Multi-sensor data acquisition method and system based on Linux platform

Abstract

The application provides a multi-sensor data acquisition method based on a Linux platform, comprising the following steps: S101, sampling mode switching. The multi-sensor data acquisition method and system based on the Linux platform provided by the application can quickly switch the acquisition mode, automatically complete the pre-sampling equipment verification and abnormal recovery, one-key start the multi-sensor synchronous acquisition, verify the data integrity and effectiveness after sampling and realize the automatic hierarchical archiving of data, and the method has good scalability, can simplify the multi-sensor data acquisition preparation process, improve the data synchronization and quality control effect, establish a unified acquisition and storage management mechanism, simultaneously support the flexible expansion of multiple types of sensors and functions, and solve the problems of complex multi-sensor data acquisition process, difficult data synchronization and quality control, non-unified management mechanism and poor scalability.

Description

Technical Field

[0001] This invention relates to the field of data acquisition and processing in autonomous driving and intelligent perception systems, and particularly to a multi-sensor data acquisition method and system based on the Linux platform. Background Technology

[0002] With the rapid development of autonomous driving technology, perception systems play a central role in vehicle environmental understanding and decision-making control. To achieve high-precision environmental perception and positioning, autonomous driving systems typically need to fuse data from multiple sensors, including image sensors, LiDAR, inertial navigation systems (INS), and global positioning systems (GPS). This multi-source data is not only used for training and validating algorithm models, but also plays a crucial role in the construction of high-precision maps and dynamic environment modeling.

[0003] However, existing multi-sensor data acquisition workflows still have many shortcomings. First, the preparation process is complex. Because multiple types of sensor devices need to be connected and configured simultaneously, operators must initialize, set parameters, and synchronize the time for each sensor separately, making the workflow cumbersome and prone to errors. Second, data synchronization and quality control are difficult. Different sensors have different time bases and sampling frequencies; without an effective synchronization and verification mechanism, data frame misalignment, time drift, or partial data loss can easily occur, affecting the accuracy of subsequent algorithm training and map construction. Furthermore, the lack of a unified management mechanism for data acquisition and storage often requires multiple manual interventions, increasing the operational burden and error risk. Due to the low data availability, operators often need to perform repeated data collection to ensure data integrity, resulting in a waste of time and human resources and high overall development costs.

[0004] Therefore, it is necessary to provide a multi-sensor data acquisition method and system based on the Linux platform to solve the above-mentioned technical problems. Summary of the Invention

[0005] This invention provides a multi-sensor data acquisition method and system based on the Linux platform, which solves the problems of complex multi-sensor data acquisition process, difficulty in data synchronization and quality control, inconsistent management mechanism and poor scalability in existing multi-sensor data acquisition systems.

[0006] To address the aforementioned technical problems, this invention provides a multi-sensor data acquisition method based on the Linux platform, comprising the following steps: S101, Data Acquisition Mode Switching: Supports quick and convenient switching between different types of data acquisition modes to adapt to data acquisition tasks in multiple scenarios. S102. Pre-acquisition check: Verify the integrity and legality of the data acquisition configuration file, and check the operating status of each sensor hardware and data source. When an abnormal configuration or sensor status is detected, provide an error message and automatically attempt to reinitialize or restore the abnormal sensor. If the abnormality cannot be restored, prevent the acquisition from starting. S103, One-click data acquisition: After checking that all indicators are normal before data acquisition, the formal data acquisition can be quickly started through one-click operation of software commands or hardware buttons, coordinating the acquisition and recording of multi-source data by each sensor in a synchronous sequence. S104. Post-acquisition inspection: Perform critical data inspection on the acquired data package. Through data integrity detection and timestamp consistency verification, detect whether there are problems such as missing frames, abnormal time intervals, and data format errors in the acquired data, and verify the integrity and validity of the acquired data. S105. Data archiving: Automatically name and hierarchically store the collected data according to the time information, type information and collection task identifier of the collection mode, and archive both normal data packets and abnormal data packets. Furthermore, this method has good scalability and conforms to the open / closed principle, so as to support the flexible expansion of multiple types of sensors and data processing functions.

[0007] Preferably, the data acquisition mode switching in S101 supports rapid switching between perception data acquisition mode and mapping data acquisition mode, and the corresponding mode can be flexibly selected according to different acquisition needs such as perception modeling and high-precision map construction.

