A control method for intelligent traffic cones

Abstract

This invention discloses a control method for intelligent traffic cones, relating to the field of intelligent traffic cones. It establishes a communication connection between the intelligent traffic cones and a central control system based on a fixed base. Simultaneously, the algorithm module analyzes the current position of the moving cone group in the inertial coordinate system based on image data collected by a camera and feeds this position information back to the central control system. When deployment is required, the central control system generates corresponding deployment path information based on the current position and pre-arranged formation of each moving cone group and issues a deployment command and corresponding path information to the control module. After receiving the deployment command, the control module, combining attitude calculation from the inertial navigation module, angular velocity measurement from the wheel speed sensor, calculation from the algorithm module, and the directional error adjustment mechanism of the PID controller, accurately executes the path movement task, effectively solving the path conflict or overlapping coverage problems that may occur during the collaborative deployment of multiple intelligent traffic cones.

Description

Technical Field

[0001] This invention relates to the field of intelligent traffic cones, and more particularly to a control method for intelligent traffic cones. Background Technology

[0002] With the development of intelligent transportation systems, traditional traffic cones, due to their limited functionality and lack of intelligent management capabilities, are unable to meet the demands of modern complex traffic environments. While existing intelligent traffic cones have addressed these issues to some extent by integrating mobile components, sensors, and communication modules to achieve autonomous movement and dynamic adjustment, they still suffer from limited positioning accuracy, low efficiency in group collaboration, and inconvenient energy management. Particularly in environments with variable lighting conditions or complex terrain, existing intelligent traffic cones are prone to inaccurate positioning; path conflicts or overlapping coverage occur frequently when multiple devices work together, impacting overall efficiency; and the demands of frequent movement and long-term operation pose challenges to battery life, as existing charging methods are neither convenient nor efficient. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes a control method for intelligent traffic cones, wherein the intelligent traffic cone comprises:

[0004] A mobile cone group and a fixed base; the mobile cone group includes a control module, a camera, an algorithm module communicatively connected to the control module, and an inertial navigation module and a wheel speed sensor communicatively connected to the algorithm module;

[0005] The control method includes:

[0006] Establish a communication connection between the intelligent traffic cone and the central control system based on a fixed base;

[0007] The algorithm module uses a convolutional neural network to process the image data collected in real time by the camera, analyzes the current position of the moving traffic cone group relative to the positioning reference point in the inertial coordinate system, and sends the position information to the central control system through the control module. When deployment is required, the central control system generates the corresponding deployment path information based on the current position of each moving traffic cone group and the pre-arranged formation, and issues the deployment command and the corresponding deployment path information including the destination position to the control module of the intelligent traffic cone.

[0008] When the control module receives a deployment command and the corresponding deployment path information including the destination location:

[0009] The inertial navigation module uses a quaternion algorithm to calculate the current attitude information of the moving cone group; the wheel speed sensor obtains the angular velocity of the driving wheel of the moving cone group and transmits it to the algorithm module;

[0010] The algorithm module fuses the current attitude information with the angular velocity of the drive wheel to obtain the current actual direction angle. Based on the current position of the moving cone group in the inertial coordinate system and the deployment path information received by the control module, the target direction angle of the moving cone group in the inertial coordinate system is calculated in real time.

[0011] The control module uses the current actual direction angle and the real-time calculated target direction angle to calculate the direction error in the cone coordinate system. Based on this error, the PID controller adjusts the output of the drive element in real time, so that the moving cone group moves to the corresponding endpoint position according to the received deployment path information.

[0012] Furthermore, the movable cone assembly further includes: a movable component and a cone; wherein: the movable component includes a movable base, a drive wheel, and a drive element; the camera is connected to the movable base; the movable base is provided with a receiving cavity; the drive element and the drive wheel are both connected to the bottom of the movable base; the output shaft of the drive element is connected to the drive wheel; the drive element can drive the drive wheel to rotate; a control module is disposed in the receiving cavity and connected to the drive element; the cone is disposed above the movable base, covering the opening of the receiving cavity.

[0013] Furthermore, the fixed base is equipped with an RFID tag, the mobile base is also equipped with an RFID reader, the fixed base is provided with a docking space, and the mobile base can be accommodated in the docking space, at which time the RFID reader can be close to the RFID tag.

[0014] Furthermore, the establishment of a communication connection between the intelligent traffic cone and the central control system based on the fixed base specifically includes:

[0015] By reading the RFID tag information of the fixed base with an RFID card reader, the intelligent traffic cone can be automatically numbered and identified. Based on the numbering information, the group division and communication frequency band configuration are completed, and the communication connection between the intelligent traffic cone and the central control system is established.

[0016] The inertial navigation module includes a gyroscope, an accelerometer, and a magnetic field sensor; wherein: the gyroscope is used to measure the angular velocities of the moving cone group around the X, Y, and Z axes of its cone coordinate system in real time; the accelerometer is used to detect the linear acceleration of the moving cone group in the cone coordinate system in real time; and the magnetic field sensor is used to measure the geomagnetic field strength of the moving cone group in the cone coordinate system in real time.

[0017] The attitude information includes the current orientation angle of the moving cone group in the inertial coordinate system.

