth preliminary positioning; s2, visual identity rechecking; s3, performing visual accurate positioning; s4, satellite flash positioning and identity re-checking; and S5, confirming the state of the charging port. According to the invention, seamless identity recognition and multi-precision positioning are realized, and the reliability, the success rate and the full-automatic experience of automatic charging are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging, and in particular to a method for electric vehicle identification and multi-location for charging robots. Background Technology

[0002] With the increasing popularity of electric vehicles, the demand for automated, intelligent, and safe charging is growing. As a key piece of equipment for unattended charging services, the core challenge of automated charging robots lies in how to accurately and reliably identify vehicle identities, confirm charging needs, and precisely locate the charging port after the vehicle is parked, so as to automatically plug and unplug the charging gun.

[0003] Currently, existing technical solutions have significant shortcomings: (1) Single RFID or Bluetooth identification solutions: These can only complete identity recognition, but cannot provide accurate location information, or the positioning accuracy provided based on Bluetooth signal strength indication is low, easily affected by environmental interference, and cannot directly guide the robotic arm to perform precise insertion and removal operations. (2) Pure vision positioning solutions: Although they can provide high positioning accuracy, they cannot independently complete identity recognition. In addition, under complex lighting conditions (such as strong light, backlight, and dim light), their recognition success rate and positioning accuracy will decrease significantly, and the system robustness is insufficient. (3) Mechanical structure guidance solutions: These solutions use physical guide grooves and other methods to force alignment, which completely depends on the user's parking accuracy and cannot perform identity recognition and intelligent positioning. This solution has a complex mechanical structure, is easily worn, has poor applicability, and lacks intelligence.

[0004] Therefore, there is an urgent need in this field for a comprehensive solution that can integrate the advantages of multiple technologies, work collaboratively at different stages and with different levels of precision, obtain charging needs when the user is parking, and achieve high reliability and high precision identification and positioning under various operating conditions. Summary of the Invention

[0005] To address the existing problems, this invention provides a method for electric vehicle identification and multi-location for charging robots, the specific solution of which is as follows:

[0006] A method for electric vehicle identification and multi-location for charging robots includes the following steps:

[0007] S1. Identity Recognition and Preliminary Bluetooth Positioning: The charging control system of the charging robot establishes a Bluetooth connection with the electric vehicle that enters the communication range through its Bluetooth module to perform identity authentication; after successful authentication, it obtains the charging demand and performs preliminary area positioning of the electric vehicle based on the Bluetooth signal strength, and then activates the robotic arm control system to perform self-check.

[0008] S2. Visual Identity Verification: The robotic arm control system captures the license plate image of the electric vehicle through the visual monitoring unit, and further confirms the identity of the electric vehicle using the color and number of the license plate;

[0009] S3. Visual Precision Positioning: The robotic arm control system captures images of the electric vehicle through a visual monitoring unit and uses a pre-trained deep learning model to identify and position the electric vehicle's charging port.

[0010] S4. Star Flash Positioning and Identity Verification: After receiving a valid parking signal, the charging control system communicates with one or more pre-installed star flash beacons on the electric vehicle through its star flash module to reconfirm the electric vehicle's identity and calculate the relative distance and orientation data between the charging robot and the electric vehicle based on the star flash beacons.

[0011] S5. Charging Port Status Confirmation: After confirming that parking is complete and the distance is within the operable range, the charging control system notifies the electric vehicle to open the charging cover via Bluetooth communication. The visual monitoring unit of the robotic arm control system detects the opening status of the charging cover and whether there are foreign objects in the charging port.

[0012] Preferably, step S1 specifically includes:

[0013] S11. In standby mode, the charging robot periodically searches for directional broadcast signals of the bound electric vehicles via Bluetooth module;

[0014] S12. Once the electric vehicle enters the Bluetooth communication range and establishes a connection, both parties exchange encrypted information to complete identity authentication.