[0008] Preferably, the pre-acquisition check in S102 sequentially detects the operating status of the inertial navigation system, the working status of the lidar, and the imaging status of the camera, and verifies the time synchronization of the multiple sensors, while also verifying whether the inertial navigation data meets the mapping accuracy requirements.

[0009] Preferably, the post-acquisition inspection of S104 specifically includes checking whether the data frame rate meets the preset standard, whether the inertial navigation data continuously meets the mapping requirements, whether the time synchronization between the data of each sensor is normal, and when data abnormality is detected, feeding back the specific abnormality type and possible cause to facilitate problem location and troubleshooting.

[0010] Preferably, the data archiving in S105 implements hierarchical storage of collected data according to the collection task identifier, timestamp, and collection type, which enables rapid retrieval and management of collected data. At the same time, the archiving of abnormal data packets avoids the loss of critical data and improves the integrity and traceability of data management.

[0011] Preferably, the scalability of the method is achieved through a modular architecture design, which enables the expansion of new acquisition types or data processing functions through plug-ins without modifying the existing module code.

[0012] To address the above problems, this invention also provides a multi-sensor data acquisition system based on the Linux platform, comprising: The data acquisition mode switching module is used to quickly and conveniently switch between different types of data acquisition modes according to acquisition needs, adapting to data acquisition tasks in multiple scenarios. The pre-collection inspection module is used to verify the integrity and legality of the data acquisition configuration file before formal data collection. It also detects the operating status of each sensor hardware and data source, provides error prompts and performs sensor abnormality recovery operations when an anomaly is detected. The one-click acquisition module is used to quickly start the formal data acquisition process after the pre-acquisition check module confirms that the acquisition configuration and sensor status are normal, by receiving software commands or hardware button trigger signals, and coordinating the synchronous acquisition of multi-source data by each sensor. The post-collection verification module is used to perform key data checks on the data collection packages generated by the collection. It verifies the integrity and validity of the collected data through the data integrity detection submodule and the timestamp consistency verification submodule. The data archiving module is used to automatically name and hierarchically store the collected data according to the time information, type information and collection task identifier of the collection mode, and to archive both normal data packets and abnormal data packets.

[0013] Preferably, the data acquisition mode switching module supports switching between perception data acquisition mode, mapping data acquisition mode and other extended acquisition modes, and can be flexibly selected according to different acquisition needs such as perception modeling and high-precision map construction. The detection content of the post-acquisition verification module includes whether the data frame rate meets the preset standard, whether the inertial navigation data continuously meets the mapping requirements, whether the time synchronization of the data of each sensor is normal, and whether there are missing frames or format errors in the data. When an anomaly is detected, the specific anomaly type and possible cause are fed back.

[0014] Preferably, the system also includes an extension module. The extension module adopts a modular architecture design, conforms to the open / closed principle, and can extend new acquisition types or data processing functions through plug-ins without modifying the existing module code, supporting the access of multiple types of sensors.

[0015] Preferably, the camera includes a mounting plate with mounting holes on all four sides of the top of the mounting plate. A buffer assembly is provided on the top of the mounting plate, and the buffer assembly includes a mounting frame. The mounting frame is fixedly installed on the top of the mounting plate. Multiple damping rods are fixedly installed on the bottom of the inner side of the mounting frame. Buffer springs are sleeved on the outer sides of the multiple damping rods. A movable plate is fixedly installed on the top of the multiple damping rods, and the camera body is fixedly installed on the top of the movable plate.

[0016] Compared with related technologies, the multi-sensor data acquisition method and system based on the Linux platform provided by this invention have the following advantages: This invention provides a multi-sensor data acquisition method and system based on the Linux platform. Through the coordinated steps of data acquisition mode switching, pre-acquisition checks, one-click data acquisition, post-acquisition checks, and data archiving, it can quickly switch acquisition modes, automatically complete pre-acquisition equipment verification and anomaly recovery, initiate multi-sensor synchronous acquisition with one click, verify data integrity and validity post-acquisition, and achieve automatic hierarchical data archiving. The method also possesses good scalability. It simplifies the multi-sensor data acquisition preparation process, improves data synchronization and quality control, establishes a unified acquisition and storage management mechanism, and supports flexible expansion of multiple sensor types and functions. It solves the problems of complex multi-sensor data acquisition processes, difficult data synchronization and quality control, inconsistent management mechanisms, and poor scalability in existing multi-sensor data acquisition systems. Attached Figure Description