[0018] Furthermore, the step of calculating the current attitude information of the moving cone group using a quaternion algorithm via the inertial navigation module specifically involves:

[0019] Quaternion state variables are defined based on the measurement data from the gyroscope;

[0020] Define three-axis angular velocities; the three-axis angular velocities are the angular velocity components measured by the gyroscope in the cone coordinate system, which correspond to the rotational rates around the X-axis, Y-axis and Z-axis respectively; wherein, the cone coordinate system is a local coordinate system based on the moving cone group body, and its origin is located at the geometric center of the moving cone group, used to describe the attitude and orientation of the moving cone group in space;

[0021] Predicting the rate of change of quaternion state variables based on triaxial angular velocity;

[0022] Estimate quaternion state variables based on the rate of change of quaternion state variables;

[0023] The component of gravity direction in the cone coordinate system in the accelerometer measurement data is obtained by estimating the quaternion state variables; the component of geomagnetic field direction in the cone coordinate system in the magnetic field sensor measurement data is obtained by estimating the quaternion; the two obtained components are combined into the observation vector Z;

[0024] Calculate the Kalman gain and use the Kalman gain and the observation vector Z to update the quaternion state variable estimates;

[0025] The normalized updated quaternion state variable estimate is obtained as the normalized quaternion state variable;

[0026] The current orientation angle of the moving cone group in the inertial coordinate system is extracted from the normalized quaternion state variables.

[0027] Furthermore, the calculation of the Kalman gain specifically involves:

[0028] The prediction error covariance matrix P is initialized based on the measurement noise characteristics of the gyroscope and the uncertainty of the quaternion state variable estimation; the prediction error covariance matrix P is dynamically updated based on the uncertainty of the quaternion state variable estimation during the Kalman filter iteration process;

[0029] Construct an observation matrix H, which represents the linearized mapping relationship between the measurement data of the accelerometer and the magnetic field sensor and the quaternion state variables, wherein the quaternion state variables are used to characterize the attitude of the moving cone group in three-dimensional space.

[0030] The observation noise covariance matrix R is set according to the sensor noise characteristics of the accelerometer and the magnetic field sensor; the Kalman gain is calculated by the prediction error covariance matrix P, the observation matrix H and the observation noise covariance matrix R.

[0031] Furthermore, the step of fusing the current attitude information with the drive wheel angular velocity through the algorithm module to obtain the current actual direction angle is as follows:

[0032] The heading angle of the driving wheel relative to the initial direction in the inertial coordinate system is obtained by integrating the angular velocity of the driving wheel.

[0033] The current orientation angle of the extracted moving cone group in the inertial coordinate system is weighted and fused with the heading angle of the drive wheel relative to the initial direction in the inertial coordinate system to obtain the fused orientation angle, which is the current actual orientation angle.

[0034] Furthermore, the deployment path information received by the control module includes: the target position and desired direction of the moving cone group in the inertial coordinate system at the current moment.

[0035] Furthermore, a wireless charging receiver is provided at the bottom of the mobile base, and a wireless charging transmitter is provided in the docking space of the fixed base. When the mobile base is accommodated in the docking space, the wireless charging receiver is close to the wireless charging transmitter.

[0036] Furthermore, when disarming is required, the central control system assigns corresponding disarming path information and fixed bases to each mobile cone group based on the current position of all mobile cone groups and the availability of each fixed base, and issues disarming commands, along with their corresponding disarming path information and fixed base positions, to the control module of the intelligent traffic cone.

[0037] The control method further includes: when the control module receives a disarming command and its corresponding disarming path information and fixed base position:

[0038] The inertial navigation module calculates the current attitude information of the moving cone group, and the wheel speed sensor obtains the angular velocity of the drive wheel and transmits it to the algorithm module.

[0039] The algorithm module fuses the current attitude information with the angular velocity of the drive wheels to obtain the current actual orientation angle; the target orientation angle of the moving cone group in the inertial coordinate system is calculated in real time based on the current position of the moving cone group in the inertial coordinate system and the return path received by the control module.

[0040] The control module uses the current actual direction angle and the real-time calculated target direction angle to calculate the direction error in the cone coordinate system. Based on this error, the PID controller adjusts the output of the drive element in real time, so that the moving cone group moves to the corresponding fixed base according to the received disarmament path information.

[0041] When the moving cone group reaches the corresponding fixed base, the corresponding control module detects the wireless charging transmitter signal and connects with it to establish a stable wireless charging connection.

[0042] Compared with the prior art, the present invention has at least the following beneficial effects:

[0043] (1) This invention establishes a communication connection between the intelligent traffic cone and the central control system based on a fixed base; at the same time, the algorithm module uses a convolutional neural network to process the image data collected by the camera, analyzes the current position of the moving cone group in the inertial coordinate system, and feeds back the position information to the central control system; when deployment is required, the central control system generates the corresponding deployment path information according to the current position and pre-arrangement of each moving cone group, and issues the deployment command and the corresponding path information to the control module; after receiving the deployment command, the control module combines the attitude calculation of the inertial navigation module, the angular velocity measurement of the wheel speed sensor, the calculation of the algorithm module, and the direction error adjustment mechanism of the PID controller to accurately execute the path movement task; this scheme effectively solves the path conflict or repeated coverage problem that may occur in the collaborative deployment of multiple intelligent traffic cones by automatically numbering and generating corresponding deployment path information for each moving cone group, while improving the overall positioning and motion control accuracy.

[0044] (2) This invention employs a quaternion algorithm combined with data from gyroscopes, accelerometers, and magnetic field sensors to achieve high-precision attitude estimation. Specifically, the inertial navigation module predicts the rate of change of the quaternion state variables based on the three-axis angular velocity and fuses the data from the accelerometer and magnetic field sensor using Kalman filtering to obtain accurate attitude information. This not only improves the navigation accuracy of the intelligent traffic cone in complex environments but also effectively reduces attitude drift caused by sensor errors. Through this method, the intelligent traffic cone can more accurately calculate its orientation angle in the inertial coordinate system, improving the control accuracy of the control method of this invention.