[0015] S13. The charging control system confirms the charging demand of the electric vehicle and analyzes the received Bluetooth signal strength value to roughly determine the approximate distance range of the electric vehicle relative to the charging robot.

[0016] S14. After confirming that there is a charging requirement, the charging control system notifies the robotic arm control system to start the self-test program.

[0017] Preferably, in step S2, the visual monitoring unit is a monocular or multi-view camera, and the deep learning model is used to identify the charging port from the image and output its position and orientation information in the camera coordinate system.

[0018] Preferably, step S4 specifically includes:

[0019] S41. After visual positioning confirms that the electric vehicle has been parked in a valid parking space, the charging control system activates its star flash module.

[0020] S42. The starlight module communicates with one or more starlight beacons on the electric vehicle to complete secondary authentication through information exchange.

[0021] S43, the Star Beacon module calculates the relative distance and orientation data between the charging robot and the electric vehicle based on the Star Beacon.

[0022] Preferably, in step S5, if the visual monitoring unit detects that the charging cover has not been successfully opened or there is a foreign object in the charging port, the charging control system will pause the automatic charging gun insertion process and send a prompt message to the user.

[0023] Preferably, the method constitutes a redundant system throughout the process: when Bluetooth communication fails, the charging process is manually triggered through the vehicle application or the back-end server; when visual positioning fails or is inaccurate due to poor ambient lighting conditions, positioning guidance is mainly provided by the high-precision distance and orientation data provided by the star-flash positioning module.

[0024] The present invention also discloses a computer-readable storage medium and a computer system, wherein a computer program is stored on the medium, and the computer program, when executed, performs the method described in any of the preceding claims. A computer system includes a processor and a storage medium, wherein a computer program is stored on the storage medium, and the processor reads from the storage medium and runs the computer program to perform the method described in any of the preceding claims.

[0025] The beneficial effects of this invention are as follows:

[0026] (1) Seamless process integration: The process of identity recognition, security authentication, charging demand confirmation and multi-level positioning guidance is organically integrated. Users only need to complete parking to trigger the subsequent fully automatic charging process, truly realizing the automated experience of "one-click parking and charging immediately".

[0027] (2) A redundant and reliable system was constructed: Bluetooth, vision, and star-flash technologies constitute a redundant positioning and identification system. Bluetooth is responsible for the initial handshake and request confirmation, and its failure can be compensated by other methods; vision provides intuitive spatial pose perception; star-flash provides absolutely accurate ranging and anti-interference positioning. The three complement each other, ensuring that the system can still degrade or maintain high-precision operation when some sensors are affected by the environment (such as Bluetooth interference or poor visual lighting), which greatly enhances the robustness and applicability of the system.

[0028] (3) Significantly improved positioning accuracy and insertion success rate: Combining the visual perception of object features and spatial relationships with the sub-meter level precise absolute ranging capability of Star Flash technology, it provides composite positioning information for the motion control of the robotic arm that far exceeds that of a single technology, greatly reducing the risk of insertion failure or mechanical damage caused by positioning errors.

[0029] (4) Enhanced security and environmental adaptability: Through dual authentication via Bluetooth and StarScan, illegal occupation and theft are effectively prevented. StarScan technology performs well in charging station environments with high electromagnetic interference, overcoming the problem of traditional wireless technology being susceptible to co-frequency interference, and ensuring communication and positioning reliability in complex scenarios. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0033] The control system of the charging robot is mainly divided into two parts: the charging control system and the robotic arm control system. The charging control system, as the main control unit, is mainly responsible for the scheduling of the automatic charging system, information confirmation, and charging control guidance, and simultaneously collects information from the vehicle and robotic arm control systems; the robotic arm control system, as the motion and vision control unit, is mainly responsible for environmental recognition and automatic charging gun insertion control.