[0017] Figure 1 This is a flowchart of the multi-sensor data acquisition method based on the Linux platform in this invention; Figure 2 This is an implementation diagram of the multi-sensor data acquisition method based on the Linux platform in this invention; Figure 3 Block diagram of the multi-sensor data acquisition system based on the Linux platform in this invention; Figure 4 This is a schematic diagram of the camera structure provided by the present invention; Figure 5 for Figure 4 The cross-sectional structure shown is an arbitrary diagram.

[0018] The diagram is labeled as follows: 310, Data Acquisition Mode Switching Module; 320, Pre-Acquisition Inspection Module; 330, One-Click Acquisition Module; 340, Post-Acquisition Verification Module; 350, Data Archiving Module. 1. Mounting plate; 11. Mounting hole; 2. Buffer assembly; 21. Mounting frame; 22. Moving plate; 23. Damping rod; 24. Buffer spring; 3. Camera body. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Please refer to the following: Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 ,in, Figure 1 This is a flowchart of the multi-sensor data acquisition method based on the Linux platform in this invention; Figure 2This is an implementation diagram of the multi-sensor data acquisition method based on the Linux platform in this invention; Figure 3 Block diagram of the multi-sensor data acquisition system based on the Linux platform in this invention; Figure 4 This is a schematic diagram of the camera structure provided by the present invention; Figure 5 for Figure 4 The cross-sectional structure shown is an arbitrary diagram.

[0021] The multi-sensor data acquisition method based on the Linux platform includes the following steps: S101, Data Acquisition Mode Switching: Supports quick and convenient switching between different types of data acquisition modes to adapt to data acquisition tasks in multiple scenarios. S102. Pre-acquisition check: Verify the integrity and legality of the data acquisition configuration file, and check the operating status of each sensor hardware and data source. When an abnormal configuration or sensor status is detected, provide an error message and automatically attempt to reinitialize or restore the abnormal sensor. If the abnormality cannot be restored, prevent the acquisition from starting. S103, One-click data acquisition: After checking that all indicators are normal before data acquisition, the formal data acquisition can be quickly started through one-click operation of software commands or hardware buttons, coordinating the acquisition and recording of multi-source data by each sensor in a synchronous sequence. S104. Post-acquisition inspection: Perform critical data inspection on the acquired data package. Through data integrity detection and timestamp consistency verification, detect whether there are problems such as missing frames, abnormal time intervals, and data format errors in the acquired data, and verify the integrity and validity of the acquired data. S105. Data archiving: Automatically name and hierarchically store the collected data according to the time information, type information and collection task identifier of the collection mode, and archive both normal data packets and abnormal data packets. Furthermore, this method has good scalability and conforms to the open / closed principle, so as to support the flexible expansion of multiple types of sensors and data processing functions.

[0022] The data acquisition system supports multiple data acquisition modes, including sensing data acquisition mode and mapping data acquisition mode. Specifically, such as... Figure 2 As shown, after the system starts, it first enters the mode selection phase, where users can switch between perception, mapping, or other extended modes according to task requirements. The system supports a quick switching mechanism, allowing flexible entry into corresponding data acquisition tasks in different modes to meet data acquisition needs in multiple scenarios; The system performs a sensor status self-check before data acquisition begins to ensure the reliability of the acquisition hardware and data source. Specifically, such as... Figure 2As shown, the system sequentially detects the operating status of the inertial navigation system, the working status of the lidar, and the imaging status of the camera, and verifies the time synchronization of multiple sensors. Simultaneously, the system also verifies whether the inertial navigation data meets the mapping accuracy requirements. When an anomaly is detected in a sensor, the system will automatically attempt to reinitialize or restore that sensor and output the corresponding anomaly type and prompt information. Once all pre-acquisition checks are passed, the system enters the formal data acquisition phase. Data acquisition can be triggered by a single button operation, which can be implemented via software commands or hardware buttons. Upon receiving the acquisition command, the system automatically initiates the preset acquisition process, coordinating all sensors to acquire and record multi-source data in a synchronous sequence, thereby achieving an efficient and reliable data acquisition process. After data acquisition is complete, the system performs integrity and consistency checks on the generated data packets. The checks include: whether the data frame rate meets preset standards, whether the inertial navigation data is continuous, and whether the time synchronization between data from various sensors is normal, to ensure the validity and usability of the acquired data. Specifically, such as... Figure 2 As shown, when an anomaly is detected in the data, the system will provide feedback on the specific anomaly type and possible causes, facilitating quick problem location and troubleshooting. After the anomaly is resolved, the data acquisition task for the corresponding scenario can be re-executed to ensure that the data quality meets the requirements for subsequent perception modeling or high-precision map construction. The system categorizes and archives the collected data packets based on the data acquisition scenario and timestamp information to facilitate subsequent data retrieval and use. Specifically, for example... Figure 2 As shown, the system not only stores and manages normal data packets during the archiving process, but also archives detected abnormal data packets to prevent the loss of critical data in situations where the problem is difficult to reproduce. This archiving mechanism effectively improves the integrity and traceability of data management, providing reliable data support for subsequent algorithm training and map construction.