[0045] (3) This invention achieves a more accurate calculation of the actual heading angle by fusing the current attitude information with the angular velocity of the drive wheels. First, the heading angle is obtained by integrating the angular velocity of the drive wheels; then, this heading angle is compared with the current heading angle of the moving cone group in the inertial coordinate system. Weighted fusion is performed to obtain the current actual direction angle. This multi-sensor data fusion method significantly improves the accuracy of direction angle calculation, enabling intelligent traffic cones to perform deployment tasks more precisely. Furthermore, based on the real-time calculated target direction angle and the current actual direction angle, the control module uses a PID controller to adjust the output of the drive components in real time, further enhancing the accuracy and stability of path following.

[0046] (4) This invention integrates wireless charging technology. When the mobile seat of the intelligent traffic cone reaches the designated fixed base, it can connect with the wireless charging transmitter on the fixed base through the wireless charging receiver to establish a stable wireless charging connection. This design not only simplifies the charging process and avoids the hassle of frequently replacing batteries or manually plugging and unplugging charging cables, but also improves the availability and maintenance efficiency of the device. Especially in scenarios of long-term continuous operation, wireless charging technology significantly extends the working time of the device, reduces the risk of task interruption due to insufficient power, and further improves the overall performance and user experience of this invention. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the structure of the intelligent traffic cone according to Embodiment 1 of the present invention;

[0048] Figure 2 This is a schematic diagram of the interior of the moving component in Embodiment 1 of the present invention;

[0049] Figure 3 This is a front view of the intelligent traffic cone according to Embodiment 1 of the present invention;

[0050] Figure 4 for Figure 3 Enlarged view of detail A in the middle;

[0051] Figure 5 This is a schematic diagram of the fixed base in Embodiment 1 of the present invention;

[0052] Figure 6 for Figure 5 A magnified view of detail B in the middle;

[0053] Figure 7 This is a flowchart of a control method for intelligent traffic cones according to Embodiment 2 of the present invention.

[0054] In the diagram: 1. Moving component; 11. Moving base; 111. Receiving cavity; 112. Wireless charging receiver; 12. Drive wheel; 13. Drive element; 2. Control module; 3. Cone; 31. Flashing light; 32. First assembly; 33. Second assembly; 34. Third assembly; 4. Support wheel; 5. Fixed base; 51. Parking space; 52. Wireless charging transmitter; 521. Second adjustment hole; 53. Connection hole; 6. RFID reader; 7. Connector; 71. First adjustment hole; 8. Position sensor. Detailed Implementation

[0055] The following are specific embodiments of the present invention, which are described in conjunction with the accompanying drawings. However, the present invention is not limited to these embodiments.

[0056] Example 1

[0057] In modern urban traffic management, traffic cones serve as crucial temporary traffic guidance and road construction isolation facilities, widely used in road construction sites, accident scenes, and temporary traffic control areas. Traditional traffic cones are typically fixed structures, consisting of a cone-shaped body that relies on its own weight or a base counterweight for stable placement. However, this static placement method has many limitations, such as the inability to automatically and quickly adjust its position according to traffic conditions and its difficulty in adapting to complex and changing road environments. To address this issue, such as... Figures 1-6 As shown, this embodiment proposes an intelligent traffic cone, including: a mobile cone group (not shown in the figure), which includes a mobile component 1, a control module 2, a cone 3, an algorithm module (not shown in the figure) that is communicatively connected to the control module, and an inertial navigation module (not shown in the figure) and a wheel speed sensor (not shown in the figure) that are communicatively connected to the algorithm module.

[0058] The movable component 1 includes a movable base 11, a drive wheel 12, and a drive element 13. The movable base 11 is provided with a receiving cavity 111. The drive element 13 and the drive wheel 12 are both connected to the bottom of the movable base 11. The output shaft of the drive element 13 is connected to the drive wheel 12, and the drive element 13 can drive the drive wheel 12 to rotate.

[0059] The control module 2 is disposed in the receiving cavity 111 and is connected to the driving element 13.

[0060] The cone 3 is positioned above the movable seat 11 and covers the opening of the receiving cavity 111. A flashing light 31 is also provided on the top of the cone 3.

[0061] Specifically, the control module 2 can be connected to the drive element 13 to drive the mobile cone group to move and position automatically according to the background instructions, so as to realize the collaborative operation and dynamic arrangement of multiple mobile cone groups. In scenarios such as road construction, traffic accidents or temporary traffic control, staff can remotely complete the rapid layout and adjustment of traffic guidance lines without manually carrying heavy traffic cones.

[0062] In this embodiment, the intelligent traffic cone greatly improves operational efficiency, reduces labor costs, and effectively reduces the safety risks associated with manual on-site operation. It avoids accidental injuries that may be caused by personnel working in areas with heavy traffic. In addition, the flashing light 31 on the top of the cone 3 is clearly visible during the day and night, promptly reminding passing vehicles to slow down and give way, further enhancing the safety of road traffic.

[0063] like Figures 1-6As shown, based on the above embodiment, the moving component 1 further includes a support wheel 4, which is rotatably connected to the bottom of the moving base 11.

[0064] Specifically, the support wheel 4 is located at the bottom of the movable seat 11 and together with the drive wheel 12 forms a stable support plane, thereby providing a smoother and more stable operation during the overall movement of the movable cone group.

[0065] In this embodiment, during the overall movement of the moving cone assembly, the support wheel 4 not only plays an auxiliary role in bearing the weight, but also works in coordination with the drive wheel 12 to ensure that the equipment maintains a low center of gravity and good balance during movement, thereby effectively reducing the occurrence of bumps, vibrations and deviations.

[0066] like Figures 1-6 As shown, based on the above embodiment, there are two drive wheels 12 and two drive elements 13, and the control module 2 is connected to the two drive elements 13 respectively.

[0067] Specifically, there are two drive wheels 12 and two drive elements 13, forming a symmetrical drive structure. The control module 2 is connected to the two drive elements 13 respectively, and can independently control the speed and direction of rotation of each drive wheel 12. Thus, the moving cone group can move forward, backward, turn and turn in place through the speed difference between the two drive wheels 12.

