A control method and system for an omnidirectional mobile cleaning robot in a confined space

Abstract

The application provides a control method and system of an omnidirectional mobile cleaning robot in a confined space, and relates to the field of cleaning robot control. The control method comprises: acquiring dust concentration information, obstacle perception information, robot state information and horizontal driving device pose information; performing data processing on the obstacle perception information to obtain obstacle grid map information; performing kinematic solution on the robot state information and horizontal driving device pose information to obtain running boundary information; matching the dust concentration information through a cleaning operation model to obtain cleaning operation parameter information; and performing modal fusion on the obstacle grid map information, running boundary information and cleaning operation parameter information to obtain fusion decision information. The control method realizes dynamic planning of a cleaning path, and is suitable for uneven dust cleaning operation requirements in a confined space.

Description

Technical Field

[0001] This invention relates to the field of cleaning robot control, and more specifically, to a control method and system for an omnidirectional mobile cleaning robot in confined spaces, particularly suitable for dust cleaning operations in confined spaces such as the bottom of conveyor belts. Background Technology

[0002] In industrial production, warehousing, and logistics scenarios, there are numerous narrow, confined spaces divided by equipment, walls, and columns. These spaces suffer from significant dust and material accumulation problems. Manual cleaning is not only inefficient but also poses safety risks such as dust inhalation and injuries from collisions. Existing automated cleaning robots are mostly designed for open spaces, exhibiting two significant shortcomings in confined environments: Firstly, most robot perception solutions fail to accurately integrate obstacle information, equipment position information, and actual cleaning requirements, making it difficult to plan a reasonable cleaning path within narrow boundaries, easily leading to missed areas, jamming, or collisions with obstacles. Secondly, existing cleaning control solutions cannot adjust cleaning parameters based on the actual dust distribution within the space. This results in either over-operation leading to energy waste or insufficient cleaning power failing to meet cleaning requirements, failing to adapt to the uneven dust distribution in confined spaces. Consequently, both cleaning effectiveness and operational efficiency fall short of expectations. Therefore, there is an urgent need for an omnidirectional mobile cleaning robot control method adapted to confined space operations. Summary of the Invention

[0003] The purpose of this invention is to provide a control method and system for an omnidirectional mobile cleaning robot in confined spaces, which solves the problems of unreasonable path planning, missed cleaning, jamming or collision with obstacles that existing automatic cleaning robots easily cause when operating in narrow and confined spaces; on the other hand, it can adapt to the operation requirements of uneven dust distribution in confined spaces.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, this application provides a control method for an omnidirectional mobile cleaning robot in a confined space, the method comprising: The system acquires dust concentration information, obstacle perception information, robot status information, and horizontal drive device pose information. The horizontal drive device pose information is information collected by pose sensors installed on the horizontal drive device. The horizontal drive device is installed on a base and the base is fixedly connected to the vehicle body. The horizontal drive device drives the tracked sweeping mechanism to perform horizontal extension operations. The obstacle perception information is processed to obtain obstacle grid map information; Kinematic calculations are performed on the robot's state information and the pose information of the horizontal drive device to obtain the running boundary information; The dust concentration information is matched with the cleaning operation model to obtain cleaning operation parameter information; Modal fusion is performed on the obstacle grid map information, running boundary information and cleaning operation parameter information to obtain fused decision information. The fused decision information is used to generate the target cleaning path and motion adjustment instructions for the omnidirectional mobile cleaning robot.

[0005] Secondly, this application also provides a control system for an omnidirectional mobile cleaning robot in a confined space. The information acquisition module is used to acquire dust concentration information, obstacle perception information, robot status information and horizontal drive device pose information. The horizontal drive device pose information is the information collected by the pose sensor installed on the horizontal drive device. The horizontal drive device is installed on the base and the base is fixedly connected to the vehicle body. The horizontal drive device drives the tracked sweeping mechanism to perform horizontal extension operations. The data processing module is used to process the obstacle perception information to obtain obstacle grid map information; The motion calculation module is used to perform kinematic calculations on the robot's state information and the pose information of the horizontal drive device to obtain the running boundary information; The cleaning matching module is used to match the dust concentration information with the cleaning operation model to obtain cleaning operation parameter information; The information fusion module is used to perform modal fusion of the obstacle grid map information, running boundary information and cleaning operation parameter information to obtain fusion decision information. The fusion decision information is used to generate the target cleaning path and motion adjustment instructions for the omnidirectional mobile cleaning robot.

[0006] Thirdly, this application also provides a control device for an omnidirectional mobile cleaning robot in a confined space, comprising: Memory, used to store computer programs; A processor is used to implement the steps of the control method for the omnidirectional mobile cleaning robot in a confined space when executing the computer program.

[0007] Fourthly, this application also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described control method for an omnidirectional mobile cleaning robot in a confined space.

