Cleaning robot narrow area identifying, cleaning and exiting method

Abstract

The invention discloses a cleaning robot narrow area identification, cleaning and exiting method, which comprises the steps of S1, acquiring boundary point cloud data, fitting lengths of two sides of a boundary through the point cloud data, calculating linear widths of the two sides of the boundary, calculating whether the linear widths of the two sides of the boundary are smaller than a set threshold value or not, and judging whether a robot enters a narrow area or not; s2, acquiring the type of a narrow area, and recording pose data of the robot; s3, selecting a proper wall-following cleaning strategy according to the type of the narrow area; s4, whether the width of the front narrow area is smaller than a preset safety threshold value or not is detected, sweeping stopping operation is executed, and a sweeping returning mechanism is started; and S5, after successfully exiting the narrow area, marking and storing the information of the narrow area encountered and processed in the cleaning process. According to the invention, the cleaning efficiency and coverage rate of the robot in a narrow area are improved, the recognition capability of the robot to a complex environment is enhanced, and the phenomenon of work interruption caused by jamming or collision is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of sweeping robots, and in particular to a method for a cleaning robot to identify, clean and exit a narrow area. Background Art

[0002] With the growing demand for automated cleaning in homes and commercial environments, cleaning robots are increasingly being used. However, when performing cleaning tasks, cleaning robots often encounter narrow areas, such as small gaps between furniture or corners of rooms with complex layouts. These areas are not only difficult to enter but can also easily cause the robot to be trapped. Therefore, it is particularly important to develop a cleaning robot technology solution that can effectively identify, clean, and safely exit narrow areas. The present invention is proposed based on this practical demand.

[0003] Traditional cleaning robots usually adopt a fixed-mode cleaning strategy when dealing with narrow areas, that is, they clean according to a preset path or random walking. Although this approach is simple and easy to implement, its disadvantages are also obvious: on the one hand, due to the lack of dynamic perception of the environment, the robot cannot accurately judge whether the front is a passable narrow area, which may cause collision or jam; on the other hand, once entering a narrow area, the robot often finds it difficult to find an effective exit path autonomously, affecting the overall cleaning efficiency. In addition, traditional methods rarely take into account the specific shape and distribution of obstacles during the cleaning process, which makes the robot lack flexibility when facing complex environments.

[0004] In the existing technology, some advanced cleaning robots have begun to try to use sensors to enhance their environmental perception capabilities, such as through devices such as LiDAR to achieve more accurate positioning and map construction. Although this type of technology has significantly improved the robot's navigation accuracy and obstacle avoidance performance, it still has limitations when dealing with particularly narrow spaces. The main problems include: the measurement of the specific width in a narrow space is not accurate enough, resulting in robot misjudgment; when moving in a narrow area, there is a lack of an effective cleaning strategy adjustment mechanism, resulting in low cleaning coverage; and when an emergency exit is required, a reliable path planning solution is not provided to ensure safe escape.

[0005] In response to the above problems, the present invention proposes an innovative method for narrow area identification, cleaning and exit of a cleaning robot. The solution first quickly and accurately identifies narrow areas through point cloud data analysis, and selects appropriate cleaning strategies according to the area type, such as parallel or gradually narrowing cleaning methods. At the same time, combined with real-time monitoring and intelligent algorithm optimization, it ensures that the robot can complete the cleaning task while ensuring its own safety and smoothly exit the narrow area. Compared with the prior art, the present invention not only improves the cleaning efficiency and coverage of the robot in narrow areas, but also enhances its ability to cope with complex environments, reduces work interruptions caused by jamming or collisions, and thus provides users with a more efficient and reliable home cleaning solution. Summary of the invention

[0006] The present invention provides a method for a cleaning robot to identify, clean and exit a narrow area, comprising:

[0007] S1. Obtain boundary point cloud data, fit the lengths of both sides of the boundary through the point cloud data, calculate the widths of the straight lines on both sides of the boundary, calculate whether the widths of the straight lines on both sides of the boundary are less than the set threshold, and determine whether the robot enters a narrow area;

[0008] S2, the robot rotates 45 degrees left and 45 degrees right on the spot to obtain the type of narrow area and record the robot's posture data;

[0009] S3, the robot selects the appropriate wall cleaning strategy according to the type of narrow area;

[0010] S4, detecting whether the width of the narrow area ahead is less than a preset safety threshold, executing a stop cleaning operation and starting a return cleaning mechanism;

[0011] S5. After successfully exiting the narrow area, the narrow area information encountered and processed during the cleaning process is marked and stored.