[0068] In this embodiment, the moving cone group can turn, travel in arcs, or even rotate in place by rotating two drive wheels 12 (left drive wheel and right drive wheel) at different speeds or directions. It can move flexibly in narrow spaces or complex environments, and the differential control can reasonably allocate power output according to actual conditions to avoid unnecessary energy consumption and help improve the range.

[0069] like Figures 1-6 As shown, based on the above embodiment, it also includes a fixed base 5, which is provided with an RFID tag (not shown in the figure), and the movable base 11 is also provided with an RFID reader 6. The fixed base 5 is provided with a docking space 51, and the movable base 11 can be accommodated in the docking space 51. At this time, the RFID reader 6 can be close to the RFID tag.

[0070] Specifically, when the mobile cone group moves and accurately stops at the designated fixed space, the RFID reader 6 integrated on its bottom mobile base 11 can automatically identify and read the information stored in the RFID tag installed on the fixed base 5. Through this identification process, the mobile cone group can quickly establish a data connection with the background management system (i.e., the central control system).

[0071] In this embodiment, if a mobile cone group needs to be replaced due to damage or other reasons, the maintenance personnel only need to place the new mobile cone group on the same fixed base 5. The RFID reader 6 on the new equipment can automatically read the relevant information in the RFID tag on the base. There is no need to manually input configuration information, which not only greatly improves the replacement efficiency, but also effectively reduces the risk of human error and improves the overall system's intelligence level and ease of operation and maintenance. This function is particularly suitable for traffic management scenarios with large-scale deployment, frequent changes in location, or the need for rapid response.

[0072] like Figures 1-6 As shown, based on the above embodiment, the bottom of the mobile base 11 is also provided with a wireless charging receiver 112, and the docking space 51 of the fixed base 5 is provided with a wireless charging transmitter 52. When the mobile base 11 is accommodated in the docking space 51, the wireless charging receiver 112 is close to the wireless charging transmitter 52.

[0073] Specifically, after completing its warning mission, the mobile cone group returns to the parking space 51 of the fixed base 5, and the wireless charging receiver 112 at its bottom automatically aligns with and approaches the wireless charging transmitter 52 in the fixed base 5, thereby establishing an efficient wireless charging connection.

[0074] In this embodiment, the design of the wireless charging transmitter 52 and the wireless charging receiver 112 not only improves the convenience and automation of the device, but also effectively avoids the problems of wear, corrosion and leakage that may be caused by traditional plug-in charging interfaces.

[0075] like Figures 1-6 As shown, based on the above embodiment, it also includes a connector 7, which is connected to the fixed base 5. The connector 7 is provided with a first adjustment hole 71, and the wireless charging transmitter 52 is provided with a second adjustment hole 521. It also includes an adjustment member (not shown in the figure), which is connected to the first adjustment hole 71 and the second adjustment hole 521, thereby realizing that the wireless charging transmitter 52 and the connector 7 can be connected or disconnected in a height-adjustable manner.

[0076] Specifically, the connector 7 is connected to the fixed base 5, the adjusting member is rotatably connected to the first adjusting hole 71, and the adjusting member is threadedly connected to the second adjusting hole 521. Rotating the adjusting hole can realize the lifting and lowering of the wireless charging transmitter 52 and the connector 7, as well as their detachable connection.

[0077] In this embodiment, when the operator rotates the adjusting component, the adjusting component will be displaced along its axial direction due to the action of the thread, thereby driving the wireless charging transmitter 52 connected to it to achieve vertical movement. At the same time, this adjustment structure also allows for quick and detachable connection between the wireless charging transmitter 52 and the connector 7, making it easy to replace the wireless charging transmitter module with different power or model according to actual usage needs to adapt to various application scenarios. The design of this adjustment mechanism also allows the height of the wireless charging transmitter 52 to be flexibly adjusted according to the actual position of the wireless charging receiver 112 on the moving base 11, ensuring that the two maintain the best alignment in the vertical direction.

[0078] like Figures 1-6 As shown, based on the above embodiment, the moving component 1 further includes a positioning sensor 8, which is connected to the moving base 11. When the moving base 11 is accommodated in the docking space 51, the positioning sensor 8 is located on the side close to the fixed base 5.

[0079] Specifically, the positioning sensor 8 is installed on the movable seat 11 to monitor the relative distance and positional relationship between the movable seat 11 and the fixed base 5 in real time. When the movable cone group is about to enter the parking space 51, the positioning sensor 8 starts to work and continuously detects the change in distance between it and the fixed base 5. The control system dynamically adjusts the traveling state of the movable seat 11 according to the signal of the positioning sensor 8 to ensure that the movable cone group can accurately and smoothly stop at the preset designated position.

[0080] In this embodiment, the precise positioning function of the positioning sensor 8 can effectively ensure that the wireless charging receiver 112 on the mobile base 11 and the wireless charging transmitter 52 on the fixed base 5 are precisely aligned in the vertical and horizontal directions, thereby improving the wireless charging efficiency and avoiding energy transmission interruption. At the same time, it also ensures that the RFID reader 6 and the RFID tag on the fixed base 5 maintain the best reading distance and angle, ensuring the stability and accuracy of data communication.

[0081] like Figures 1-6 As shown, based on the above embodiment, the fixed base 5 is also provided with a connection hole 53 and a fastener (not shown in the figure). The fastener can pass through the connection hole 53 to connect with the ground or other placement plane.

[0082] Specifically, the fasteners pass through the connecting holes 53 located at the bottom of the fixed base 5 and are securely connected to the ground or other placement surfaces, thereby ensuring that the entire mobile cone assembly has good stability and anti-overturning ability during use.

