Multi-robot cooperative self-adaptive negative pressure vehicle bottom dust collection method and robot

Abstract

The invention provides a multi-robot cooperative self-adaptive negative pressure vehicle bottom dust collection method and a robot, and the method comprises the steps that the robot scans the vehicle bottom contour of a current operation area, and constructs a three-dimensional map of the current operation area; based on the three-dimensional map, a self-adaptive negative pressure sealing mechanism is controlled, and a local closed dust collection cavity is formed between the robot and the vehicle bottom; a dust collection fan is started to conduct negative pressure dust collection, the dust condition in the locally-closed dust collection cavity is monitored in real time, and the wind direction and the operation power of the dust collection fan are adjusted; and carrying out multi-stage filtering treatment on the sucked dust-containing airflow until the dust collection work of all the operation areas is completed. By means of the dust collection device, negative pressure leakage can be effectively reduced, the dust collection efficiency is improved, meanwhile, the suction force and the wind direction are dynamically adjusted according to the dust concentration and distribution, and the problem that in the prior art, the vehicle bottom dust cleaning efficiency is poor is solved.

Description

Technical Field

[0001] This invention relates to the field of rail transit vehicle maintenance technology, and in particular to an adaptive negative pressure dust collection method and robot for multi-robot collaboration under the vehicle. Background Technology

[0002] With the rapid development of rail transit, subways and light rail vehicles, with their high capacity and efficiency, have become the backbone of urban public transportation. Maintaining the cleanliness of operating vehicles is not only a basic requirement for improving passenger experience, but also a crucial aspect of ensuring vehicle operation safety and extending equipment lifespan. During operation, the underside of rail transit vehicles, especially the bogie area, accumulates a large amount of dust, metal debris, and oil mixture from track and brake pad wear, as well as the external environment. If this accumulated dust is not cleaned in a timely manner, it can lead to a series of serious problems: Safety hazards: Thick dust accumulation may cover critical components such as sensors, terminals, and braking units, leading to poor heat dissipation, signal failure, or malfunction. In severe cases, it may cause equipment failure and affect driving safety.

[0003] Equipment wear and tear: Dust is abrasive and will accelerate the wear and tear of moving parts such as bogies, shorten the maintenance cycle and service life of parts, and increase the total life cycle operating cost.

[0004] Difficulty in maintenance: The dirty environment under the vehicle makes daily inspection and maintenance work extremely inconvenient, reducing maintenance efficiency and quality.

[0005] Currently, automated blowing equipment exists on the market for cleaning the underside of rail transit vehicles. However, their dust collection systems lack flexible sealing structures, failing to effectively conform to the vehicle's contours, leading to negative pressure leakage and low dust collection efficiency. Furthermore, due to the lack of intelligent sensing and control capabilities, the equipment cannot intelligently adjust the angle of the suction grille based on real-time dust distribution for precise collection, nor can it adaptively adjust the fan power according to dust concentration, resulting in energy waste. In addition, the terminal dust collection hopper still relies on manual cleaning, indicating low automation and becoming a bottleneck for overall cleaning efficiency.

[0006] There is currently no effective solution to the problem of poor efficiency in cleaning dust under vehicles in existing related technologies. Summary of the Invention

[0007] This invention provides an adaptive negative pressure dust collection method and robot for vehicle undercarriage using multi-robot collaboration, which solves the shortcomings of poor dust cleaning efficiency in existing related technologies, and achieves efficient and accurate collection and treatment of dust under the vehicle, greatly improving cleaning efficiency and automation level.

[0008] In a first aspect, the present invention provides a multi-robot collaborative adaptive negative pressure undercarriage dust collection method, comprising: The robot scans the outline of the vehicle's underside in the current work area to construct a three-dimensional map of the current work area; Based on the three-dimensional map, an adaptive negative pressure sealing mechanism is controlled to form a partially sealed dust collection chamber between the robot and the vehicle floor. Start the dust collection fan to collect dust under negative pressure, monitor the dust level in the local sealed dust collection chamber in real time, and adjust the airflow direction and operating power of the dust collection fan. The inhaled dust-laden airflow undergoes multi-stage filtration until dust collection is completed in all work areas.