[0012] Preferably, in S1, when fitting the lengths of both sides of the boundary by the forward line laser data, the point cloud data of the left boundary and the right boundary are respectively fitted with a line using the least squares method to obtain the straight lines L of the left and right boundaries. l With L r , calculate the cumulative distance d between consecutive points on each straight line as the length of the side boundary; the left side boundary is Where (x i ,y i ) is the left coordinate; the right boundary is Where (x′ j ,y′ j) is the right coordinate; when the lengths of the boundaries on both sides meet the preset minimum length threshold, a straight line m representing the width of the narrow area ahead is fitted through the forward line laser point cloud, and it is judged whether to enter the narrow area based on this.

[0013] Preferably, the two straight lines L representing the left and right boundaries are fitted. l With L r Then, calculate the shortest distance L between the two lines. m As the width W of the narrow area, the formula is used Where n is the straight line L l With L r The points selected above are used to determine whether the minimum width W is less than the preset prefabricated width, so as to judge that the robot is about to enter or is already in a narrow area that requires special treatment.

[0014] Preferably, in S2, to confirm whether the front is a real narrow area and distinguish the type of narrow lane, the robot first rotates 45 degrees to the left on the spot, uses a line laser sensor to obtain the point cloud data of the obstacle on the left, and calculates the distance from the point cloud data of the obstacle on the left to the center of the robot. Where (x i ,y i ) is the left coordinate, (x robot ,y robot ) is the coordinate of the robot center position; after the robot returns to its initial orientation, it rotates 45 degrees to the right again, collects information about obstacles on the right side using a line laser sensor, and calculates the distance from the point cloud data of the obstacles on the right side to the center of the robot Where (x′ j ,y′ j ) is the right coordinate, and the distance from the right point cloud data to the robot is calculated; by analyzing the distance change trend between the point cloud data from the nearest to the farthest point cloud data and the robot, if the distance from the left or right point cloud data to the robot gradually increases, it is judged that this side is a parallel narrow area; conversely, if the distance from the point cloud data on one side to the robot shows a trend of first decreasing and then increasing, it is considered to be a narrow area type that is getting smaller and smaller.

[0015] Preferably, when the robot completes a 45-degree left rotation and a 45-degree right rotation in situ and obtains relevant data on the narrow area type, the current posture information of the robot is immediately recorded through the built-in inertial measurement unit and encoder, including but not limited to the robot's position coordinates, orientation angle, and the position of the rotation center point; the posture data will be stored in the robot's memory and associated with the corresponding narrow area type information to reproduce the state of the robot in a specific narrow area.

[0016] Preferably, in S3, a suitable wall-cleaning strategy is selected according to the type of narrow area. If it is identified as a parallel narrow area, the robot moves forward and cleans along one wall until there is no passable path ahead and then returns along the original route, and moves parallel to the other wall to continue cleaning until it is identified that there is no passable path ahead and then returns along the original route; if it is identified as a gradually narrowing narrow area, the robot cleans along one wall, and when it detects that the road ahead is impassable, it performs a backward operation and calculates a safe rotation space, completes the rotation action after ensuring that there is enough space for turning, and then continues to clean along the other wall until it completely exits the gradually narrowing area.

[0017] Preferably, when the parallel narrow area is identified, the robot moves forward along one side of the wall to clean, and the width W of the passable path ahead is monitored in real time by the forward line laser sensor. c ; If the calculated width of the traversable path ahead is W c Less than the preset safety threshold W safe , satisfying W c <W safe , the robot determines that there is no way forward, and immediately stops moving forward and performs a return motion until it returns to the initial position before entering the narrow area. The ... the robot immediately stops moving forward and performs a return motion until it returns to the initial position before entering the narrow area. q , using formula D q ′=D q +2×d offset Calculate the target distance D required to move parallel to the other wall q ′, where d offset The offset is a safety offset to ensure that the robot can move smoothly to the other side without colliding with obstacles. After completing the parallel movement, the robot continues to clean along the newly selected wall until it detects that there is no passable path ahead again, and then repeats the above process of returning to the original path.