[0083] In this embodiment, the fastener can be flexibly replaced and adapted according to the actual installation environment and the material of the placement surface to meet the fixing requirements in different scenarios. Through this modular and replaceable fastener design, the adaptability of the fixing base 5 to various installation environments is improved.

[0084] like Figures 1-6 As shown, based on the above-described embodiment, a camera (not shown in the figure) is also included, which is connected to the mobile base 11.

[0085] In this embodiment, the mobile base 11 also integrates a camera, which has real-time shooting and recording functions. It can dynamically monitor the surrounding environment during the operation of the mobile cone group. The camera can also serve as an important auxiliary sensor for the mobile cone group to achieve autonomous navigation and path planning. The camera can collect and analyze surrounding road information in real time. At complex intersections or temporary construction sections, the camera can identify changes in ground markings or the location of obstacles, assisting the control system in avoiding dangerous areas and ensuring that the equipment reaches the target location safely and accurately.

[0086] like Figures 1-6 As shown, based on the above embodiment, the cone barrel 3 includes a first assembly 32, a second assembly 33 and a third assembly 34, and the two ends of the second assembly 33 are detachably connected to the first assembly 32 and the third assembly 34 respectively.

[0087] In this embodiment, the cone 3 is composed of a first assembly part 32, a second assembly part 33 and a third assembly part 34, which are interlocked or spliced ​​together. This design not only allows the cone 3 to maintain a stable cone shape when in use, but also enables convenient storage and transportation when not in use by compressing its volume.

[0088] Example 2

[0089] To effectively address potential path conflicts or overlapping coverage issues that may arise during the collaborative deployment of multiple intelligent traffic cones, and to improve the overall accuracy of positioning and motion control, such as... Figure 7 As shown, this embodiment proposes a control method for the intelligent traffic cone in Embodiment 1, including:

[0090] By reading the RFID tag information of the fixed base using an RFID reader, the intelligent traffic cones are automatically numbered and identified. Based on the numbering information, grouping and communication frequency band configuration are completed, establishing a communication connection between the intelligent traffic cones and the central control system; specifically:

[0091] The RFID reader reads the RFID tag information of the fixed base, and the control module automatically numbers the intelligent traffic cones based on the tag information and sends the numbering information to the central control system. The central control system divides the intelligent traffic cones into groups according to the received numbers and pre-arranged formations, determines the communication frequency band corresponding to each group, and feeds back the group information and communication frequency band to each intelligent traffic cone. The intelligent traffic cones can identify their group and communication frequency band based on their numbers, thereby establishing a communication connection with the central control system.

[0092] The algorithm module uses a convolutional neural network to process the image data collected in real time by the camera, analyzes the current position of the moving traffic cone group relative to the positioning reference point in the inertial coordinate system, and sends the position information to the central control system through the control module. When deployment is required, the central control system generates the corresponding deployment path information based on the current position of each moving traffic cone group and the pre-arranged formation, and issues the deployment command and the corresponding deployment path information including the destination position to the control module of the intelligent traffic cone.

[0093] When the control module receives a deployment command and the corresponding deployment path information including the destination location:

[0094] The current attitude information of the moving cone group is calculated by the inertial navigation module using a quaternion algorithm;

[0095] The inertial navigation module includes a gyroscope, an accelerometer, and a magnetic field sensor; wherein: the gyroscope is used to measure the angular velocities of the moving cone group around the X, Y, and Z axes of its cone coordinate system in real time; the accelerometer is used to detect the linear acceleration of the moving cone group in the cone coordinate system in real time; and the magnetic field sensor is used to measure the geomagnetic field strength of the moving cone group in the cone coordinate system in real time.

[0096] The attitude information includes the current orientation angle of the moving cone group in the inertial coordinate system;

[0097] The current attitude information of the moving cone group is calculated using a quaternion algorithm via the inertial navigation module, specifically as follows:

[0098] Define quaternion state variables: ;in: , , , In the formula, This represents the total rotation angle of the moving cone group relative to the inertial coordinate system, obtained by integrating the three-axis angular velocities measured by the gyroscope. These represent the components of the rotation axis on the X, Y, and Z axes multiplied by , respectively. ; The unit vector representing the axis of rotation;

[0099] Define the three-axis angular velocity The three-axis angular velocities are the angular velocity components measured by the gyroscope in the cone-shaped coordinate system, which correspond to the rotational rates around the X-axis, Y-axis, and Z-axis, respectively. The cone-shaped coordinate system is a local coordinate system based on the moving cone assembly body, with its origin located at the geometric center of the moving cone assembly, and is used to describe the attitude and orientation of the moving cone assembly in space.

[0100] The rate of change of quaternion state variables is predicted based on triaxial angular velocity. The prediction formula is as follows:

[0101] ;in, , representing angular velocity in pure quaternion form; Represents quaternion multiplication; Represents the rate of change of a quaternion state variable;

[0102] Quaternion state variables are estimated based on their rate of change. The estimation formula is as follows:

[0103] ;in, Indicates the integration time interval. This represents the estimated value of the quaternion state variable at the next time point;

[0104] The component of gravity direction in the cone coordinate system in the accelerometer measurement data is obtained by estimating the quaternion state variables; the component of geomagnetic field direction in the cone coordinate system in the magnetic field sensor measurement data is obtained by estimating the quaternion; the two obtained components are combined into the observation vector Z;

[0105] In this embodiment:

[0106] The formula for obtaining the component of gravity in the cone coordinate system from accelerometer measurement data is:

[0107] ;

[0108] in, , is the acceleration due to gravity;

[0109] for . conjugate.

[0110] The formula for obtaining the component of the geomagnetic field direction in the cone coordinate system in the magnetic field sensor measurement data is as follows:

[0111] ;

[0112] in, This represents the unit component of the Earth's magnetic field in the inertial coordinate system.