[0023] The data acquisition mode switching of S101 supports rapid switching between perception data acquisition mode and mapping data acquisition mode, and can flexibly select the corresponding mode according to different acquisition needs such as perception modeling and high-precision map construction.

[0024] The pre-acquisition check in S102 sequentially checks the operating status of the inertial navigation system, the working status of the lidar, and the imaging status of the camera, and verifies the time synchronization of the multiple sensors, while also verifying whether the inertial navigation data meets the mapping accuracy requirements.

[0025] The post-acquisition inspection of S104 specifically includes checking whether the data frame rate meets the preset standard, whether the inertial navigation data continuously meets the mapping requirements, and whether the time synchronization between the data of each sensor is normal. When data abnormality is detected, the specific abnormality type and possible cause are fed back to facilitate problem location and troubleshooting.

[0026] The data archiving in S105 enables hierarchical storage of collected data according to the collection task identifier, timestamp, and collection type, allowing for rapid retrieval and management of collected data. At the same time, it avoids the loss of critical data by archiving abnormal data packets, thereby improving the integrity and traceability of data management.

[0027] The scalability of the method is achieved through a modular architecture design, which allows for the extension of new acquisition types or data processing functions through plug-ins without modifying existing module code.

[0028] To address the above problems, this invention also provides a multi-sensor data acquisition system based on the Linux platform, comprising: The data acquisition mode switching module 310 is used to quickly and conveniently switch between different types of data acquisition modes according to acquisition needs, adapting to data acquisition tasks in multiple scenarios. The pre-collection inspection module 320 is used to verify the integrity and legality of the data acquisition configuration file before formal data collection, and at the same time detect the operating status of each sensor hardware and data source. When an anomaly is detected, it provides error prompts and performs sensor anomaly recovery operations. The one-click acquisition module 330 is used to receive software instructions or hardware button trigger signals after the pre-acquisition inspection module 320 confirms that there are no abnormalities in the acquisition configuration and sensor status, and quickly start the formal data acquisition process to coordinate the synchronous acquisition of multi-source data by each sensor. The post-collection verification module 340 is used to perform key data checks on the data collection packages generated by the collection. It verifies the integrity and validity of the collected data through the data integrity detection submodule and the timestamp consistency verification submodule. The data archiving module 350 is used to automatically name and hierarchically store the collected data according to the time information, type information and collection task identifier of the collection mode, and to archive both normal data packets and abnormal data packets.

[0029] The data acquisition mode switching module 310 supports switching between perception data acquisition mode, mapping data acquisition mode and other extended acquisition modes. It can be flexibly selected according to different acquisition needs such as perception modeling and high-precision map construction. The detection content of the post-acquisition verification module includes whether the data frame rate meets the preset standard, whether the inertial navigation data continuously meets the mapping requirements, whether the time synchronization of the data of each sensor is normal, and whether there are missing frames or format errors in the data. When an anomaly is detected, the specific anomaly type and possible causes are fed back.

[0030] The system also includes an extension module, which adopts a modular architecture design that conforms to the open / closed principle. It can extend new acquisition types or data processing functions through plug-ins without modifying the existing module code, and supports the access of multiple types of sensors.