[0018] Preferably, when the narrow area is identified as a gradually narrowing area, the robot cleans along one side of the wall and continuously monitors the width of the passable path ahead through the forward line laser sensor; once it is detected that the front is impassable, that is, the width of the passable path ahead is less than the preset safety threshold W safe The robot immediately moves backward until it reaches a safe distance d from the nearest obstacle. safe ; According to the current posture information and the point cloud data of the front, back, left and right, the minimum radius R required for rotation is calculated min The safe rotation space is: Where L is the length of the longest side of the robot, and θ is the angle that the robot needs to rotate. After confirming that there is enough space for turning, the robot completes the rotation and continues to clean along the other wall until it completely drives out of the narrowing area.

[0019] Preferably, when cleaning a narrow area in a gradually narrowing manner, the robot cleans along the other side wall, detects obstacles in front through the forward line laser sensor, obtains obstacle point cloud data, and calculates the obstacle point cloud data through the formula Calculate the obstacle length z obstacle , where (x k ,y k ) is the point cloud coordinate of the obstacle. The robot performs a translation operation, translates the width of the obstacle and then moves forward. The robot uses the radar to scan whether it has avoided the obstacle. If it has successfully avoided the obstacle, the robot performs a translation operation to bypass the obstacle and continue cleaning along the wall.

[0020] Preferably, after the robot successfully exits the narrow area in S5, the location coordinates, type, cleaning path and obstacle distribution information of the narrow area encountered during the cleaning process are marked and stored in the robot's memory database; these data are updated to the robot's environmental model in the form of a map, including the specific boundaries of the narrow area, the cleaning strategy adopted, and any special processing measures, to ensure that known narrow areas can be effectively avoided or the cleaning path can be optimized in future cleaning tasks.

[0021] Compared with the prior art, the technical solution of this application has the following technical effects:

[0022] The present invention uses the technical solution of fitting the lengths of both sides of the boundary using point cloud data and calculating the width of the straight line. The present invention can accurately identify the narrow area in front of the cleaning robot. When the robot enters a potential narrow space, it will analyze the forward line laser data to determine whether the current environment meets the criteria for entering the narrow area. This solves the problem of the robot misjudging or failing to find the narrow area in time due to the lack of accurate measurement methods in the traditional method, thereby effectively avoiding the ground jam or collision accidents caused by mistakenly entering the inaccessible area, and improving the safety and efficiency of the cleaning process.

[0023] The present invention adopts a method of obtaining the type of narrow area by rotating left and right 45 degrees in situ, and combines the analysis of the trend of the distance change from the obstacle point cloud data to the center of the robot. The present invention can accurately distinguish different types of narrow areas (such as parallel and gradually narrowing). This not only helps the robot better understand the specific conditions of its environment, but also provides a basis for the subsequent selection of appropriate cleaning strategies. It solves the problem that general cleaning robots are difficult to flexibly adjust their behavior patterns when facing complex layouts, so that efficient and thorough cleaning operations can be achieved even in extremely small spaces, enhancing the adaptability and flexibility of the robot.

[0024] The present invention is a technical solution that automatically adjusts the cleaning strategy according to the type of narrow area. For example, for a parallel narrow area, the cleaning strategy is to move forward along one side of the wall until there is no way to pass, then return to the original path and switch to the other side to continue cleaning. For a gradually narrowing area, a safe rotation action will be performed to change the direction of travel when it is detected that the road ahead is impassable. This method solves the problem in the prior art that the cleaning strategy is single and does not consider specific environmental factors, resulting in low cleaning efficiency and insufficient coverage. As a result, a high cleaning coverage rate can be guaranteed regardless of whether it is in a narrow area of ​​regular or irregular shape, and unnecessary repeated cleaning is reduced, thereby optimizing the overall cleaning path planning.

[0025] The present invention stores the relevant location coordinates, type and other information marks in the memory database after successfully exiting the narrow area, so that the cleaning robot can actively avoid known difficult areas or adopt a better cleaning path in future cleaning tasks. This function overcomes the shortcomings of the traditional system that lacks a memory mechanism and needs to relearn the environment structure every time cleaning. The ultimate effect is that over time, the robot can gradually form a deep understanding of its working environment, further improving cleaning efficiency and user experience, while also reducing energy consumption caused by frequent attempts to explore unknown areas.