[0113] Calculate the Kalman gain and use the Kalman gain and the observation vector Z to update the quaternion state variable estimates;

[0114] The calculation of the Kalman gain is specifically as follows:

[0115] The prediction error covariance matrix P is initialized based on the measurement noise characteristics of the gyroscope and the uncertainty of the quaternion state variable estimation; the prediction error covariance matrix P is dynamically updated based on the uncertainty of the quaternion state variable estimation during the Kalman filter iteration process;

[0116] Construct an observation matrix H, which represents the linearized mapping relationship between the measurement data of the accelerometer and the magnetic field sensor and the quaternion state variables, wherein the quaternion state variables are used to characterize the attitude of the moving cone group in three-dimensional space.

[0117] The observation noise covariance matrix R is set according to the sensor noise characteristics of the accelerometer and the magnetic field sensor;

[0118] The Kalman gain is calculated using the prediction error covariance matrix P, the observation matrix H, and the observation noise covariance matrix R. The calculation formula is:

[0119] .

[0120] In this embodiment, the update formula for updating the quaternion state variable estimate using Kalman gain and observation vector Z is as follows:

[0121] ;

[0122] In the formula, This represents the updated quaternion state variable estimate.

[0123] The normalized updated quaternion state variable estimate is obtained as the normalized quaternion state variable;

[0124] In this embodiment, the normalization formula is:

[0125] In the formula, This represents a normalized quaternion state variable.

[0126] Extract the current orientation angle of the moving cone group in the inertial coordinate system from the normalized quaternion state variables. The extraction formula is:

[0127] ;

[0128] In the formula, Represents the normalized quaternion state variables (i.e. Quaternion state variables in (the context of the problem).

[0129] Let this be an arctangent function used to calculate angles, with a range of 0. .

[0130] This invention employs a quaternion algorithm combined with data from gyroscopes, accelerometers, and magnetic field sensors to achieve high-precision attitude estimation. Specifically, the inertial navigation module predicts the rate of change of the quaternion state variables based on the three-axis angular velocities and fuses the data from the accelerometer and magnetic field sensor using Kalman filtering to obtain accurate attitude information. This not only improves the navigation accuracy of the intelligent traffic cone in complex environments but also effectively reduces attitude drift caused by sensor errors. Through this method, the intelligent traffic cone can more accurately calculate its orientation angle in the inertial coordinate system, improving the control accuracy of the control method of this invention.

[0131] The angular velocity of the drive wheels is obtained by the wheel speed sensor and transmitted to the algorithm module;

[0132] The algorithm module fuses the current attitude information with the angular velocity of the drive wheel to obtain the current actual direction angle. Based on the current position of the moving cone group in the inertial coordinate system and the deployment path information received by the control module, the target direction angle of the moving cone group in the inertial coordinate system is calculated in real time.

[0133] The process of fusing the current attitude information with the angular velocity of the drive wheels through the algorithm module to obtain the current actual direction angle is as follows:

[0134] The heading angle of the driving wheel relative to the initial direction in the inertial coordinate system is obtained by integrating the angular velocity of the driving wheel; the integral formula is: ;in, ;

[0135] In the formula, The integration time interval, The angular velocity of the driving wheel is the rotational angular velocity of the driving wheel relative to the inertial coordinate system in the horizontal plane. The initial heading angle of the driving wheel in the inertial coordinate system; This is the heading angle of the driving wheel relative to the initial direction in the inertial coordinate system; These are the angular velocities of the left and right drive wheels, respectively. Indicates the radius of the drive wheel; This indicates the distance between the left and right drive wheels.

[0136] The current orientation angle of the extracted moving cone group in the inertial coordinate system. The heading angle of the drive wheels relative to the initial direction in the inertial coordinate system Perform weighted fusion to obtain the fused direction angle, which is the current actual direction angle. The formula for weighted fusion is:

[0137] ;in: ;

[0138] In the formula, express The corresponding preset weight value, express The corresponding preset weight value; This indicates the current actual direction angle.

[0139] This invention achieves a more accurate calculation of the actual heading angle by fusing current attitude information with the angular velocity of the drive wheels. First, the heading angle is obtained by integrating the angular velocity of the drive wheels; then, this heading angle is compared with the current heading angle of the moving cone group in the inertial coordinate system. Weighted fusion is performed to obtain the current actual direction angle. This multi-sensor data fusion method significantly improves the accuracy of direction angle calculation, enabling intelligent traffic cones to perform deployment tasks more precisely. Furthermore, based on the real-time calculated target direction angle and the current actual direction angle, the control module uses a PID controller to adjust the output of the drive components in real time, further enhancing the accuracy and stability of path following.

[0140] The deployment path information received by the control module includes: the target position and desired direction of the moving cone group in the inertial coordinate system at the current moment;

[0141] The target orientation angle of the moving cone group in the inertial coordinate system is calculated in real time based on the current position of the moving cone group in the inertial coordinate system and the deployment path information received by the control module. The calculation formula is as follows:

[0142] ;

[0143] In the formula, This indicates the target position of the moving cone group in the inertial coordinate system at the current moment. This indicates the current position of the moving cone group in the inertial coordinate system; This indicates the desired direction of the moving cone group in the inertial coordinate system at the current moment; This represents the target orientation angle of the moving cone group in the inertial coordinate system.

[0144] The control module uses the current actual direction angle and the real-time calculated target direction angle to calculate the direction error in the cone coordinate system. Based on this error, the PID controller adjusts the output of the drive element in real time, so that the moving cone group moves to the corresponding endpoint position according to the received deployment path information.