[0008] The beneficial effects of this invention are as follows: This invention combines multi-sensor information acquisition and modal fusion with spatial constraints, dust distribution, and robot motion boundaries to achieve dynamic planning of the cleaning path. This effectively avoids the robot getting stuck and colliding in narrow spaces. At the same time, it automatically adjusts the cleaning power and operating speed for areas with higher dust concentrations, reducing missed areas and improving the overall efficiency of the cleaning operation. It is suitable for cleaning operations with uneven dust in confined spaces.

[0009] Furthermore, the present invention employs a controlled omnidirectional movement structure and a horizontally extendable tracked cleaning mechanism, which can reach corners and edges that conventional cleaning devices cannot reach, further expanding the coverage of cleaning operations and improving the adaptability and automation of cleaning operations in confined spaces.

[0010] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the control method for an omnidirectional mobile cleaning robot in a confined space as described in an embodiment of the present invention; Figure 2 This is a schematic diagram of the overall structure of this omnidirectional mobile cleaning robot; Figure 3 This is a schematic diagram of a vibration damping structure; Figure 4 This is a rear view of the omnidirectional mobile cleaning robot. Figure 5 This is a top view of the omnidirectional mobile cleaning robot; Figure 6 This is a side view of the omnidirectional mobile cleaning robot; Figure 7 This is a schematic diagram of the operation of this omnidirectional mobile cleaning robot; Figure 8 This is a schematic diagram of the control device for an omnidirectional mobile cleaning robot in a confined space, as described in an embodiment of the present invention.

[0013] Marked in the image: 1. Vehicle body; 2. Mecanum wheel set; 20. Drive motor; 21. Mounting bracket; 22. Shock-absorbing spring; 23. Slide table; 30. Base; 31. Tracked sweeping mechanism; 32. Sweeping disc; 33. Connecting arm assembly; 34. Dust collection box; 4. Control system; 51. Spray system; 52. Dust sensor; 53. Water tank; 6. Electric push rod; 7. Built-in power supply; 331. Primary connecting arm; 332. Secondary connecting arm; 333. Drive rod; 800. Control device for omnidirectional mobile sweeping robot in confined space; 801. Processor; 802. Memory; 803. Multimedia component; 804. I / O interface; 805. Communication component. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0015] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0016] Example 1: This embodiment provides a control method for an omnidirectional mobile cleaning robot in a confined space. (See also...) Figure 1 The figure shows that this method includes: Step S1: Obtain dust concentration information, obstacle perception information, robot status information and horizontal drive device pose information. The horizontal drive device pose information is the information collected by the pose sensor installed on the horizontal drive device. The horizontal drive device is installed on the base 30 and the base 30 is fixedly connected to the vehicle body 1. The horizontal drive device drives the tracked sweeping mechanism 31 to perform horizontal extension operation. In addition, the dust concentration information and obstacle perception information are collected by the dust concentration sensor and obstacle detection sensor on the top of the omnidirectional mobile cleaning robot body 1, respectively, and the robot status information is collected by the IMU sensor on the bottom of the body 1.

[0017] In this omnidirectional mobile cleaning robot, considering the narrow bottom space in confined spaces, the sensors are functionally divided into an upper sensing layer and a lower sensing layer to ensure omnidirectional perception of the narrow bottom space. Specifically: the upper sensing layer consists of obstacle detection sensors and dust concentration sensors; the obstacle detection sensors include LiDAR and an infrared camera; the lower sensing layer includes an IMU sensor and a pose sensor.

[0018] In terms of data synchronization, PTP (Precision Time Protocol) based on the IEEE 1588 protocol is used as the synchronization architecture. High-precision GNSS / IMU integrated navigation is used as the master clock. Synchronization messages are distributed to all sensors through industrial Ethernet switches. Among them, dust sensor data is acquired by GPIO hard triggering, and the response delay is controlled within 10μs.

[0019] Regarding the sensor's location: the dust concentration sensor is a laser scattering dust sensor, installed on the top of the vehicle body 1, preferably located at the tracked sweeping mechanism 31 and the sweeping disc 32, for real-time monitoring of environmental dust concentration; the sensor has an accuracy of ±0.5% and a response time of less than 500ms, and can adapt to dynamic environmental monitoring in narrow spaces.

[0020] The obstacle detection sensor combines LiDAR and infrared cameras to achieve 360° obstacle detection. The LiDAR is installed on the top of the vehicle body 1, with a scanning range of 0.1-10m. The infrared cameras are installed on both sides of the vehicle body 1 to supplement obstacle perception information in low-lying areas.

[0021] The IMU sensor is installed at the bottom of the vehicle body 1 to monitor the pose, movement speed and other status information of the omnidirectional mobile cleaning robot in real time. The IMU sensor integrates an encoder, gyroscope, accelerometer and other components to collect data, as well as the angle, linear velocity and angular velocity of the omnidirectional mobile structure. The omnidirectional mobile structure can be set as a Mecanum wheel set.

[0022] The posture sensor is used to monitor the posture information of the tracked sweeping mechanism 31 during horizontal extension operations, with an accuracy of ±1mm. The horizontal drive device can be a telescopic cylinder, a lead screw, or a connecting structure.