[0026] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application so that it can be implemented in accordance with the contents of the specification, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following is a detailed description of the preferred embodiments of the present application in conjunction with the accompanying drawings as follows.

[0027] Based on the detailed description of the specific embodiments of the present application in combination with the accompanying drawings below, those skilled in the art will become more aware of the above and other objects, advantages and features of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings without creative work. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale.

[0029] Figure 1 This is a flow chart of a method for narrow area identification, cleaning and exiting of a cleaning robot according to the present invention;

[0030] Figure 2 A structural diagram of the cleaning robot of the present invention;

[0031] Figure 3 This is an identification diagram of a method for recognizing, cleaning and exiting a narrow area of ​​a cleaning robot according to the present invention;

[0032] Figure 4 A path diagram of the cleaning robot of the present invention in a parallel narrow area;

[0033] Figure 5 A path diagram of the cleaning robot of the present invention in a gradually narrowing narrow area;

[0034] Figure 6 It is an obstacle path diagram of the cleaning robot of the present invention in a gradually narrowing narrow area;

[0035] Figure 7 The walls on both sides of the cleaning robot of the present invention are all at a height that can be identified by radar;

[0036] Figure 8 The height radar of the wall on one side of the cleaning robot of the present invention cannot recognize the path map;

[0037] Fig. 9 The height radars of the walls on both sides of the cleaning robot of the present invention cannot recognize the path map. DETAILED DESCRIPTION

[0038] To make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, rather than all of the embodiments. In the following description, specific details such as specific configuration and components are provided only to help fully understand the embodiments of the present application. Therefore, it should be clear to those skilled in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, for clarity and brevity, the description of known functions and structures is omitted in the embodiment.

[0039] It should be understood that the references to "one embodiment" or "this embodiment" throughout the specification mean that the specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present application. Therefore, the references to "one embodiment" or "this embodiment" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0040] In addition, the present application may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplicity and clarity, and does not in itself indicate the relationship between the various embodiments and / or settings discussed.

[0041] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" in this article describes another type of association object relationship, indicating that there can be two relationships. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the previous and next associated objects are in an "or" relationship.

[0042] The term "at least one" in this article is merely a description of the association relationship of associated objects, indicating that there may be three relationships. For example, at least one of A and B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0043] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusions.

[0044] Example 1

[0045] This embodiment mainly describes a method for a cleaning robot to identify, clean and exit a narrow area. Figure 1 As shown, including:

[0046] S1. Obtain boundary point cloud data, fit the lengths of both sides of the boundary through the point cloud data, calculate the widths of the straight lines on both sides of the boundary, calculate whether the widths of the straight lines on both sides of the boundary are less than the set threshold, and determine whether the robot enters a narrow area;

[0047] S2, the robot rotates 45 degrees left and 45 degrees right on the spot to obtain the type of narrow area and record the robot's posture data;

[0048] S3, the robot selects the appropriate wall cleaning strategy according to the type of narrow area;

[0049] S4, detecting whether the width of the narrow area ahead is less than a preset safety threshold, executing a stop cleaning operation and starting a return cleaning mechanism;

[0050] S5. After successfully exiting the narrow area, the narrow area information encountered and processed during the cleaning process is marked and stored.

[0051] like Figure 2The cleaning robot can realize identification and exit by setting radar and line laser. The radar is located on the top of the cleaning robot to detect suspended obstacles. The line laser includes forward line laser and side line laser. The forward line laser is located at the front end of the cleaning robot, and the side line laser is located on both sides of the cleaning robot to detect low obstacles.

[0052] Furthermore, when fitting the lengths of both sides of the boundary through the forward line laser data, the point cloud data of the left boundary and the right boundary are fitted with straight lines using the least squares method to obtain the straight lines L of the left and right boundaries. l With L r , calculate the cumulative distance d between consecutive points on each straight line as the length of the side boundary; the left side boundary is Where (x i ,y i ) is the left coordinate; the right boundary is Where (x′ j ,y′ j ) is the right coordinate; when the lengths of the two side boundaries meet the preset minimum length threshold, a straight line L representing the width of the narrow area in front is fitted through the forward line laser point cloud m , and judge whether it has entered a narrow area based on this.