[0009] According to the multi-robot collaborative adaptive negative pressure vehicle undercarriage dust collection method provided by the present invention, before the robots scan the vehicle undercarriage contour of the current working area and construct a three-dimensional map of the current working area, the method includes: The robot receives dust collection instructions from the central dispatch system and completes its self-check. The robot's self-test includes the chassis drive, dust collection fan, sensor module, adaptive negative pressure sealing mechanism, and communication module.

[0010] According to the present invention, a multi-robot collaborative adaptive negative pressure vehicle undercarriage dust collection method includes scanning the vehicle undercarriage contour of the current work area and constructing a three-dimensional map of the current work area, comprising: The robots use onboard 3D LiDAR or depth vision sensors to scan the vehicle's undercarriage outline within their respective areas of responsibility to obtain outline data. The contour data is compared and fitted with a pre-stored rut model to construct a three-dimensional map of the current work area and identify the spatial locations of key components, including bogies and pipelines.

[0011] According to the present invention, a multi-robot collaborative adaptive negative pressure vehicle undercarriage dust collection method, based on the three-dimensional map, controls an adaptive negative pressure sealing mechanism to form a partially sealed dust collection chamber between the robots and the vehicle undercarriage, comprising: Based on the three-dimensional map, the adaptive negative pressure sealing mechanism is driven to extend the retractable flexible skirt and adaptively fit the vehicle bottom surface, forming a partially sealed dust collection chamber between the robot and the vehicle bottom.

[0012] According to the present invention, a multi-robot collaborative adaptive negative pressure vehicle undercarriage dust collection method is provided, which monitors the dust situation in the locally sealed dust collection chamber in real time, including: The dust concentration in the locally sealed dust collection chamber is monitored using a dust concentration sensor; After dust is captured by the distributed sensing mechanism, the spatial distribution and accumulation of dust in the locally sealed dust collection chamber are used to generate a dust distribution heat map.

[0013] According to the present invention, a multi-robot collaborative adaptive negative pressure vehicle undercarriage dust collection method includes adjusting the airflow direction and operating power of the dust collection fan, comprising: Based on the dust distribution heat map, adjust the orientation and angle of the dust collection grille of the dust collection fan; Based on the dust concentration in the locally sealed dust collection chamber, the operating power of the dust collection fan is adaptively adjusted by the frequency converter.

[0014] According to the present invention, an adaptive negative pressure dust collection method for vehicle undercarriage using multi-robot collaboration performs multi-stage filtration on the inhaled dust-laden airflow, including: Dust-laden airflow enters the primary settling chamber, where large particles are separated from the airflow and fall into the dust collection hopper; The subsequent airflow penetrates the secondary filtration mechanism, where fine dust particles are trapped on the surface of the filter material, and clean air is discharged.

[0015] According to the multi-robot collaborative adaptive negative pressure vehicle undercarriage dust collection method provided by the present invention, if the dust concentration in the locally sealed dust collection chamber is lower than a preset completion threshold for a continuous period of time, the dust collection operation in the current work area is determined to be completed. The central dispatch system determines the task list based on the overall task list. If the dust collection operation in all work areas has been completed, the robot will perform automatic dust removal. Otherwise, the system will control the robot to move to the next work area to perform the dust collection operation.

[0016] Secondly, the present invention also provides a multi-robot collaborative adaptive negative pressure undercarriage dust collection robot, comprising: Chassis drive is used to control the robot's movement between different work areas; Dust collection fan, used to perform dust collection operations; The sensor module is used to scan the outline of the vehicle's underside and monitor dust concentration; An adaptive negative pressure sealing mechanism is used to create a locally sealed dust collection chamber between the robot and the vehicle floor; A communication module is used for the robot to interact with the central scheduling system.