[0023] Step S2: Process the obstacle perception information to obtain obstacle grid map information; To clarify the specific process of data processing in step S2, step S2 includes S21-S23, specifically: S21: Preprocess the obstacle perception information to obtain obstacle perception preprocessed information; In step S21, the robot's current working space is divided into grids based on a preset grid resolution. The occupancy probability of obstacles within the grid is marked by combining obstacle perception information. After filtering out noise interference data, obstacle perception preprocessing information is obtained.

[0024] S21: Input the obstacle perception preprocessing information into the segmentation model to obtain pixel segmentation information, which includes the obstacle category and confidence level of each pixel; The segmentation model can employ a pre-trained deep learning segmentation network, specifically a fully convolutional network (FCN), SegNet, DeepLab series, or a lightweight YOLOv8 segmentation module. The obstacle categories include static and dynamic obstacles. Taking the confined space of a conveyor belt as an example, static obstacles include conveyor belt supports, rollers, and fixed equipment debris; dynamic obstacles include workers and mobile equipment.

[0025] S23: Map the pixel segmentation information to a preset grid space, and update the obstacle occupancy probability of each grid using Bayesian algorithm to obtain obstacle grid map information.

[0026] Specifically, this step involves: first, transforming the pixel segmentation information from the image coordinate system to the grid map coordinate system where the robot is located; then, determining the initial value of the obstacle occupancy probability in the corresponding grid based on the obstacle category and confidence level corresponding to each pixel in the pixel segmentation information; subsequently, updating and integrating the historical occupancy probabilities of each grid based on Bayesian methods to obtain obstacle grid map information that includes the probability distribution of static obstacle updates and dynamic obstacle updates.

[0027] Step S3: Perform kinematic calculations on the robot state information and the pose information of the horizontal drive device to obtain the running boundary information; To clarify the specific process of data processing in step S3, step S3 includes S31-S32, specifically: S31: The robot state information and the pose information of the horizontal drive device are calculated through a preset motion model to obtain an achievable motion range information set. The achievable motion range information set includes the achievable motion range information of the robot body in the grid map coordinate system and the achievable motion range of the horizontal drive device in the grid map coordinate system. In this step, the preset motion model includes a robot body movement model and a relative motion model of the horizontal drive device, wherein: The robot's movement model is as follows: ; ① In equation ① above, Represents the global Directional velocity component, Represents the global Directional velocity component, Indicates the rate of change of heading angle. This indicates the linear velocity of the robot body (along the heading direction). Indicates the angular velocity of the robot body. This represents the heading angle (yaw angle) of the robot body. The relative motion model of the horizontal drive device is as follows: ;② In equation ② above, , This indicates the position of the horizontal drive unit in the grid map coordinate system. , Indicates the zero point position of the horizontal drive unit. express The amount of expansion or contraction at any given time (displacement from zero).

[0028] Range analysis is performed on multiple preset discrete time steps in the grid map coordinate system to obtain a set of achievable motion range information. This set includes the achievable motion range of the robot body in the grid map coordinate system and the achievable motion range of the horizontal drive device in the same coordinate system. Taking a belt conveyor as an example, obstacles such as idlers, crossbeams, and material discharge ports at the bottom of the conveyor need to be considered. During range analysis, these areas in the grid map are marked as impassable.

[0029] Furthermore, the speed and turning ability in the relative motion model of the robot body and the horizontal drive device are limited by factors such as ground friction and dust adhesion. The model parameters can be corrected by reducing the maximum speed and angular velocity.

[0030] S32: The reachable motion range information set is constrained by a preset safety redundancy model to obtain the operation boundary information.

[0031] In step S32, the preset security redundancy model is: ;③ In equation ③ above, This represents the output data after safety redundancy. This represents the set of information about the reachable range of motion. This represents a set of safety redundancy parameters, which includes preset mechanical redundancy reduction, obstacle avoidance buffer distance, dynamic redundancy coefficient (used to limit speed boundaries), and distance measurement error compensation redundancy in dusty environments.

[0032] Boundary constraints include the robot body's operating boundary and the horizontal drive device's operating boundary. Specifically, the robot body's operating boundary considers areas that the robot body cannot enter at the bottom of the confined space (such as areas where the gap at the bottom of the conveyor belt is too small), which can be accessed through pre-defined prohibited areas in the grid map. The horizontal drive device's operating boundary considers the safe distance or preset gap between the tracked cleaning mechanism 31 and the base at the bottom of the confined space.

[0033] Step S4: Match the dust concentration information with the cleaning operation model to obtain cleaning operation parameter information; Step S4 includes: S41: Input the dust concentration information into the preset label level model, and match the corresponding environmental risk labels according to the three pre-divided concentration ranges of low risk, medium risk and high risk. S42: Associate the matched environmental risk labels with the preset cleaning strategy mapping table to obtain cleaning operation parameter information that matches the risk level.