[0034] like Figure 1 This invention discloses a method for electric vehicle identification and multi-location for charging robots, comprising the following steps:

[0035] S1: Identity Recognition and Bluetooth Positioning Stage

[0036] The charging robot's control system is equipped with a Bluetooth module. In standby mode, the robot periodically searches for the Bluetooth broadcasts of paired vehicles. If a vehicle enters the robot's Bluetooth search range, it automatically connects via Bluetooth. After connection, both parties exchange private information to complete identity verification and security authentication. Once authentication is successful, the system first uses Bluetooth wireless communication to confirm whether the vehicle owner or the vehicle itself has a charging need. Based on the Bluetooth signal strength, it roughly determines the vehicle's approximate location (e.g., the vehicle is within 10m-50m of the charging robot and is entering). This information is then fed back to the robotic arm control system. If a charging need is detected, the system will notify the robotic arm control system in advance to perform a self-check and prepare for charging.

[0037] S2, Visual Identity Verification:

[0038] After receiving the self-check notification, the robotic arm control system completes self-checks of its motion control, vision detection, and other equipment units in advance. When a bound vehicle arrives at the designated parking space and begins parking, it sends a parking notification to the charging control system. Simultaneously, the robotic arm control system uses a vision monitoring unit (monocular or multi-view camera) to confirm whether a vehicle has entered the parking space.

[0039] The robotic arm control system captures images of the electric vehicle's license plate through a visual monitoring unit, and further confirms the electric vehicle's identity using the color and number of the license plate.

[0040] S3: Visual Positioning Stage

[0041] The robotic arm's vision monitoring unit uses a pre-trained deep learning model to quickly locate the charging port in the image and pinpoint the precise pose (position and orientation) of the charging cover. If the parking direction is incorrect, it will send feedback to the charging control system, reminding the vehicle or user to re-park.

[0042] S4: Starlight Positioning Phase

[0043] Starlight technology boasts ultra-high frequency, high precision, and strong anti-interference capabilities, achieving sub-meter positioning accuracy. A starlight module is installed in the charging control system of the charging robot. Upon receiving a valid parking confirmation from the visual detection system, the starlight module activates, interacting with one or more pre-installed starlight beacons within the electric vehicle to further verify its identity. Simultaneously, it calculates the precise distance between the vehicle and the charging robot using signal phase difference and time-of-flight ranging to determine if the vehicle is within the robot's operational range. If the vehicle is outside the robot's operational range, the user or the vehicle will be alerted to re-park.

[0044] S5: Lid Opening and Foreign Object Detection Stage

[0045] This is the final stage before the charging gun is ready. After receiving parking completion notifications from both the electric vehicle and the robotic arm control system, the charging control system sends an opening notification to the electric vehicle via Bluetooth. The electric vehicle opens the hood, and the vision detection unit within the robotic arm control system confirms whether the hood is open and detects whether there are any blockages or other obstacles inside the charging port. Finally, the detection results are fed back to the charging control system to decide on the next action. If there are any obstacles, the charging control system will alert the user.

[0046] Once all the above actions are completed, the motion control unit of the robotic arm control system will intervene and start the insertion gun.

[0047] This invention seamlessly integrates identity recognition, authentication, positioning, and guided charging processes, truly achieving a fully automated experience of one-click parking and instant charging. Furthermore, the invention's triple positioning technology constitutes a redundant system. Bluetooth communication can complete identity recognition and authentication and collect charging requests in advance during parking; Bluetooth failure can be manually triggered by the vehicle's app or backend. When visual positioning is ineffective in poor lighting conditions, it can be supplemented and dominated by the highly interference-resistant StarFlash positioning, ensuring the system can still operate or safely degrade when some sensors are limited. Moreover, this invention combines the spatial perception capabilities of vision with the absolute precision ranging capabilities of StarFlash, greatly improving the success rate of final connection and avoiding mechanical damage or charging failure caused by positioning errors. Finally, the StarFlash technology used in this invention has superior anti-interference characteristics in complex electromagnetic environments, effectively overcoming the co-frequency interference problem of traditional wireless technologies in dense charging station scenarios.