[0145] This invention uses an RFID reader to read RFID tag information on a fixed base, enabling automatic numbering and identification of intelligent traffic cones. Based on the numbering information, it completes group division and communication frequency band configuration, establishing a communication connection with the central control system. Simultaneously, the algorithm module uses a convolutional neural network to process image data collected by cameras, analyzing the current position of the moving cone group in the inertial coordinate system and feeding this position information back to the central control system. When deployment is required, the central control system generates corresponding deployment path information based on the current position and pre-arranged formation of each moving cone group, and issues deployment commands and corresponding path information to the control module. Upon receiving the deployment command, the control module combines attitude calculation from the inertial navigation module, angular velocity measurement from the wheel speed sensor, algorithm module calculation, and PID controller direction error adjustment mechanism to accurately execute the path movement task. This scheme, through automatic numbering—generating corresponding deployment path information for each moving cone group—effectively solves the path conflict or overlapping coverage problems that may occur during the collaborative deployment of multiple intelligent traffic cones, while improving the overall positioning and motion control accuracy.

[0146] The bottom of the mobile base is also provided with a wireless charging receiver, and the docking space of the fixed base is provided with a wireless charging transmitter. When the mobile base is accommodated in the docking space, the wireless charging receiver is close to the wireless charging transmitter.

[0147] When disarming is required, the central control system assigns a corresponding disarming path information and a fixed base to each mobile cone group based on the current position of all mobile cone groups and the availability of each fixed base, and issues a disarming command and its corresponding disarming path information and fixed base position to the control module of the intelligent traffic cone.

[0148] The control method further includes: when the control module receives a disarming command and its corresponding disarming path information and fixed base position:

[0149] The inertial navigation module calculates the current attitude information of the moving cone group, and the wheel speed sensor obtains the angular velocity of the drive wheel and transmits it to the algorithm module.

[0150] The algorithm module fuses the current attitude information with the angular velocity of the drive wheels to obtain the current actual orientation angle; the target orientation angle of the moving cone group in the inertial coordinate system is calculated in real time based on the current position of the moving cone group in the inertial coordinate system and the return path received by the control module.

[0151] The control module uses the current actual direction angle and the real-time calculated target direction angle to calculate the direction error in the cone coordinate system. Based on this error, the PID controller adjusts the output of the drive element in real time, so that the moving cone group moves to the corresponding fixed base according to the received disarmament path information.

[0152] When the moving cone group reaches the corresponding fixed base, the corresponding control module detects the wireless charging transmitter signal and connects with it to establish a stable wireless charging connection.

[0153] This invention integrates wireless charging technology. When the mobile base of the intelligent traffic cone reaches the designated fixed base, it can establish a stable wireless charging connection by docking the wireless charging receiver with the wireless charging transmitter on the fixed base. This design not only simplifies the charging process and avoids the hassle of frequent battery replacements or manual plugging and unplugging of charging cables, but also improves the availability and maintenance efficiency of the device. Especially in scenarios involving long-term continuous operation, wireless charging technology significantly extends the device's operating time, reduces the risk of task interruption due to insufficient power, and further enhances the overall performance and user experience of this invention.

[0154] It should be noted that each time the intelligent traffic cones are deployed, they are automatically renumbered based on the RFID tags on their fixed bases to ensure accurate management of the device's location and identity. Furthermore, the central control system issues deployment or disarming commands upon receiving permission signals from traffic management authorities. This ensures operational safety.

[0155] This invention not only enables automatic deployment of intelligent traffic cones but also ensures efficient charging after disarming. During deployment, the central control system generates corresponding deployment path information based on the current position and pre-arranged formation of each mobile cone group and issues deployment commands, enabling each mobile cone group to move precisely to its designated position. Upon completion of the task, the system automatically plans the disarming path, guiding each mobile cone group back to its fixed base and automatically charging via wireless charging technology, ensuring the equipment is always in optimal working condition. This achieves fully automated management of the entire process from deployment to disarming and charging.

[0156] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0157] Furthermore, in this invention, descriptions involving terms such as "first," "second," and "a" are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0158] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0159] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

