Visual cloud control platform for unmanned sweeper

Abstract

The visual cloud control platform comprises a vehicle data receiving module, a running state analysis module, an abnormal information feedback module, a data processing module, a data display module and a historical data storage module. According to the method, the vehicle running state parameters on the unmanned vehicle can be judged, a solution is given in real time when data are abnormal, the state of the unmanned vehicle is monitored in real time, meanwhile, equipment problems of the unmanned vehicle are rapidly solved, rapid repair and maintenance of the unmanned vehicle are achieved, the maintenance cost is reduced, and the working efficiency is improved. The running safety of the unmanned vehicle equipment is improved; in addition, real-time display of track information and cleaning state information of the unmanned vehicle can be achieved, a user can conveniently check the information, and the user experience feeling is effectively improved; in addition, the cleaning result can be evaluated and analyzed, and it is guaranteed that the cleaning effect is better.

Description

Technical Field

[0001] The present invention relates to the field of unmanned driving, and in particular to a visual cloud control platform for unmanned driving sweepers. Background Art

[0002] To improve street cleaning efficiency, the sanitation industry is gradually moving toward unmanned operations. Currently, this primarily involves autonomous street sweepers, replacing sanitation workers. However, a city's sweeping operations cover a vast area. To fully implement autonomous cleaning and improve efficiency, it is crucial to intelligently and in real time dispatch autonomous sweepers, display their operating status in real time, and promptly resolve any issues they encounter.

[0003] Current unmanned road sweepers generally offer features such as treading closely to the roadside, sweeping garbage, and automatically dumping it. Clearly, these vehicles have essentially automated cleaning operations. However, they lack monitoring and response capabilities for fault response, trajectory, cleaning performance, and the health of these vehicles. If problems arise with these devices, there's no way to promptly troubleshoot, identify, and resolve them. This results in low efficiency, high maintenance costs, and a diminished user experience.

[0004] In addition, the operation trajectory and cleaning data (cleaning status, cleaning area, operation time, etc.) of the unmanned sweeper can only be viewed on the unmanned sweeper, and cannot be viewed and analyzed in real time through other channels. It is also impossible to view and analyze the operation trajectories of multiple unmanned sweepers at the same time in the cloud. The convenience is low and it is impossible to evaluate the cleaning effect and operation trajectory.

[0005] Therefore, the existing technology has yet to be improved. Summary of the Invention

[0006] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a visual cloud control platform for unmanned sweepers, aiming to solve the problem of lack of monitoring of unmanned sweepers in the prior art, which makes it impossible to solve problems arising from unmanned sweeper equipment in a timely manner, affecting the cleaning effect; at the same time, it solves the problem of being unable to view information such as vehicle operation trajectory in real time, reducing user experience.

[0007] The technical solution of the present invention is as follows: A visual cloud control platform for unmanned road sweepers, comprising:

[0008] A vehicle data receiving module is used to receive vehicle operating status parameters sent by an unmanned vehicle; the vehicle data receiving module communicates with a wireless communication module on the unmanned vehicle, and the vehicle operating status parameters are sent to the vehicle data receiving module through the wireless communication module.

[0009] The operating status analysis module is used to evaluate the vehicle operating status parameters using a built-in data analysis model and determine whether the vehicle equipment is normal based on the evaluation results. This analysis process involves real-time analysis of the vehicle operating status parameters sent by the unmanned vehicle to determine whether there are any anomalies.

[0010] The system is configured to transmit information about any vehicle equipment anomalies and solutions to the unmanned vehicle's abnormality information feedback module based on the vehicle equipment's normal operation determination sent by the operating status analysis module. After the abnormality information feedback module transmits the solution information to the unmanned vehicle, the user can promptly inspect and repair the vehicle equipment, thereby enabling prompt identification and rapid resolution of issues.

[0011] Obviously, the visual cloud control platform for unmanned sweepers in the present invention can analyze and evaluate relevant data after receiving the vehicle operation status parameters. If there is an abnormality, it will be immediately sent to the abnormal information feedback module. The abnormal information feedback module will give corresponding solutions according to the existing abnormal situation and form solution information, so that the unmanned vehicle can take relevant response measures in time, solve related problems in time, ensure its normal operation, reduce equipment maintenance costs, and improve work efficiency.