[0053] Further, two straight lines L representing the left and right boundaries are fitted l With L r Then, calculate the shortest distance L between the two lines. m As the width W of the narrow area, the formula is used Where n is the straight line L l With L r The points selected above are used to determine whether the minimum width W is less than the preset prefabricated width, so as to judge that the robot is about to enter or is already in a narrow area that requires special treatment.

[0054] Further, if Figure 3 As shown in the figure, to confirm whether the front is a real narrow area and distinguish the type of narrow alley, the robot first rotates 45 degrees to the left on the spot, uses the line laser sensor to obtain the point cloud data of the obstacle on the left, and calculates the distance from the point cloud data of the obstacle on the left to the center of the robot. Where (x i ,y i ) is the left coordinate, (x robot ,y robot ) is the coordinate of the robot center position; after the robot returns to its initial orientation, it rotates 45 degrees to the right again, collects information about obstacles on the right side using a line laser sensor, and calculates the distance from the point cloud data of the obstacles on the right side to the center of the robot Where (x′ j ,y′ j ) is the right coordinate, and the distance from the right point cloud data to the robot is calculated; by analyzing the distance change trend between the point cloud data from the nearest to the farthest point cloud data and the robot, if the distance from the left or right point cloud data to the robot gradually increases, it is judged that this side is a parallel narrow area; conversely, if the distance from the point cloud data on one side to the robot shows a trend of first decreasing and then increasing, it is considered to be a narrow area type that is getting smaller and smaller.

[0055] Furthermore, when the robot completes a 45-degree left rotation and a 45-degree right rotation on the spot and obtains relevant data on the narrow area type, the current posture information of the robot is immediately recorded through the built-in inertial measurement unit and encoder, including but not limited to the robot's position coordinates, orientation angle, and the position of the rotation center point; the posture data will be stored in the robot's memory and associated with the corresponding narrow area type information to reproduce the state of the robot in a specific narrow area.

[0056] Furthermore, appropriate wall cleaning strategies are selected according to the type of narrow area, such as Figure 4 As shown, if it is identified as a parallel narrow area, the robot will move forward and clean along one wall until there is no passable path ahead, then return along the original path, and move parallel to the other wall to continue cleaning until it is identified that there is no passable path ahead, then return along the original path;

[0057] like Figure 5 As shown, the robot identifies a gradually narrowing area and cleans along one wall. When it detects that the road ahead is impassable, it backs up and calculates a safe rotation space. After ensuring that there is enough space for turning, it completes the rotation action and then continues to clean along the other wall until it completely exits the narrow area.

[0058] Further, if Figure 4 As shown in the figure, when a parallel narrow area is identified, the robot moves forward along one side of the wall to clean, and the width W of the passable path ahead is monitored in real time through the forward line laser sensor. c ; If the calculated width of the traversable path ahead is W c Less than the preset safety threshold W safe , satisfying W c <W safe , the robot determines that there is no way forward, and immediately stops moving forward and performs a return motion until it returns to the initial position before entering the narrow area. The ... the robot immediately stops moving forward and performs a return motion until it returns to the initial position before entering the narrow area. q , using formula D q ′=D q +2×d offset Calculate the target distance D required to move parallel to the other wallq ′, where d offset The offset is a safety offset to ensure that the robot can move smoothly to the other side without colliding with obstacles. After completing the parallel movement, the robot continues to clean along the newly selected wall until it detects that there is no passable path ahead again, and then repeats the above process of returning to the original path.

[0059] like Figure 5 As shown in the figure, when a gradually narrowing area is identified, the robot cleans along one wall and continuously monitors the width of the passable path ahead through the forward line laser sensor; once it is detected that the front is impassable, that is, the width of the passable path ahead is less than the preset safety threshold W safe The robot immediately moves backward until it reaches a safe distance d from the nearest obstacle. safe ; According to the current posture information and the point cloud data of the front, back, left and right, the minimum radius R required for rotation is calculated min The safe rotation space is: Where L is the length of the longest side of the robot, and θ is the angle that the robot needs to rotate. After confirming that there is enough space for turning, the robot completes the rotation and continues to clean along the other wall until it completely drives out of the narrowing area.

[0060] Further, if Figure 6 As shown in the figure, when cleaning a narrow area, the robot cleans along the other side of the wall, detects obstacles in front through the forward line laser sensor, obtains obstacle point cloud data, and uses the formula Calculate obstacle length Z obstacle , where (x k ,y k ) is the point cloud coordinate of the obstacle. The robot performs a translation operation, translates the width of the obstacle and then moves forward. The robot uses the radar to scan whether it has avoided the obstacle. If it has successfully avoided the obstacle, the robot performs a translation operation to bypass the obstacle and continue cleaning along the wall.