[0031] The multi-sensor data acquisition system based on the Linux platform according to embodiments of this application can switch to the corresponding acquisition mode according to different data acquisition application scenarios. Before formal acquisition, the system first performs routine checks to confirm whether each acquisition hardware device has started normally and to check whether the data status of various sensors is normal, such as whether the image data frame rate is stable and whether the inertial navigation system is normal. When all checks pass, the system can start the formal data acquisition process with one-click operation.

[0032] After data collection is completed, the system automatically verifies the results, including checking data frame rate, temporal continuity, and data integrity, to ensure that the collected data meets the quality requirements for perceptual model training, high-precision map construction, and other application scenarios. For data that passes the verification, the system further classifies and archives the data according to the collection mode and time information, improving the efficiency of data management and subsequent retrieval.

[0033] For specific limitations regarding the Linux-based multi-sensor data acquisition system, please refer to the limitations of the Linux-based multi-sensor data acquisition method described above, which will not be repeated here. The various modules of the aforementioned Linux-based multi-sensor data acquisition system can be implemented entirely or partially through software, hardware, or a combination thereof.

[0034] Compared with related technologies, the multi-sensor data acquisition method and system based on the Linux platform provided by this invention have the following advantages: By coordinating steps such as data acquisition mode switching, pre-acquisition checks, one-click data acquisition, post-acquisition checks, and data archiving, the system can quickly switch acquisition modes, automatically complete pre-acquisition equipment verification and anomaly recovery, initiate multi-sensor synchronous acquisition with one click, verify data integrity and validity after acquisition, and automatically archive data in a hierarchical manner. The method also boasts good scalability. It simplifies the multi-sensor data acquisition preparation process, improves data synchronization and quality control, establishes a unified acquisition and storage management mechanism, and supports flexible expansion of multiple sensor types and functions. This addresses the problems of complex multi-sensor data acquisition processes, difficult data synchronization and quality control, inconsistent management mechanisms, and poor scalability in existing multi-sensor data acquisition systems.

[0035] The camera includes a mounting plate 1, with mounting holes 11 on all four sides of the top of the mounting plate 1. A buffer assembly 2 is provided on the top of the mounting plate 1. The buffer assembly 2 includes a mounting frame 21, which is fixedly mounted on the top of the mounting plate 1. Multiple damping rods 23 are fixedly mounted on the bottom of the inner side of the mounting frame 21. Buffer springs 24 are sleeved on the outer sides of the multiple damping rods 23. A movable plate 22 is fixedly mounted on the top of the multiple damping rods 23. The camera body 3 is fixedly mounted on the top of the movable plate 22.

[0036] When in use, the bolt is passed through the mounting hole 11 and the bolt is threaded to the mounting surface to install the mounting plate 1. During subsequent use, when vibration occurs, the moving plate 22 will move up and down on the inner side of the mounting frame 21, thereby moving the camera body 3. While the moving plate 22 is moving, the damping rod 23 and the buffer spring 24 can extend and retract, thereby playing a buffering role and preventing damage to the camera body 3 caused by long-term vibration.

[0037] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A multi-sensor data acquisition method based on the Linux platform, characterized in that, Includes the following steps: S101, Data Acquisition Mode Switching: Supports quick and convenient switching between different types of data acquisition modes to adapt to data acquisition tasks in multiple scenarios. S102. Pre-acquisition check: Verify the integrity and legality of the data acquisition configuration file, and check the operating status of each sensor hardware and data source. When an abnormal configuration or sensor status is detected, provide an error message and automatically attempt to reinitialize or restore the abnormal sensor. If the abnormality cannot be restored, prevent the acquisition from starting. S103, One-click data acquisition: After checking that all indicators are normal before data acquisition, the formal data acquisition can be quickly started through one-click operation of software commands or hardware buttons, coordinating the acquisition and recording of multi-source data by each sensor in a synchronous sequence. S104. Post-acquisition inspection: Perform critical data inspection on the acquired data package. Through data integrity detection and timestamp consistency verification, detect whether there are problems such as missing frames, abnormal time intervals, and data format errors in the acquired data, and verify the integrity and validity of the acquired data. S105. Data archiving: Automatically name and hierarchically store the collected data according to the time information, type information and collection task identifier of the collection mode, and archive both normal data packets and abnormal data packets. Furthermore, this method has good scalability and conforms to the open / closed principle, so as to support the flexible expansion of multiple types of sensors and data processing functions.