[0012] In one embodiment, the vehicle data receiving module is further configured to receive vehicle trajectory data. The vehicle data receiving module directly communicates with a positioning system on the unmanned vehicle, which is generally a GPS module or a SLAM positioning module on the unmanned vehicle.

[0013] In one embodiment, the unmanned road sweeper visualization cloud control platform further includes a data processing module for calculating the vehicle trajectory data and generating trajectory information. The data processing module processes the trajectory data primarily to convert the raw vehicle trajectory data into trajectory information suitable for display, thereby facilitating the display and making it easier for users to understand and understand at a glance, thereby improving the user experience.

[0014] In one embodiment, the unmanned road sweeper visualization cloud control platform further includes a data display module configured to receive the trajectory information output by the data processing module and display the trajectory information in a graphical or data form, such as directly displaying the calculated data value or displaying a trajectory graph obtained by calculation and fitting.

[0015] In one embodiment, the vehicle data receiving module is further configured to receive cleaning status information transmitted by the unmanned vehicle; and the data display module is further configured to receive the cleaning status information transmitted by the vehicle data receiving module and display it in text or data form. When the cleaning status information is required, the user selects "View cleaning status information" to display it.

[0016] In another embodiment, the aforementioned unmanned road sweeper visualization cloud control platform further includes a historical data storage module for storing the trajectory information and cleaning status information. Therefore, when historical trajectory information or cleaning status information is needed, the data display module can be used to display the relevant historical data, allowing evaluation of the unmanned vehicle's driving and cleaning status, thereby meeting higher user requirements and effectively improving the user experience.

[0017] In one embodiment, the data analysis model built into the operating status analysis module is a threshold analysis model and / or a trend analysis model and / or a fault diagnosis model.

[0018] In another embodiment, the abnormal information feedback module includes a preset fault library. Therefore, when a vehicle device is not operating normally, a solution can be proposed based on the problem. The preset fault library has already proposed multiple solutions based on common problems, so when a problem is received, timely feedback can be provided to quickly assist the unmanned vehicle device in resolving the problem.

[0019] In one embodiment, the data processing module uses a map engine processing method and / or a moving average method and / or a Kalman filter method and / or a Bezier curve fitting method and / or a path optimization processing method and / or a data compression processing method to calculate the vehicle operation trajectory data.

[0020] In one embodiment, the cleaning status information includes: whether the cleaning operation is in progress and / or cleaning efficiency and / or cleaning environment information.

[0021] In summary, the visual cloud control platform for unmanned road sweepers proposed in this paper has the following beneficial effects:

[0022] 1. When unmanned vehicle equipment is not operating normally, it can propose solutions based on the problem, quickly assist unmanned vehicle equipment to solve the problem and reduce maintenance costs;

[0023] 2. It can display vehicle trajectory information, allowing users to check and evaluate cleaning tracks at any time, understand cleaning status in real time, and improve user experience;

[0024] 3. The cleaning status of the unmanned vehicle can be understood in real time through the display of cleaning status information, which improves the user's control over the cleaning task and enables timely response measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0026] Figure 1 This is a principle block diagram of the present invention.

[0027] Among them: vehicle data receiving module 1, operation status analysis module 2, abnormal information feedback module 3, data processing module 4, data display module 5, historical data storage module 6. DETAILED DESCRIPTION

[0028] To make the objectives, technical solutions, and effects of the present invention more clear and distinct, the present invention is further described in detail below. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. The embodiments of the present invention are described below with reference to the accompanying drawings.

[0029] Please refer to Figure 1 A visualization cloud control platform for unmanned sweepers includes: a vehicle data receiving module 1, an operation status analysis module 2, an abnormal information feedback module 3, a data processing module 4, a data display module 5, and a historical data storage module 6; it can judge the vehicle operation status parameters on the unmanned vehicle, and give a solution in real time when there is an abnormality in the data, realize real-time monitoring of the equipment status of the unmanned vehicle, realize the rapid resolution of the equipment problems of the unmanned vehicle, realize its rapid repair and maintenance, reduce maintenance costs, and improve the safety of the operation of the unmanned vehicle; in addition, it can realize real-time display of data on the unmanned vehicle, which is convenient for users to view and effectively improve the user experience; in addition, it can also evaluate and analyze the cleaning results to ensure better cleaning effects.