[0061] Furthermore, after the robot successfully exits the narrow area in S5, the location coordinates, type, cleaning path and obstacle distribution information of the narrow area encountered during the cleaning process are marked and stored in the robot's memory database; these data are updated to the robot's environmental model in the form of a map, including the specific boundaries of the narrow area, the cleaning strategy adopted, and any special processing measures, to ensure that known narrow areas can be effectively avoided or the cleaning path can be optimized in future cleaning tasks.

[0062] This embodiment uses point cloud data to fit the boundary length, distinguish the types of narrow areas, and select appropriate cleaning strategies accordingly, so that the cleaning robot can not only accurately identify and safely enter narrow spaces when encountering them, but also efficiently complete the cleaning task and exit smoothly when necessary. This solves the problem of ground jamming or inefficient cleaning caused by the lack of accurate measurement and flexible response mechanism in traditional methods, significantly improves the adaptability and cleaning efficiency of the robot in complex environments, and reduces unnecessary energy consumption, providing users with a more intelligent and reliable cleaning solution.

[0063] Example 2

[0064] This embodiment is based on Embodiment 1 and describes in detail an optimization scheme of a method for recognizing, cleaning and exiting a narrow area by a cleaning robot, which specifically includes:

[0065] In the existing environment, there are three different cleaning environments, including walls on both sides with a height that can be identified by radar, walls on one side with a height that cannot be identified by radar, and walls on both sides with a height that cannot be identified by radar;

[0066] like Figure 7 As shown, the walls on both sides are recognizable height walls, which can be identified, cleaned and exited through the technical solution of this application;

[0067] like Figure 8 As shown in the figure, the height of the wall on one side cannot be identified by the radar, the right side is a straight wall, and the left side is a low obstacle (not visible to the radar). The cleaning machine comes from the right side along the wall. narrow The straight-line distance from the left obstacle to the right obstacle, the cleaning robot detects the right straight wall through radar and the right obstacle through line laser, realizes the recognition of narrow areas, and realizes cleaning and exit through this technical solution;

[0068] like Fig. 9 As shown, the heights of the walls on both sides cannot be identified by radar. The cleaning robot uses line laser to detect obstacles on the left and right sides to identify narrow areas, and clean and exit through this technical solution.

[0069] This embodiment describes in detail that the cleaning robot uses line laser detection technology. Even when faced with walls that cannot be identified by radar, it can also achieve narrow area identification, cleaning and exit according to the technical method of this application, thus overcoming the difficulty that traditional cleaning robots cannot identify.

[0070] The above are only preferred embodiments of the present invention, which do not limit the scope of protection of the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any changes, modifications, replacements, integrations and parameter changes to these embodiments within the spirit and principles of the present invention through conventional substitutions or without departing from the principles and spirit of the present invention fall within the scope of protection of the present invention.

Claims

1. A method for identifying, cleaning and exiting a narrow area by a cleaning robot, characterized in that: include: S1. Obtain boundary point cloud data, fit the lengths of both sides of the boundary through the point cloud data, calculate the widths of the straight lines on both sides of the boundary, calculate whether the widths of the straight lines on both sides of the boundary are less than the set threshold, and determine whether the robot enters a narrow area; S2, the robot rotates 45 degrees left and 45 degrees right on the spot to obtain the type of narrow area and record the robot's posture data; S3, the robot selects the appropriate wall cleaning strategy according to the type of narrow area; S4, detecting whether the width of the narrow area ahead is less than a preset safety threshold, executing a stop cleaning operation and starting a return cleaning mechanism; S5. After successfully exiting the narrow area, the narrow area information encountered and processed during the cleaning process is marked and stored.

2. A method for identifying, cleaning and exiting a narrow area by a cleaning robot according to claim 1, characterized in that: In S1, when fitting the lengths of both sides of the boundary by the forward line laser data, the point cloud data of the left boundary and the right boundary are fitted with a line by the least square method to obtain the line L of the left and right boundaries. l With L r , calculate the cumulative distance d between consecutive points on each straight line as the length of the side boundary; the left side boundary is Where (x i ,y i ) is the left coordinate; the right boundary is Where (x′ j ,y′ j ) is the right coordinate; when the lengths of the two side boundaries meet the preset minimum length threshold, a straight line L representing the width of the narrow area in front is fitted through the forward line laser point cloud m , and judge whether it has entered a narrow area based on this.