[0034] The cleaning strategy mapping table sets three types of operating parameters corresponding to different concentration levels: track speed, cleaning disc suction power, and spray water volume. The low-risk level corresponds to the normal track speed, basic cleaning disc suction power, and basic spray water volume; the medium-risk level corresponds to reducing the track speed and increasing the cleaning disc suction power and spray water volume to the medium level; the high-risk level corresponds to further reducing the track speed and increasing it to the highest level of cleaning disc suction power and spray water volume, thereby matching the cleaning needs under different dust concentrations and balancing cleaning effect and operating energy consumption.

[0035] S5: Modal fusion is performed on the obstacle grid map information, running boundary information, and cleaning operation parameter information to obtain fused decision information; wherein, step S5 includes: S51: Perform feature transformation on the obstacle grid map information, running boundary information, and cleaning operation parameter information to obtain a transformed feature dataset; wherein: S511: Convert the obstacle grid map information into probabilistic occupancy grid features; The conversion process in this step is as follows: normalize the grid occupancy probability value in the obstacle grid map information to the range of [0,1], where 0 represents a completely unobstructed free area and 1 represents a completely obstructed area. The conversion of the probabilistic occupancy grid feature is completed in sequence.

[0036] S512: Map the running boundary information into path constraint features; Specifically, using the actual coordinate system of the cleaning robot as a reference, the coordinate information of the operating boundary is converted into binary constraint features of the feasible and prohibited areas, marking the range in which the cleaning robot can operate safely, and providing a constraint basis for path planning in the fusion decision information.

[0037] S513: Convert cleaning operation parameter information into cleaning weight features; In this step, the cleaning operation parameter information includes parameters such as cleaning area priority, cleaning repetition number, and cleaning method requirements. Based on the degree of influence of each parameter on the cleaning path planning, they are converted into cleaning weight values ​​for the corresponding grid positions. The higher the weight, the higher the cleaning demand level of the area, which can guide the robot to prioritize matching the cleaning operation demand when planning the path.

[0038] S514: Construct a transformation feature dataset based on the probabilistic occupancy grid features, path constraint features, and sweep weight features.

[0039] S52: The transformed feature dataset is processed by feature splicing and weighting through a preset fusion network model to obtain fusion decision information, which includes priority scores and passability probabilities for different cleaning areas.

[0040] Step S52 specifically includes: S521: Input the probabilistic grid occupancy features, path constraint features, and sweep weight features into the corresponding input channels of the fusion network model, and align the three features in dimensions to ensure that the spatial positions of different features correspond in the same grid coordinate system. S522: The three types of features are spliced ​​and fused by the convolutional module of the fusion network, and adaptive weights are assigned to different features by combining the attention mechanism: For areas with a high proportion of obstacles, the weight of the probabilistic occupancy grid feature is increased, and the influence of the cleaning weight feature is reduced; For priority cleaning areas marked as passable, the weight of the cleaning weight feature is increased to ensure that the operation needs are prioritized. S523: Normalize the fused feature output and finally output the cleaning priority score and passability probability of each grid cell to form fused decision information.

[0041] Following step S5, step S6 is also included: outputting a cleaning action command after obtaining the fused decision information, including: S61: Calculate the priority score and passability probability of different cleaning areas to obtain the comprehensive weight of each passable grid in the grid map and generate the target cleaning path; In this step, the cleaning priority score and passability probability of each grid are multiplied to obtain the comprehensive path planning weight of the corresponding grid. Then, the comprehensive weight is combined to search for the optimal path from the current robot position to the highest priority uncleaned area. During the path search process, grids with passability probability lower than a preset threshold are eliminated to prevent the robot from entering uncertain areas. Finally, a complete target cleaning path is generated.

[0042] S62: Based on the target cleaning path, generate corresponding motion adjustment commands. The motion adjustment commands may include displacement commands for the horizontal drive device, track speed control commands for the tracked cleaning mechanism 31, and speed commands for the omnidirectional moving structure. This step includes: Based on the real-time coordinates of the path nodes of the target cleaning path, the deviation between the robot's current pose and the target node pose is calculated. The drive quantity of the horizontal drive device is adjusted based on the PID algorithm to determine the speed of the omnidirectional moving structure, ensuring that the robot travels along the preset path. At the same time, based on the detection results of the degree of dirt in the area where the path node is located, the track rotation speed of the tracked cleaning mechanism is adjusted. For areas with high degree of dirt, the travel speed is reduced and the track cleaning speed is increased, while for areas with low degree of dirt, the normal cleaning speed is maintained, thus completing the matching control of the corresponding cleaning action.

[0043] Example 2: like Figures 2 to 7 As shown, an omnidirectional mobile cleaning robot for the bottom of a belt conveyor includes: The vehicle body 1 has omnidirectional moving structures on both sides and a cleaning device on the front side. The cleaning device includes a base 30, a tracked cleaning mechanism 31, a cleaning disc 32, a connecting arm assembly 33, and a dust collection box 34. The base 30 is fixedly connected to the vehicle body 1. Horizontal drive devices are provided on both sides of the base 30, and the transmission end of the horizontal drive device is connected to the tracked cleaning mechanism 31. The surface of the tracked cleaning mechanism 31 is provided with cleaning brushes. The cleaning disc 32 is rotatably connected to the base 30 through the connecting arm assembly 33. A one-way dust inlet pipe is provided inside the connecting arm assembly 33. One end of the dust inlet pipe is connected to the cleaning disc 32, and the other end of the dust inlet pipe is connected to the dust collection box 34. The dust collection box 34 is located on the top of the base 30. The vehicle body 1 is equipped with a control system 4, which is electrically connected to the omnidirectional moving structure and the horizontal drive device.