[0017] According to the present invention, an adaptive negative pressure undercarriage dust collection robot with multi-robot collaboration is provided, wherein the sensor module includes: 3D LiDAR or depth vision sensor is used to scan the vehicle underside contour of the current work area and construct a three-dimensional map of the current work area; A dust concentration sensor is used to monitor the dust concentration within the locally sealed dust collection chamber.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a multi-robot collaborative adaptive negative pressure dust collection method for vehicle undercarriages. Through multi-robot collaborative operation, adaptive sealing, intelligent sensing, and closed-loop control, it achieves efficient and precise collection and treatment of dust under vehicles, significantly improving cleaning efficiency and automation level. The adaptive negative pressure sealing mechanism dynamically adjusts the dust collection fan, effectively reducing negative pressure leakage and improving dust collection efficiency. Simultaneously, it dynamically adjusts suction and airflow direction based on dust concentration and distribution, solving the problem of poor dust cleaning efficiency in existing related technologies. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the multi-robot collaborative adaptive negative pressure undercarriage dust collection method provided by the present invention; Figure 2 This is a schematic diagram illustrating the process of a robot performing dust collection operations in an embodiment of the present invention; Figure 3 This is a schematic diagram of the working scenario of the adaptive negative pressure sealing mechanism in an embodiment of the present invention; Figure 4 This is a structural block diagram of the dust collection system in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0022] This invention provides an adaptive negative pressure dust collection method for vehicle undercarriage using multi-robot collaboration. Figure 1 This is a flowchart of the multi-robot collaborative adaptive negative pressure vehicle undercarriage dust collection method provided by the present invention, as follows: Figure 1 As shown, the method includes the following steps: Step S101: The robot scans the outline of the vehicle's underside in the current work area to construct a 3D map of the current work area; Step S102: Based on the 3D map, control the adaptive negative pressure sealing mechanism to form a locally sealed dust collection chamber between the robot and the bottom of the vehicle; Step S103: Start the dust collection fan to collect dust under negative pressure, monitor the dust situation in the local sealed dust collection chamber in real time, and adjust the airflow direction and operating power of the dust collection fan. Step S104: Perform multi-stage filtration on the inhaled dust-laden airflow until dust collection in all work areas is completed.

[0023] In this method, firstly, each robot precisely scans the contour of the vehicle's underside within its assigned area, constructing a high-precision 3D map of the current work area in real time. Then, an adaptive negative pressure sealing mechanism is activated, adaptively conforming to the complex and uneven surface of the vehicle's underside, forming a physically isolated and reliable locally sealed dust collection chamber between the robot and the underside. Next, the dust collection fan is started at a preset initial power, rapidly drawing air from the locally sealed dust collection chamber, significantly lowering its internal pressure compared to the external ambient pressure, thus establishing a stable negative pressure dust collection space. Then, a dynamic operation state is entered, and a multimodal sensing system located within the chamber begins working, continuously monitoring the dust levels and adaptively adjusting the direction and power of the dust collection fan based on the monitoring results. Finally, the inhaled dust-laden airflow undergoes multi-stage filtration, expelling clean air until dust collection in all work areas is completed. Through multi-robot collaborative operation, adaptive sealing, intelligent sensing, and closed-loop control, efficient and precise collection and treatment of dust from under the vehicle is achieved, significantly improving cleaning efficiency and automation levels. By dynamically adjusting the dust collection fan through an adaptive negative pressure sealing mechanism, negative pressure leakage is effectively reduced and dust collection efficiency is improved. At the same time, the suction and airflow direction are dynamically adjusted according to the dust concentration and distribution, which solves the problem of poor dust cleaning efficiency under vehicles in existing related technologies.

[0024] Figure 2 This is a schematic diagram illustrating the process of a robot performing dust collection operations in an embodiment of the present invention, as shown below. Figure 2 As shown, in some embodiments, before step S101, in which the robot scans the vehicle underside contour of the current work area and constructs a three-dimensional map of the current work area, the robot receives a dust collection instruction from the central dispatch system and completes a robot self-check; the robot's self-check includes the chassis drive, dust collection fan, sensor module, adaptive negative pressure sealing mechanism, and communication module.

[0025] For example, the central dispatch system has a one-click start function. After startup, the robot is ready and completes a self-check, which includes checking the status of the robot chassis drive, dust collection fan, sensor module, adaptive negative pressure sealing mechanism, and communication module. If no abnormalities are found, a signal is sent and the robot begins operation.

[0026] Based on this, in step S101, the robot scans the vehicle underside profile of the current work area to construct a three-dimensional map of the current work area, including: the robot uses its onboard 3D LiDAR or depth vision sensor to scan the vehicle underside profile within its respective area of ​​responsibility to obtain profile data; the profile data is compared and fitted with a pre-stored rut model to construct a three-dimensional map of the current work area and identify the spatial location of key components; key components include bogies and pipelines.