[0030] Specifically, in this embodiment, the vehicle data receiving module 1 is used to receive vehicle operating status parameters sent by the unmanned vehicle; the vehicle operating status parameters are battery power, parameters of each motor used for driving (such as the sweeping drive motor, garbage turning drive motor, etc.) (motor speed, current, temperature, etc.), the degree of filter blockage in the garbage hopper, the water spraying status of the sprinkler in the garbage hopper, sensor status and other data. These data are collected by relevant data collection equipment (existing) on ​​the unmanned vehicle and transmitted to the vehicle data receiving module 1 in the present invention through wireless communication (4G / 5G / WIFI, etc.).

[0031] Specifically, in this embodiment, the operating status analysis module 2 is used to evaluate the vehicle operating status parameters using a built-in data analysis model and determine whether the vehicle equipment is functioning properly based on the evaluation results. This analysis process involves real-time analysis of the vehicle operating status parameters transmitted by the unmanned vehicle to determine whether any anomalies exist. Specifically, the data analysis model built into the operating status analysis module 2 may be a threshold analysis model, a trend analysis model, and / or a fault diagnosis model.

[0032] The threshold analysis model works by setting a threshold within a normal range for each vehicle operating parameter. When a parameter exceeds the threshold, it is considered abnormal. For example, if the battery level threshold is set to 20%, then if the battery level in the received vehicle operating parameters is below 20%, the battery level is considered low.

[0033] The trend analysis model works by analyzing the changing trends of vehicle operating parameters over time and determining whether an abnormal trend exists by exceeding a set threshold. For example, if the filter clogging level continues to increase and exceeds a set threshold, the filter is considered clogged.

[0034] The fault diagnosis model works by modeling the failure modes of autonomous vehicle equipment based on failure mode and effects analysis (FMEA) or fault tree analysis (FTA). The model then uses associated parameters to determine if a component is faulty. For example, motor current, temperature, and other parameters can be analyzed to determine if a motor is faulty.

[0035] The specific data analysis model selected by the operation status analysis module 2 can be determined according to actual needs; in addition, it should be noted that, in this embodiment, the operation status analysis module 2 can also conduct a comprehensive evaluation of all vehicle operation status parameters after analysis and evaluation, thereby conducting a comprehensive evaluation of the unmanned vehicle equipment, analyzing its health status, and outputting normal, abnormal, warning and other results, which can be specifically set according to actual needs.

[0036] Specifically, in this embodiment, the abnormal information feedback module 3 is used to send abnormal vehicle equipment information and solution information to the unmanned vehicle based on the judgment result of whether the vehicle equipment is normal sent by the operating status analysis module 2. After the abnormal information feedback module 3 sends the solution information to the unmanned vehicle, the unmanned vehicle equipment can be inspected and repaired in a timely manner, thereby realizing timely discovery and rapid resolution of problems. A preset fault library is set up in the abnormal information feedback module 3; the preset fault library contains solutions to common faults. For example, when the battery is detected to be low, the preset fault library provides a "please charge" solution to remind the corresponding unmanned vehicle to perform a charging operation (the unmanned vehicle charges itself or manually). Obviously, when the vehicle equipment is operating abnormally, a solution can be proposed based on the problem, and timely feedback can be provided when the problem is received, quickly assisting the unmanned vehicle equipment to solve the problem and reduce maintenance costs.

[0037] Specifically, in this embodiment, the vehicle data receiving module 1 is also used to receive vehicle trajectory data. The vehicle data receiving module 1 directly communicates with the unmanned vehicle's positioning system, typically a GPS module or SLAM positioning module. Specifically, after obtaining vehicle trajectory data (such as timestamps, longitude and latitude coordinates, and speed), the positioning system's backend server pushes the data to the vehicle data receiving module 1 via WebSocket or HTTP.

[0038] Specifically, in this embodiment, the data processing module 4 is used to calculate the vehicle running trajectory data and generate trajectory information. The data processing module 4 uses a map engine processing method and / or a moving average method and / or a Kalman filter method and / or a Bezier curve fitting method and / or a path optimization processing method and / or a data compression processing method to calculate the vehicle running trajectory data.