[0044] like Figure 7As shown, the working process of this omnidirectional mobile cleaning robot is as follows: After the cleaning robot moves to the bottom area of ​​the conveyor belt, it adjusts the position of the vehicle body 1 through the omnidirectional moving structure. The horizontal drive device drives the tracked cleaning mechanisms 31 on both sides to extend outward, so that the cleaning brushes on the tracked cleaning mechanisms 31 are in contact with the side walls and corner areas of the bottom of the conveyor belt. The rotation of the tracks drives the cleaning brushes to perform cleaning work. At the same time, the connecting arm assembly 33 drives the cleaning disc 32 to rotate, cleaning the flat area at the bottom of the conveyor belt. Dust is directly sucked into the dust collection box 34 along the dust inlet pipe for collection. Among them: Compared to traditional cylindrical brushes, the tracked sweeping mechanism 31 increases the contact area with the ground, effectively improving the sweeping area and significantly enhancing the efficiency of coal ash and debris collection and the cleanliness of the sweeping. The sweeping disc 32, driven by the connecting arm assembly 33, adjusts its height and angle accordingly, enabling precise cleaning of blind spots that are difficult to reach by conventional sweeping paths, such as the base of the support and the area under the roller.

[0045] The dust collection box 34 can integrate multiple dust collection chambers to temporarily store the coal ash collected during cleaning, enabling dust collection while cleaning and preventing secondary scattering of coal ash.

[0046] In this system, the omnidirectional moving structure can be set as Mecanum wheel sets 2. The Mecanum wheel sets 2 are respectively installed at the four opposite corners of the bottom of the vehicle body 1, and each Mecanum wheel is controlled to rotate by an independently set drive motor 20. Each drive motor 20 is electrically connected to the control system 4.

[0047] In addition, the omnidirectional movement structure can also be a steering wheel structure. The steering wheel structures are respectively set at the diagonal positions at the bottom of the vehicle body 1. Each steering wheel is equipped with an independent drive and steering unit. Each drive and steering unit is connected to the control system 4 to realize the omnidirectional movement of the vehicle body.

[0048] The introduction of an omnidirectional moving structure can solve the problem of the difficulty of turning around the cleaning robot. During operation, the control system 4 controls the independent motors in the omnidirectional moving structure to achieve multiple movement modes such as forward, backward, lateral translation, 360° turning in place, and diagonal driving. The flexible movement is suitable for narrow spaces with limited bottom height of the conveyor belt and dense surrounding support blocks. It can achieve full-area automated cleaning of the bottom of the conveyor belt without manual adjustment of the equipment position, greatly reducing manual intervention and avoiding manual entry into dangerous areas.

[0049] like Figure 3As shown, to absorb the vibrations generated during the movement of the cleaning robot and ensure the stability of the vehicle body, a shock-absorbing device is installed in each Mecanum wheel. The shock-absorbing device includes a mounting frame 21, a shock-absorbing spring 22, and a slide 23. The mounting frame 21 is used to fix it to the vehicle body 1. A connecting rod is provided inside the mounting frame 21. The shock-absorbing spring 22 and the slide 23 are slidably connected to the connecting rod. The two ends of the shock-absorbing spring 22 abut against the inner wall of the mounting frame 21 and the side wall of the slide 23, respectively. The drive motor 20 is fixedly connected to the slide 23, and the output end of the drive motor 20 is connected to the input shaft of the Mecanum wheel. The working process of the shock absorption device is as follows: When the Mecanum wheel travels over an uneven road surface, the Mecanum wheel and the slide 23 slide along the connecting rod towards the inside of the mounting bracket 21. At this time, the shock absorption spring 22 is compressed and contracted by the slide 23, absorbing most of the impact energy and preventing the impact force from causing the vehicle body 1 to vibrate and shake. When the road surface returns to a smooth surface, the compressed shock absorption spring 22 releases its elasticity, pushing the slide 23 to reset along the connecting rod, causing the Mecanum wheel to return to its initial position and maintaining the stability of the vehicle body during travel.

[0050] like Figure 5 and Figure 6 As shown, this cleaning robot also includes a dust suppression device to achieve intelligent dust suppression. The dust suppression device includes a spray system 51, a dust sensor 52, and a water tank 53, wherein: The dust sensor 52 is mounted on the base 30, the water tank 53 is fixedly mounted on the vehicle body 1, the water inlet of the spray system 51 is connected to the water tank 53, the water outlet of the spray system 51 is set to correspond to the cleaning device, and the spray system 51, the dust sensor 52 and the control system 4 are electrically connected.