[0027] Figure 3 This is a schematic diagram of the working scenario of the adaptive negative pressure sealing mechanism in an embodiment of the present invention, as shown below. Figure 3 As shown, in some embodiments, step S102, based on a three-dimensional map, controls an adaptive negative pressure sealing mechanism to form a partially sealed dust collection chamber between the robot and the vehicle bottom, including: according to the three-dimensional map, driving the adaptive negative pressure sealing mechanism to extend a retractable flexible skirt that adaptively fits the surface of the vehicle bottom to form a partially sealed dust collection chamber between the robot and the vehicle bottom.

[0028] For example, based on the acquired contour data, the robot drives an adaptive negative pressure sealing mechanism. A retractable flexible skirt extends upwards under precise control, actively and adaptively conforming to the complex, uneven surface of the vehicle's underside, forming a physically isolated and reliable locally sealed dust collection chamber between the robot and the vehicle's underside. This device consists of a main drive platform and a multi-segment independently controlled micro-servo electric cylinder drive array. The array's end is connected to a flexible skirt made of wear-resistant flexible composite material, with an adaptive microporous foamed silicone sealing strip embedded in its sealing edge. The core of the method lies in first acquiring the vehicle's underside contour data through 3D vision pre-scanning, and then driving the array to actively follow the contour extension. During the contact phase, each segment, based on feedback from integrated thin-film pressure sensors, uses a force-position hybrid closed-loop control strategy for independent and precise fine-tuning, driving the flexible skirt and sealing strip to actively conform to the complex curved surface, ensuring uniform sealing pressure, thereby forming a physically isolated and reliable locally negative pressure dust collection chamber between the robot and the vehicle's underside. This negative pressure environment ensures that blown-up dust is effectively confined within the chamber and provides power for subsequent collection.

[0029] In some embodiments, step S103, real-time monitoring of dust conditions in a locally sealed dust collection chamber, includes: monitoring the dust concentration in the locally sealed dust collection chamber using a dust concentration sensor; and generating a dust distribution heat map by capturing the spatial distribution and aggregation of dust in the locally sealed dust collection chamber after dust is generated using a distribution sensing mechanism.

[0030] Adjusting the airflow direction and operating power of the dust collection fan includes: adjusting the orientation and angle of the dust collection fan's suction inlet based on the dust distribution heat map; and adaptively adjusting the operating power of the dust collection fan via a frequency converter based on the dust concentration in the locally enclosed dust collection chamber.

[0031] For example, after entering the dynamic operation state, the multimodal sensing system located in the locally sealed dust collection chamber starts working. The dust concentration sensor continuously monitors the overall dust concentration in the locally sealed dust collection chamber, and the distribution sensing mechanism captures the spatial distribution and accumulation of dust in the locally sealed dust collection chamber in real time. The distribution sensing mechanism can be a visual sensor or an array of dust detectors.

[0032] Based on distribution sensing, the dust collection grille is adjusted. According to the real-time dust distribution heat map, the servo mechanism of the intelligent directional dust collection grille is driven to dynamically adjust the orientation and angle of its suction port, so as to achieve precise directional suction of high-concentration dust areas. Based on concentration sensing, the operating power of the dust collection fan is adaptively adjusted by the frequency converter to achieve optimal energy efficiency control of "strong wind for dense dust and weak wind for light dust".

[0033] In some embodiments, step S104 involves multi-stage filtration of the inhaled dust-laden airflow, including: the dust-laden airflow entering the primary settling chamber to separate large particles from the airflow and allow them to fall into the dust collection hopper; subsequent airflow passing through the secondary filtration mechanism, where fine dust is trapped on the surface of the filter material of the secondary filtration mechanism, and clean air is discharged.

[0034] In this embodiment, the dust-laden airflow first enters the primary settling chamber, where large particles separate from the airflow under gravity and fall into the dust collection hopper. Subsequently, the airflow penetrates the secondary filtration mechanism, where fine dust is trapped on the surface of the filter material, and clean air is discharged by a fan. The secondary filtration mechanism can be a filter cartridge or a filter bag.

[0035] Based on the above embodiments, if the dust concentration in the local sealed dust collection chamber is lower than the preset completion threshold for a continuous period of time, the dust collection operation in the current work area is determined to be completed. The central scheduling system makes a judgment based on the global task list. If the dust collection operation in all work areas has been completed, the robot performs automatic dust removal. Otherwise, the robot is controlled to move to the next work area to perform the dust collection operation, and a new round of "scan-seal-sensing-adjustment-collection" cycle is started for the next work area until the entire vehicle is covered.