2. The multi-sensor data acquisition method based on the Linux platform according to claim 1, characterized in that, The data acquisition mode switching of S101 supports rapid switching between perception data acquisition mode and mapping data acquisition mode, and can flexibly select the corresponding mode according to different acquisition needs such as perception modeling and high-precision map construction.

3. The multi-sensor data acquisition method based on the Linux platform according to claim 1, characterized in that, The pre-acquisition check in S102 sequentially checks the operating status of the inertial navigation system, the working status of the lidar, and the imaging status of the camera, and verifies the time synchronization of the multiple sensors, while also verifying whether the inertial navigation data meets the mapping accuracy requirements.

4. The multi-sensor data acquisition method based on the Linux platform according to claim 1, characterized in that, The post-acquisition inspection of S104 specifically includes checking whether the data frame rate meets the preset standard, whether the inertial navigation data continuously meets the mapping requirements, and whether the time synchronization between the data of each sensor is normal. When data abnormality is detected, the specific abnormality type and possible cause are fed back to facilitate problem location and troubleshooting.

5. The multi-sensor data acquisition method based on the Linux platform according to claim 1, characterized in that, The data archiving in S105 enables hierarchical storage of collected data according to the collection task identifier, timestamp, and collection type, allowing for rapid retrieval and management of collected data. At the same time, it avoids the loss of critical data by archiving abnormal data packets, thereby improving the integrity and traceability of data management.

6. The multi-sensor data acquisition method based on the Linux platform according to claim 1, characterized in that, The scalability of the method is achieved through a modular architecture design, which allows for the extension of new acquisition types or data processing functions through plug-ins without modifying existing module code.

7. A multi-sensor data acquisition system based on the Linux platform, characterized in that, include: The data acquisition mode switching module is used to quickly and conveniently switch between different types of data acquisition modes according to acquisition needs, adapting to data acquisition tasks in multiple scenarios. The pre-collection inspection module is used to verify the integrity and legality of the data acquisition configuration file before formal data collection. It also detects the operating status of each sensor hardware and data source, provides error prompts and performs sensor abnormality recovery operations when an anomaly is detected. The one-click acquisition module is used to quickly start the formal data acquisition process after the pre-acquisition check module confirms that the acquisition configuration and sensor status are normal, by receiving software commands or hardware button trigger signals, and coordinating the synchronous acquisition of multi-source data by each sensor. The post-collection verification module is used to perform key data checks on the data collection packages generated by the collection. It verifies the integrity and validity of the collected data through the data integrity detection submodule and the timestamp consistency verification submodule. The data archiving module is used to automatically name and hierarchically store the collected data according to the time information, type information and collection task identifier of the collection mode, and to archive both normal data packets and abnormal data packets.

8. The multi-sensor data acquisition system based on the Linux platform according to claim 7, characterized in that, The data acquisition mode switching module supports switching between perception data acquisition mode, mapping data acquisition mode and other extended acquisition modes. It can be flexibly selected according to different acquisition needs such as perception modeling and high-precision map construction. The detection content of the post-acquisition verification module includes whether the data frame rate meets the preset standard, whether the inertial navigation data continuously meets the mapping requirements, whether the time synchronization of the data of each sensor is normal, and whether there are missing frames or format errors in the data. When an anomaly is detected, the specific anomaly type and possible causes are fed back.

9. The multi-sensor data acquisition system based on the Linux platform according to claim 7, characterized in that, It also includes an extension module, which adopts a modular architecture design that conforms to the open / closed principle. It can extend new acquisition types or data processing functions through plug-ins without modifying the existing module code, and supports the access of multiple types of sensors.

10. The multi-sensor data acquisition method based on the Linux platform according to claim 3, characterized in that, The camera includes a mounting plate with mounting holes around its top four sides. A buffer assembly is provided on the top of the mounting plate, and the buffer assembly includes a mounting frame. The mounting frame is fixedly mounted on the top of the mounting plate. Multiple damping rods are fixedly mounted on the bottom of the inner side of the mounting frame. Buffer springs are sleeved on the outer sides of the multiple damping rods. A movable plate is fixedly mounted on the top of the multiple damping rods, and the camera body is fixedly mounted on the top of the movable plate.

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