[0051] The working principle of the dust suppression device is as follows: The control system 4 has multiple dust concentration thresholds and matching speed settings for the tracked sweeping mechanism 31. The dust sensor 52 collects real-time dust concentration data from the environment at the bottom of the conveyor belt and transmits the data to the control system 4. Based on the real-time data from the dust sensor 52, the control system 4 automatically adjusts the speed of the tracked sweeping mechanism 31 and controls the start and stop of the spray system 51. Regarding the multiple dust concentration thresholds, when the detected dust concentration is higher than the preset threshold, the spray system 51 starts and simultaneously controls the tracked sweeping mechanism 31 to reduce speed, achieving coordinated operation of dust suppression and speed adjustment to prevent dust from accumulating in the enclosed space. When the dust concentration is lower than the preset threshold, the spray system 51 stops spraying and controls the tracked sweeping mechanism 31 to increase speed, improving cleaning efficiency.

[0052] This system employs a cleaning strategy driven by dual data of "dust concentration + accumulation amount," employing slow, low-speed sweeping to control dust in high-dust / grey areas and high-speed, fast sweeping to improve efficiency in low-dust / grey areas, thus balancing cleaning cleanliness, dust control, and operational efficiency.

[0053] In the above structure, the spray system 51 can use low-pressure fine atomizing nozzles, which have good atomization effect and wide dust suppression range. They are distributed in front of the sweeping device to effectively suppress the dust generated during the sweeping process and will not cause the ground to become too wet, thus affecting the operation of the equipment.

[0054] The water tank 53 is made of lightweight materials. While ensuring that the water consumption meets the dust suppression requirements, the volume of the water tank is minimized and the weight of the equipment is reduced, making it more suitable for passage in narrow spaces with limited bottom height of the belt conveyor, while extending the equipment's operating time.

[0055] To clarify the specific structure of the horizontal drive device, it is described as a telescopic cylinder. The cylinder body is fixed to the base 30, and the transmission end of the telescopic cylinder is connected to the tracked cleaning mechanism 31. The telescopic stroke of the cylinder can be flexibly adjusted according to the gap and width of the conveyor belt support. The maximum telescopic stroke must meet the cleaning requirements of the conventional conveyor belt support gap, facilitating deep cleaning into the gaps and bottom crevices of the support.

[0056] like Figure 4 As shown, the connecting arm assembly 33 in this system includes a primary connecting arm 331, a secondary connecting arm 332, and a transmission rod 333. A servo motor for driving rotation is provided between each level of the connecting arm. The servo motor is electrically connected to the control system 4. One end of the primary connecting arm 331 is rotatably connected to the base 30, and the other end is rotatably connected to the secondary connecting arm 332. The end of the secondary connecting arm 332 away from the primary connecting arm 331 is rotatably connected to the cleaning disc 32. One end of the transmission rod 333 is rotatably connected to the base 30, and the other end of the transmission rod 333 is rotatably connected to the secondary connecting arm 332. Through the coordinated rotation of each stage of the servo motor, the connecting arm assembly 33 can drive the cleaning disc 32 to adjust its angle and position within a preset range, avoiding blind spots and ensuring overall cleaning effectiveness.

[0057] To facilitate the unloading of dust from the dust collection box 34, the cleaning robot also includes an electric push rod 6. One end of the electric push rod 6 is rotatably connected to the base 30, and the other end is rotatably connected to the dust collection box 34 via a hinge shaft. The body of the dust collection box 34 is rotatably connected to the top of the base 30. The electric push rod 6 is electrically connected to the control system 4. When it is necessary to unload dust from the dust collection box 34, the electric push rod 6 extends, pushing the dust collection box 34 outward around its rotatable connection point with the base 30, so that the opening of the dust collection box 34 faces downward, allowing the accumulated dust to be unloaded. After unloading, the electric push rod 6 retracts, pulling the dust collection box 34 back to its original position.

[0058] To prevent dust from spreading upwards and outwards, the dust collection box 34 is equipped with a dust collection sealing cover. A capacity detection sensor is installed on the wall of the dust collection box 34. The capacity detection sensor is electrically connected to the control system 4. When the dust collected by the dust collection box 34 accumulates to a set capacity, the capacity detection sensor sends a dust discharge signal, and the control system 4 controls the electric push rod 6 to perform the dust discharge action.

[0059] This cleaning robot also includes a built-in power supply 7, which is mounted on the vehicle body 1 and electrically connected to the control system 4. The built-in power supply 7 powers the entire cleaning robot. When the robot completes its cleaning task or detects that the remaining power of the built-in power supply 7 is below a set threshold, the control system 4 will control the omnidirectional movement structure to return the robot to the charging station to complete the charging operation, ensuring power supply for the next task. The built-in power supply 7 can use a high-capacity rechargeable lithium battery, integrating power monitoring, low-voltage alarm, overcharge protection, and fast charging functions to provide stable power for the entire robot's operation.