[0036] In this embodiment, if the dust concentration in the locally sealed dust collection chamber is not lower than a preset completion threshold, the current work area will continue to be monitored and adaptively cleaned. Through the above-mentioned determination mechanism, full coverage cleaning of all work areas can be achieved.

[0037] After dust collection operations are completed in all work areas, the robot returns to the dust collection station and starts the automatic dust cleaning program. Using methods such as pulse backflushing, the dust adhering to the filter media of the secondary filtration mechanism is shaken off into the dust collection hopper. Without manual intervention, the filter media cleaning and dust collection are completed, achieving full automation of dust collection and cleaning and reducing operating costs.

[0038] Once all the work is completed, the central dispatch system aggregates all the data and generates a report on the cleaning operation.

[0039] This invention also provides a multi-robot collaborative adaptive negative pressure undercarriage dust collection robot. The following describes the multi-robot collaborative adaptive negative pressure undercarriage dust collection robot provided by this invention. The multi-robot collaborative adaptive negative pressure undercarriage dust collection robot described below can be referred to in correspondence with the multi-robot collaborative adaptive negative pressure undercarriage dust collection method described above. The robot includes: Chassis drive is used to control the robot's movement between different work areas; Dust collection fan, used to perform dust collection operations; The sensor module is used to scan the outline of the vehicle's underside and monitor dust concentration; An adaptive negative pressure sealing mechanism is used to create a locally sealed dust collection chamber between the robot and the vehicle floor; The communication module is used for the robot to interact with the central dispatch system.

[0040] In operation, each robot's sensor module first precisely scans the contours of the vehicle's underside within its assigned area, constructing a high-precision 3D map of the current work area in real time. Then, an adaptive negative pressure sealing mechanism is activated, adaptively conforming to the complex and uneven surface of the vehicle's underside, forming a physically isolated and reliable locally sealed dust collection chamber between the robot and the underside. Next, the dust collection fan starts at a preset initial power, rapidly drawing air from the locally sealed dust collection chamber, significantly lowering its internal pressure compared to the external ambient pressure, thus establishing a stable negative pressure dust collection space. Then, in dynamic operation mode, the multimodal sensing system located within the chamber begins operation. Sensor modules continuously monitor the dust levels within the chamber and adaptively adjust the direction and power of the dust collection fan based on the monitoring results. Finally, the inhaled dust-laden airflow undergoes multi-stage filtration, expelling clean air until dust collection in all work areas is complete. Through multi-robot collaborative operation, adaptive sealing, intelligent sensing, and closed-loop control, efficient and precise collection and processing of dust from under the vehicle is achieved, significantly improving cleaning efficiency and automation levels. By dynamically adjusting the dust collection fan through an adaptive negative pressure sealing mechanism, negative pressure leakage is effectively reduced and dust collection efficiency is improved. At the same time, the suction and airflow direction are dynamically adjusted according to the dust concentration and distribution, which solves the problem of poor dust cleaning efficiency under vehicles in existing related technologies.

[0041] Furthermore, the aforementioned robots can be equipped with, for example... Figure 4 The system shown, Figure 4 This is a structural block diagram of the dust collection system in an embodiment of the present invention. The system includes a sensing layer, a decision-making layer, and an execution layer. The sensing layer is mainly used for accurate scanning of the vehicle's undercarriage contour and monitoring the dust situation within the locally sealed dust collection chamber. The decision-making layer performs data fusion processing based on the monitored and sensed data, and generates control strategies through the central control system. The execution layer mainly controls the formation of the locally sealed dust collection chamber, the control and adjustment of the dust collection fan, and the multi-stage dust collection process.

[0042] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0043] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0044] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-robot collaborative adaptive negative pressure dust collection method for vehicle undercarriage, characterized in that, include: The robot scans the outline of the vehicle's underside in the current work area to construct a three-dimensional map of the current work area; Based on the three-dimensional map, an adaptive negative pressure sealing mechanism is controlled to form a partially sealed dust collection chamber between the robot and the vehicle bottom. Start the dust collection fan to collect dust under negative pressure, monitor the dust level in the local sealed dust collection chamber in real time, and adjust the airflow direction and operating power of the dust collection fan. The inhaled dust-laden airflow undergoes multi-stage filtration until dust collection is completed in all work areas.