[0039] The mapping engine processing method utilizes a mapping engine (such as AutoNavi, Baidu Maps, or Google Maps) to process vehicle trajectory data. Map engines can provide features such as geographic information correction, route optimization, and geo-fencing.

[0040] The principle of the moving average method is to take the average value of the trajectory points in the continuous vehicle running trajectory data to reduce the jitter of the trajectory.

[0041] The principle of the Kalman filter method is to dynamically estimate the vehicle running trajectory data, and is applicable to the situation where there is noise in the vehicle running trajectory data.

[0042] The principle of the Bezier curve fitting method is to fit the vehicle running trajectory data with a Bezier curve to make the trajectory smoother and in line with the actual running conditions.

[0043] The principle of the path optimization processing method is: if there are anomalies in the vehicle operation trajectory data (such as the vehicle taking a detour or repeating the path), a path optimization algorithm (such as the A* algorithm, Dijkstra algorithm, etc.) can be used to optimize the trajectory.

[0044] The principle of the data compression method is to compress the vehicle trajectory data to reduce the amount of data stored and transmitted. For example, the Douglas-Peucker algorithm can be used to simplify the trajectory points in the vehicle trajectory data and retain the key points.

[0045] Specifically, the corresponding data processing method can be selected according to the complexity and display requirements of the received vehicle operation trajectory data. It should be noted that the trajectory information generated by the data processing module 4 mainly includes: trajectory points, smoothed trajectories, etc. The main purpose of its processing is to process the original vehicle operation trajectory data into trajectory information suitable for display, so as to facilitate display, facilitate users to check the cleaning trajectory at any time, evaluate it, understand the cleaning status in real time, and improve user experience.

[0046] Specifically, in this embodiment, the data display module 5 is used to receive the trajectory information output by the data processing module 4 and display the trajectory information in a graphical or data form. For example, the calculated data values ​​(coordinates) may be directly displayed, or a trajectory diagram obtained by calculation and fitting may be displayed. Specifically, graphical forms include: a trajectory diagram (using a map as a background to display the vehicle's running trajectory. The running trajectory can be displayed in different colors or line styles to show different running states) and a real-time trajectory (dynamically displaying the current running trajectory of the unmanned vehicle, and the trajectory is updated in real time as the unmanned vehicle actually moves).

[0047] In addition, when the data display module 5 displays data, the user can view the details of the running track by zooming and dragging the map on its display page; the user can also filter the running track according to conditions such as time and the number of the unmanned vehicle to meet their viewing requirements.

[0048] Specifically, in this embodiment, the vehicle data receiving module 1 is further configured to receive cleaning status information transmitted by the unmanned vehicle; the data display module 5 is further configured to receive the cleaning status information transmitted by the vehicle data receiving module 1 and display it in text form (e.g., indicating that the vehicle is in a cleaning operation) or data form (e.g., a specific numerical value of the cleaning area). Specifically, the cleaning status information includes: whether the vehicle is in a cleaning operation and / or cleaning efficiency and / or cleaning environment information; the cleaning efficiency currently includes: cleaning area, operation duration, water consumption, power consumption, and task completion rate; the unmanned vehicle has different cleaning task modes. When there is not much garbage, it can be set to a patrol mode, which means that in actual operation, intelligent processing such as sweeping brush lifting and watering switch logic adjustment will be performed according to the actual environmental conditions. By displaying the cleaning efficiency-related data, users can more easily understand why the sweeping brush and watering switches are sometimes on and sometimes off, effectively understanding the cleaning operation status of the unmanned vehicle. The cleaning environment information includes: obstacles and dust concentrations detected by sensors on the unmanned vehicle; the purpose of the present invention in receiving and displaying cleaning environment information is: in the cleaning operation of the unmanned vehicle, the safety of people / vehicle body / surrounding facilities and property needs to be considered. When an obstacle is identified, it is necessary to pause / detour / or even make an emergency stop (the user can make relevant control instructions based on the received data, remote control or on-site control), which is an information factor for safe operation in auxiliary cleaning. The display of obstacles can make the user know more clearly why the equipment did not go straight / advance according to the original route, and let the user understand that it is because of obstacles that the detour / stop is caused, so that the user can make timely response decisions; in addition, the collection of information such as dust concentration can also reduce the loss of vehicle equipment and extend its service life for the use of unmanned vehicles in intelligent cleaning operations, which can save investment costs for users.