[0060] To facilitate path planning and automatically avoid obstacles such as conveyor belt supports and rollers, a lidar device and a visual navigation device are fixedly connected to the vehicle body 1. The lidar device and visual navigation device are electrically connected to the control system 4. The lidar device and visual navigation device collect environmental data of the bottom of the conveyor belt in real time and transmit it to the control system 4 for path planning, automatically avoiding obstacles at the bottom of the conveyor belt, ensuring smooth passage of the equipment in areas with dense supports at the bottom of the conveyor belt, and achieving full coverage without omissions.

[0061] Example 3: This embodiment provides a control system for an omnidirectional mobile cleaning robot in a confined space, the system comprising: The information acquisition module is used to acquire dust concentration information, obstacle perception information, robot status information and horizontal drive device pose information. The horizontal drive device pose information is the information collected by the pose sensor installed on the horizontal drive device. The horizontal drive device is installed on the base 30 and the base 30 is fixedly connected to the vehicle body 1. The horizontal drive device drives the tracked sweeping mechanism 31 to perform horizontal extension operations. The data processing module is used to process the obstacle perception information to obtain obstacle grid map information; The motion calculation module is used to perform kinematic calculations on the robot's state information and the pose information of the horizontal drive device to obtain the running boundary information; The cleaning matching module is used to match the dust concentration information with the cleaning operation model to obtain cleaning operation parameter information; The information fusion module is used to perform modal fusion of the obstacle grid map information, running boundary information and cleaning operation parameter information to obtain fusion decision information. The fusion decision information is used to generate the target cleaning path and motion adjustment instructions for the omnidirectional mobile cleaning robot.

[0062] It should be noted that the specific methods by which each module performs operations in the system described in the above embodiments have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0063] Example 4: Corresponding to the above method embodiments, this embodiment also provides a control device for an omnidirectional mobile cleaning robot in a confined space. The control device for an omnidirectional mobile cleaning robot in a confined space described below and the control method for an omnidirectional mobile cleaning robot in a confined space described above can be referred to in correspondence with each other.

[0064] Figure 8 This is a block diagram illustrating an omnidirectional mobile cleaning robot control device 800 in a confined space, according to an exemplary embodiment. Figure 8 As shown, the control device 800 may include a processor 801 and a memory 802. The control device 800 may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0065] The processor 801 controls the overall operation of the control device 800 to complete all or part of the steps in the aforementioned control method for an omnidirectional mobile cleaning robot in a confined space. The memory 802 stores various types of data to support the operation of the omnidirectional mobile cleaning robot control device 800 in the confined space. This data may include, for example, instructions for any application or method used to operate on the omnidirectional mobile cleaning robot control device 800 in the confined space, as well as application-related data such as contact data, sent and received messages, images, audio, and video. The memory 802 can be implemented using any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 802 or transmitted via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. I / O interface 804 provides an interface between processor 801 and other interface modules, such as keyboards, mice, and buttons. These buttons can be virtual or physical. Communication component 805 is used for wired or wireless communication between the omnidirectional mobile cleaning robot control device 800 and other devices in this confined space. Wireless communication includes, for example, Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination thereof. Therefore, the corresponding communication component 805 may include a Wi-Fi module, a Bluetooth module, and an NFC module.

[0066] In an exemplary embodiment, the omnidirectional mobile cleaning robot control device 800 in a confined space may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the aforementioned omnidirectional mobile cleaning robot control method in a confined space.

[0067] Example 5: Corresponding to the above method embodiments, this embodiment also provides a readable storage medium. The readable storage medium described below can be referred to in conjunction with the control method for an omnidirectional mobile cleaning robot in a confined space described above.

[0068] A readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the omnidirectional mobile cleaning robot control method in a confined space as described in the above method embodiments.

[0069] The readable storage medium can specifically be a USB flash drive, external hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, or any other readable storage medium capable of storing program code.

[0070] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0071] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A control method for an omnidirectional mobile cleaning robot in a confined space, characterized in that, include: The system acquires dust concentration information, obstacle perception information, robot status information and horizontal drive device pose information. The horizontal drive device pose information is the information collected by the pose sensor installed on the horizontal drive device. The horizontal drive device is installed on the base (30) and the base (30) is fixedly connected to the vehicle body (1). The horizontal drive device drives the tracked sweeping mechanism (31) to perform horizontal extension operations. The obstacle perception information is processed to obtain obstacle grid map information; Kinematic calculations are performed on the robot's state information and the pose information of the horizontal drive device to obtain the running boundary information; The dust concentration information is matched with the cleaning operation model to obtain cleaning operation parameter information; Modal fusion is performed on the obstacle grid map information, running boundary information and cleaning operation parameter information to obtain fused decision information. The fused decision information is used to generate the target cleaning path and motion adjustment instructions for the omnidirectional mobile cleaning robot.