2. The multi-robot collaborative adaptive negative pressure undercarriage dust collection method according to claim 1, characterized in that, Before the robot scans the undercarriage contour of the current work area and constructs a 3D map of the current work area, the following steps are included: The robot receives dust collection instructions from the central dispatch system and completes its self-check. The robot's self-test includes the chassis drive, dust collection fan, sensor module, adaptive negative pressure sealing mechanism, and communication module.

3. The adaptive negative pressure undercarriage dust collection method with multi-robot collaboration according to claim 1, characterized in that, The robot scans the undercarriage contour of the current work area to construct a 3D map of the current work area, including: The robots use onboard 3D LiDAR or depth vision sensors to scan the vehicle's undercarriage outline within their respective areas of responsibility to obtain outline data. The contour data is compared and fitted with a pre-stored rut model to construct a three-dimensional map of the current work area and identify the spatial locations of key components, including bogies and pipelines.

4. The adaptive negative pressure undercarriage dust collection method with multi-robot collaboration according to claim 1, characterized in that, Based on the aforementioned 3D map, an adaptive negative pressure sealing mechanism is controlled to form a partially sealed dust collection chamber between the robot and the vehicle floor, including: Based on the three-dimensional map, the adaptive negative pressure sealing mechanism is driven to extend the retractable flexible skirt and adaptively fit the vehicle bottom surface, forming a partially sealed dust collection chamber between the robot and the vehicle bottom.

5. The multi-robot collaborative adaptive negative pressure undercarriage dust collection method according to claim 1, characterized in that, Real-time monitoring of dust levels within the locally sealed dust collection chamber, including: The dust concentration in the locally sealed dust collection chamber is monitored using a dust concentration sensor; After dust is captured by the distributed sensing mechanism, the spatial distribution and accumulation of dust in the locally sealed dust collection chamber are used to generate a dust distribution heat map.

6. The multi-robot collaborative adaptive negative pressure undercarriage dust collection method according to claim 5, characterized in that, Adjusting the airflow direction and operating power of the dust collection fan includes: Based on the dust distribution heat map, adjust the orientation and angle of the dust collection grille of the dust collection fan; Based on the dust concentration in the locally sealed dust collection chamber, the operating power of the dust collection fan is adaptively adjusted by the frequency converter.

7. The multi-robot collaborative adaptive negative pressure undercarriage dust collection method according to claim 1, characterized in that, The intake of dust-laden airflow undergoes multi-stage filtration, including: Dust-laden airflow enters the primary settling chamber, where large particles are separated from the airflow and fall into the dust collection hopper; The subsequent airflow penetrates the secondary filtration mechanism, where fine dust particles are trapped on the surface of the filter media, and clean air is discharged.

8. The multi-robot collaborative adaptive negative pressure undercarriage dust collection method according to claim 5, characterized in that, If the dust concentration in the local sealed dust collection chamber is lower than the preset completion threshold for a continuous period of time, the dust collection operation in the current work area is determined to be completed. The central dispatch system determines the task list based on the overall task list. If the dust collection work in all work areas has been completed, the robot will perform automatic dust removal. Otherwise, the system will control the robot to move to the next work area to perform the dust collection work.

9. A multi-robot collaborative adaptive negative pressure undercarriage dust collection robot, used to implement the multi-robot collaborative adaptive negative pressure undercarriage dust collection method according to any one of claims 1-8, characterized in that, include: Chassis drive is used to control the robot's movement between different work areas; Dust collection fan, used to perform dust collection operations; The sensor module is used to scan the outline of the vehicle's underside and monitor dust concentration; An adaptive negative pressure sealing mechanism is used to create a locally sealed dust collection chamber between the robot and the vehicle floor; A communication module is used for the robot to interact with the central scheduling system.

10. The multi-robot collaborative adaptive negative pressure undercarriage dust collection robot according to claim 9, characterized in that, The sensor module includes: 3D LiDAR or depth vision sensor is used to scan the vehicle underside contour of the current work area and construct a three-dimensional map of the current work area; A dust concentration sensor is used to monitor the dust concentration within the locally sealed dust collection chamber.

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