Claims

1. A control method for intelligent traffic cones, characterized in that, The intelligent traffic cone includes: A mobile cone group and a fixed base; the mobile cone group includes a control module, a camera, an algorithm module communicatively connected to the control module, and an inertial navigation module and a wheel speed sensor communicatively connected to the algorithm module; the inertial navigation module includes a gyroscope, an accelerometer, and a magnetic field sensor; wherein: the gyroscope is used to measure the angular velocity of the mobile cone group around its cone coordinate system X-axis, Y-axis, and Z-axis in real time; the accelerometer is used to detect the linear acceleration of the mobile cone group in the cone coordinate system in real time; the magnetic field sensor is used to measure the geomagnetic field strength of the mobile cone group in the cone coordinate system in real time. The control method includes: Establish a communication connection between the intelligent traffic cone and the central control system based on a fixed base; The algorithm module uses a convolutional neural network to process the image data collected in real time by the camera, analyzes the current position of the moving traffic cone group relative to the positioning reference point in the inertial coordinate system, and sends the position information to the central control system through the control module. When deployment is required, the central control system generates the corresponding deployment path information based on the current position of each moving traffic cone group and the pre-arranged formation, and issues the deployment command and the corresponding deployment path information including the destination position to the control module of the intelligent traffic cone. When the control module receives a deployment command and the corresponding deployment path information including the destination location: The inertial navigation module calculates the current attitude information of the moving cone group using a quaternion algorithm; the wheel speed sensor acquires the angular velocity of the driving wheels of the moving cone group and transmits it to the algorithm module; the attitude information includes the current orientation angle of the moving cone group in the inertial coordinate system; The current attitude information of the moving cone group is calculated using a quaternion algorithm via the inertial navigation module, specifically as follows: Quaternion state variables are defined based on the measurement data from the gyroscope; Define three-axis angular velocities; the three-axis angular velocities are the angular velocity components measured by the gyroscope in the cone coordinate system, which correspond to the rotational rates around the X-axis, Y-axis and Z-axis respectively; wherein, the cone coordinate system is a local coordinate system based on the moving cone group body, and its origin is located at the geometric center of the moving cone group, used to describe the attitude and orientation of the moving cone group in space; Predicting the rate of change of quaternion state variables based on triaxial angular velocity; Estimate quaternion state variables based on the rate of change of quaternion state variables; The component of gravity direction in the cone coordinate system in the accelerometer measurement data is obtained by estimating the quaternion state variables; the component of geomagnetic field direction in the cone coordinate system in the magnetic field sensor measurement data is obtained by estimating the quaternion; the two obtained components are combined into the observation vector Z; Calculate the Kalman gain and update the quaternion state variable estimates using the Kalman gain and the observation vector Z; specifically, the calculation of the Kalman gain involves: The prediction error covariance matrix P is initialized based on the measurement noise characteristics of the gyroscope and the uncertainty of the quaternion state variable estimation; the prediction error covariance matrix P is dynamically updated based on the uncertainty of the quaternion state variable estimation during the Kalman filter iteration process; Construct an observation matrix H, which represents the linearized mapping relationship between the measurement data of the accelerometer and the magnetic field sensor and the quaternion state variables, wherein the quaternion state variables are used to characterize the attitude of the moving cone group in three-dimensional space. The observation noise covariance matrix R is set according to the sensor noise characteristics of the accelerometer and the magnetic field sensor; the Kalman gain is calculated by the prediction error covariance matrix P, the observation matrix H and the observation noise covariance matrix R. The normalized updated quaternion state variable estimate is obtained as the normalized quaternion state variable; Extract the current orientation angle of the moving cone group in the inertial coordinate system from the normalized quaternion state variables; The algorithm module fuses the current attitude information with the angular velocity of the drive wheel to obtain the current actual direction angle. Based on the current position of the moving cone group in the inertial coordinate system and the deployment path information received by the control module, the target direction angle of the moving cone group in the inertial coordinate system is calculated in real time. The process of fusing the current attitude information with the angular velocity of the drive wheels through the algorithm module to obtain the current actual direction angle is as follows: The heading angle of the driving wheel relative to the initial direction in the inertial coordinate system is obtained by integrating the angular velocity of the driving wheel. The current orientation angle of the extracted moving cone group in the inertial coordinate system is weighted and fused with the heading angle of the drive wheel relative to the initial direction in the inertial coordinate system to obtain the fused orientation angle, which is the current actual orientation angle. The control module uses the current actual direction angle and the real-time calculated target direction angle to calculate the direction error in the cone coordinate system. Based on this error, the PID controller adjusts the output of the drive element in real time, so that the moving cone group moves to the corresponding endpoint position according to the received deployment path information.

2. The control method for intelligent traffic cones according to claim 1, characterized in that, The movable cone assembly further includes: a movable component and a cone; wherein: the movable component includes a movable base, a drive wheel, and a drive element; the camera is connected to the movable base; the movable base is provided with a receiving cavity; the drive element and the drive wheel are both connected to the bottom of the movable base; the output shaft of the drive element is connected to the drive wheel; the drive element can drive the drive wheel to rotate; a control module is disposed in the receiving cavity and connected to the drive element; the cone is disposed above the movable base, covering the opening of the receiving cavity.

3. The control method for intelligent traffic cones according to claim 2, characterized in that, The fixed base is equipped with an RFID tag, and the mobile base is also equipped with an RFID reader. The fixed base is provided with a docking space, and the mobile base can be accommodated in the docking space. At this time, the RFID reader can be close to the RFID tag.

4. The control method for intelligent traffic cones according to claim 3, characterized in that, The establishment of a communication connection between the intelligent traffic cone and the central control system based on the fixed base is specifically as follows: By reading the RFID tag information of the fixed base with an RFID reader, the intelligent traffic cones are automatically numbered and identified. Based on the numbering information, group division and communication frequency band configuration are completed, and a communication connection between the intelligent traffic cones and the central control system is established.

5. The control method for intelligent traffic cones according to claim 1, characterized in that, The deployment path information received by the control module includes: the target position and desired direction of the moving cone group in the inertial coordinate system at the current moment.

6. The control method for intelligent traffic cones according to claim 3, characterized in that, The bottom of the mobile base is also provided with a wireless charging receiver, and the docking space of the fixed base is provided with a wireless charging transmitter. When the mobile base is accommodated in the docking space, the wireless charging receiver is close to the wireless charging transmitter.

7. A control method for intelligent traffic cones according to claim 6, characterized in that, When disarming is required, the central control system assigns a corresponding disarming path information and a fixed base to each mobile cone group based on the current position of all mobile cone groups and the availability of each fixed base, and issues a disarming command and its corresponding disarming path information and fixed base position to the control module of the intelligent traffic cone. The control method further includes: when the control module receives a disarming command and its corresponding disarming path information and fixed base position: The inertial navigation module calculates the current attitude information of the moving cone group, and the wheel speed sensor obtains the angular velocity of the drive wheel and transmits it to the algorithm module. The algorithm module fuses the current attitude information with the angular velocity of the drive wheels to obtain the current actual orientation angle; the target orientation angle of the moving cone group in the inertial coordinate system is calculated in real time based on the current position of the moving cone group in the inertial coordinate system and the return path received by the control module. The control module uses the current actual direction angle and the real-time calculated target direction angle to calculate the direction error in the cone coordinate system. Based on this error, the PID controller adjusts the output of the drive element in real time, so that the moving cone group moves to the corresponding fixed base according to the received disarmament path information. When the moving cone group reaches the corresponding fixed base, the corresponding control module detects the wireless charging transmitter signal and connects with it to establish a stable wireless charging connection.

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