2. The control method according to claim 1, characterized in that, Obstacle perception information is processed to obtain obstacle grid map information, including: The obstacle perception information is preprocessed to obtain obstacle perception preprocessed information; The obstacle perception preprocessing information is input into the segmentation model to obtain pixel segmentation information, which includes the obstacle category and confidence level of each pixel. The pixel segmentation information is mapped to a preset grid space, and the obstacle occupancy probability of each grid is updated using Bayesian methods to obtain obstacle grid map information.

3. The control method for an omnidirectional mobile cleaning robot in a confined space according to claim 1, characterized in that, Kinematic calculations are performed on the robot's state information and the pose information of the horizontal drive device to obtain the running boundary information, including: The robot's state information and the pose information of the horizontal drive device are solved by a preset motion model to obtain an achievable motion range information set. The achievable motion range information set includes the achievable motion range information of the robot body in the grid map coordinate system and the achievable motion range of the horizontal drive device in the grid map coordinate system. The operational boundary information is obtained by applying boundary constraints to the reachable motion range information set using a pre-defined safety redundancy model.

4. The control method for an omnidirectional mobile cleaning robot in a confined space according to claim 3, characterized in that, The preset motion model includes a robot body movement model and a relative motion model of the horizontal drive device, wherein: The robot's movement model is as follows: ；① In equation ① above, Represents the global Directional velocity component, Represents the global Directional velocity component, Indicates the rate of change of heading angle. This indicates the linear velocity of the robot body (along the heading direction). Indicates the angular velocity of the robot body. This represents the heading angle (yaw angle) of the robot body. The relative motion model of the horizontal drive device is as follows: ；② In equation ② above, , This indicates the position of the horizontal drive unit in the grid map coordinate system. , Indicates the zero point position of the horizontal drive unit. express The amount of expansion or contraction at any given time (displacement from zero).

5. The control method for an omnidirectional mobile cleaning robot in a confined space according to claim 3, characterized in that, The preset security redundancy model is as follows: ；③ In equation ③ above, This represents the output data after safety redundancy. This represents the set of information about the reachable range of motion. This represents a set of safety redundancy parameters, which includes preset mechanical redundancy reduction, obstacle avoidance buffer distance, dynamic redundancy coefficient (used to limit speed boundaries), and distance measurement error compensation redundancy in dusty environments.

6. The control method for an omnidirectional mobile cleaning robot in a confined space according to claim 1, characterized in that, The dust concentration information is matched with the cleaning operation model to obtain cleaning operation parameter information, including: The dust concentration information is input into a preset label level model, and environmental risk labels of the corresponding levels are obtained according to the three pre-divided concentration ranges of low risk, medium risk and high risk. The matched environmental risk labels are associated with a preset cleaning strategy mapping table to obtain cleaning operation parameter information that matches the risk level.

7. The control method for an omnidirectional mobile cleaning robot in a confined space according to claim 1, characterized in that, Modal fusion is performed on the obstacle grid map information, operation boundary information, and cleaning operation parameter information to obtain fused decision information, including: The obstacle grid map information, running boundary information, and cleaning operation parameter information are subjected to feature transformation to obtain a transformed feature dataset; The transformed feature dataset is processed by feature splicing and weighting through a preset fusion network model to obtain fusion decision information, which includes priority scores and passability probabilities for different cleaning areas.

8. The control method for an omnidirectional mobile cleaning robot in a confined space according to claim 7, characterized in that, The obstacle grid map information, running boundary information, and cleaning operation parameter information are subjected to feature transformation to obtain a transformed feature dataset, including: The obstacle grid map information is converted into probabilistic occupancy grid features; The operational boundary information is mapped to path constraint features; Convert cleaning operation parameter information into cleaning weight features; A transformation feature dataset is constructed based on the probabilistic occupancy grid features, path constraint features, and sweep weight features.

9. A control method for an omnidirectional mobile cleaning robot in a confined space according to claim 7, characterized in that, After obtaining the fusion decision information, the cleaning action command is output, including: Priority scores and passability probabilities for different cleaning areas are calculated to obtain the comprehensive weight of each passable grid cell in the grid map and generate the target cleaning path. Based on the target cleaning path, a corresponding motion adjustment command is generated.

10. A control system for an omnidirectional mobile cleaning robot in a confined space, characterized in that, include: The information acquisition module is used to acquire dust concentration information, obstacle perception information, robot status information and horizontal drive device pose information. The horizontal drive device pose information is the information collected by the pose sensor set on the horizontal drive device. The horizontal drive device is set on the base (30) and the base (30) is fixedly connected to the vehicle body (1). The horizontal drive device drives the tracked sweeping mechanism (31) to perform horizontal extension operation. The data processing module is used to process the obstacle perception information to obtain obstacle grid map information; The motion calculation module is used to perform kinematic calculations on the robot's state information and the pose information of the horizontal drive device to obtain the running boundary information; The cleaning matching module is used to match the dust concentration information with the cleaning operation model to obtain cleaning operation parameter information; The information fusion module is used to perform modal fusion of the obstacle grid map information, running boundary information and cleaning operation parameter information to obtain fusion decision information. The fusion decision information is used to generate the target cleaning path and motion adjustment instructions for the omnidirectional mobile cleaning robot.

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