[0049] Specifically, in this embodiment, the historical data storage module 6 is used to store the trajectory information and cleaning status information. The data stored in the historical data storage module 6 is used for subsequent query, analysis and display; therefore, when it is necessary to view the historical trajectory information or cleaning status information of different dates or time periods, the relevant historical data can be displayed through the data display module 5 to evaluate the driving conditions and cleaning status of the unmanned vehicle equipment, which can meet higher usage requirements and effectively improve the user experience. Specifically, the historical data storage module 6 stores data in a relational database, such as a MySQL database, a PostgreSQL database, or a non-relational database, such as a MongoDB database, a Redis database. In addition, the data stored in the historical data storage module 6 will be stored in the form of files, such as CSV files and JSON files.

[0050] From the above, it can be seen that the visual cloud control platform for unmanned sweepers in the present invention can analyze and evaluate relevant data after receiving the vehicle operation status parameters. If there is an abnormality, it will be sent to the abnormal information feedback module 3 immediately. The abnormal information feedback module 3 will give a corresponding solution according to the existing abnormal situation and form solution information, so that the unmanned vehicle can take relevant response measures in time, solve related problems in time, ensure its normal operation, reduce equipment maintenance costs, and improve work efficiency; at the same time, it can realize the display of trajectory information and cleaning status information, so that users can check the cleaning trajectory and operation status at any time, evaluate them, understand the cleaning status in real time, and effectively improve the user experience.

[0051] It should be understood that the application of the present invention is not limited to the above examples. For those skilled in the art, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A visual cloud control platform for unmanned road sweepers, characterized by: include: A vehicle data receiving module for receiving vehicle operating status parameters; An operating status analysis module for evaluating the vehicle operating status parameters using a built-in data analysis model and determining whether the vehicle equipment is operating normally based on the evaluation results; It is used to send abnormal vehicle equipment information and solution information to the abnormal information feedback module of the unmanned vehicle based on the judgment result of whether the vehicle equipment sent by the operation status analysis module is normal.

2. The visual cloud control platform for unmanned road sweepers according to claim 1 is characterized in that: The vehicle data receiving module is also used to receive vehicle running track data.

3. The visual cloud control platform for unmanned road sweepers according to claim 2 is characterized in that: Also includes: A data processing module for calculating the vehicle running trajectory data and generating trajectory information.

4. The visual cloud control platform for unmanned road sweepers according to claim 3 is characterized in that: Also includes: A data display module is used to receive the trajectory information output by the data processing module and display the trajectory information in a graphical form or a data form.

5. The visual cloud control platform for unmanned road sweepers according to claim 4 is characterized in that: The vehicle data receiving module is further used to receive the cleaning status information sent by the unmanned vehicle; the data display module is further used to receive the cleaning status information sent by the vehicle data receiving module and display it in text form or data form.

6. The visual cloud control platform for unmanned road sweepers according to claim 5 is characterized in that: Also includes: A historical data storage module is used to store the trajectory information and cleaning status information.

7. The visual cloud control platform for unmanned road sweepers according to claim 1 is characterized in that: The data analysis model built into the operation status analysis module is a threshold analysis model and / or a trend analysis model and / or a fault diagnosis model.

8. The visual cloud control platform for unmanned road sweepers according to claim 1 is characterized in that: A preset fault library is provided in the abnormal information feedback module.

9. The visual cloud control platform for unmanned road sweepers according to claim 3 is characterized in that: The data processing module calculates the vehicle running trajectory data using a map engine processing method and / or a moving average method and / or a Kalman filter method and / or a Bezier curve fitting method and / or a path optimization processing method and / or a data compression processing method.

10. The visual cloud control platform for unmanned road sweepers according to claim 5, characterized in that: The cleaning status information includes: whether the cleaning operation is in progress and / or cleaning efficiency and / or cleaning environment information.

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