[0048] The present invention also discloses a computer-readable storage medium and a computer system, wherein a computer program is stored on the medium, and the computer program, when executed, performs the method described in any of the preceding claims. A computer system includes a processor and a storage medium, wherein a computer program is stored on the storage medium, and the processor reads from the storage medium and runs the computer program to perform the method described in any of the preceding claims.

[0049] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in a generalized manner in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in different ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the invention.

[0050] The prior description of this disclosure is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not intended to be limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0051] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for electric vehicle identification and multi-location for a charging robot, characterized in that, Includes the following steps: S1. Identity Recognition and Preliminary Bluetooth Positioning: The charging control system of the charging robot establishes a Bluetooth connection with the electric vehicle that enters the communication range through its Bluetooth module to perform identity authentication; after successful authentication, it obtains the charging demand and performs preliminary area positioning of the electric vehicle based on the Bluetooth signal strength, and then activates the robotic arm control system to perform self-check. S2. Visual Identity Verification: The robotic arm control system captures the license plate image of the electric vehicle through the visual monitoring unit, and further confirms the identity of the electric vehicle using the color and number of the license plate; S3. Visual Precision Positioning: The robotic arm control system captures images of the electric vehicle through a visual monitoring unit and uses a pre-trained deep learning model to identify and position the electric vehicle's charging port. S4. Star Flash Positioning and Identity Verification: After receiving a valid parking signal, the charging control system communicates with one or more pre-installed star flash beacons on the electric vehicle through its star flash module to reconfirm the electric vehicle's identity and calculate the relative distance and orientation data between the charging robot and the electric vehicle based on the star flash beacons. S5. Charging Port Status Confirmation: After confirming that parking is complete and the distance is within the operable range, the charging control system notifies the electric vehicle to open the charging cover via Bluetooth communication. The visual monitoring unit of the robotic arm control system detects the opening status of the charging cover and whether there are foreign objects in the charging port.

2. The method according to claim 1, characterized in that, Step S1 specifically includes: S11. In standby mode, the charging robot periodically searches for directional broadcast signals of the bound electric vehicles via Bluetooth module; S12. Once the electric vehicle enters the Bluetooth communication range and establishes a connection, both parties exchange encrypted information to complete identity authentication. S13. The charging control system confirms the charging demand of the electric vehicle and analyzes the received Bluetooth signal strength value to roughly determine the approximate distance range of the electric vehicle relative to the charging robot. S14. After confirming that there is a charging requirement, the charging control system notifies the robotic arm control system to start the self-test program.

3. The method according to claim 1 or 2, characterized in that: In step S2, the visual monitoring unit is a monocular or multi-view camera, and the deep learning model is used to identify the charging port from the image and output its position and orientation information in the camera coordinate system.

4. The method according to claim 1, characterized in that, Step S4 specifically includes: S41. After visual positioning confirms that the electric vehicle has been parked in a valid parking space, the charging control system activates its star flash module. S42. The starlight module communicates with one or more starlight beacons on the electric vehicle to complete secondary authentication through information exchange. S43, the Star Beacon module calculates the relative distance and orientation data between the charging robot and the electric vehicle based on the Star Beacon.

5. The method according to claim 1, characterized in that: In step S5, if the visual monitoring unit detects that the charging cover has not been opened successfully or that there is a foreign object in the charging port, the charging control system will pause the automatic charging gun insertion process and send a prompt message to the user.

6. The method according to claim 1, characterized in that, The method constitutes a redundant system throughout the process: when Bluetooth communication fails, the charging process is manually triggered through the vehicle application or the back-end server; when visual positioning fails or is inaccurate due to poor ambient lighting conditions, positioning guidance is provided by the high-precision distance and orientation data provided by the star-flash positioning module.

7. A computer-readable storage medium, characterized in that: The medium contains a computer program, which, when run, performs the method as described in any one of claims 1 to 6.

8. A computer system, characterized in that: It includes a processor and a storage medium, on which a computer program is stored, and the processor reads from the storage medium and runs the computer program to perform the method as described in any one of claims 1 to 6.

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