3. A method for recognizing, cleaning and exiting a narrow area by a cleaning robot according to claim 2, characterized in that: The two straight lines L representing the left and right boundaries are fitted l With L r Then, calculate the shortest distance L between the two lines. m As the width W of the narrow area, the formula is used Where n is the straight line L l With L r The points selected above are used to determine whether the minimum width W is less than the preset prefabricated width, so as to judge that the robot is about to enter or is already in a narrow area that requires special treatment.

4. A method for recognizing, cleaning and exiting a narrow area by a cleaning robot according to claim 1, characterized in that: In S2, the robot first rotates 45 degrees to the left in place to confirm whether the area ahead is a real narrow area and distinguish the type of narrow alley. The line laser sensor is used to obtain the point cloud data of the obstacle on the left, and the distance from the point cloud data of the obstacle on the left to the center of the robot is calculated. Where (x i ,y i ) is the left coordinate, (x robot ,y robot ) is the coordinate of the robot center position; after the robot returns to its initial orientation, it rotates 45 degrees to the right again, collects information about obstacles on the right side using a line laser sensor, and calculates the distance from the point cloud data of the obstacles on the right side to the center of the robot Where (x′ j ,y′ j ) is the right coordinate, and the distance from the right point cloud data to the robot is calculated; by analyzing the distance change trend between the point cloud data from the nearest to the farthest point cloud data and the robot, if the distance from the left or right point cloud data to the robot gradually increases, it is judged that this side is a parallel narrow area; conversely, if the distance from the point cloud data on one side to the robot shows a trend of first decreasing and then increasing, it is considered to be a narrow area type that is getting smaller and smaller.

5. A method for identifying, cleaning and exiting a narrow area by a cleaning robot according to claim 1 or 4, characterized in that: When the robot completes a 45-degree left rotation and a 45-degree right rotation on the spot and obtains relevant data on the narrow area type, the current robot's posture information is immediately recorded through the built-in inertial measurement unit and encoder, including but not limited to the robot's position coordinates, orientation angle, and the position of the rotation center point; the posture data will be stored in the robot's memory and associated with the corresponding narrow area type information to reproduce the robot's state in a specific narrow area.

6. A method for recognizing, cleaning and exiting a narrow area by a cleaning robot according to claim 1 or 4, characterized in that: In S3, a suitable wall-cleaning strategy is selected according to the type of narrow area. If a parallel narrow area is identified, the robot moves forward and cleans along one wall until there is no passable path ahead, then returns along the original route, and moves parallel to the other wall to continue cleaning until it is identified that there is no passable path ahead, then returns along the original route. If a gradually narrowing narrow area is identified, the robot cleans along one wall, and when it detects that the road ahead is impassable, it performs a backward operation and calculates a safe rotation space, completes the rotation action after ensuring that there is enough space for turning, and then continues to clean along the other wall until it completely exits the narrow area.

7. A method for recognizing, cleaning and exiting a narrow area by a cleaning robot according to claim 6, characterized in that: When the parallel narrow area is identified, the robot moves forward and cleans along one side of the wall, and the forward line laser sensor monitors the width W of the passable path in front in real time. c ; If the calculated width of the traversable path ahead is W c Less than the preset safety threshold W safe , satisfying W c <W safe , the robot determines that there is no way forward, and immediately stops moving forward and performs a return motion until it returns to the initial position before entering the narrow area. The ... the robot immediately stops moving forward and performs a return motion until it returns to the initial position before entering the narrow area. q , using formula D q ′=D q +2×d offset Calculate the target distance D required to move parallel to the other wall q ′, where d offset The offset is a safety offset to ensure that the robot can move smoothly to the other side without colliding with obstacles. After completing the parallel movement, the robot continues to clean along the newly selected wall until it detects that there is no passable path ahead again, and then repeats the above process of returning to the original path.

8. A method for recognizing, cleaning and exiting a narrow area by a cleaning robot according to claim 6, characterized in that: When the robot is identified as a gradually narrowing area, it cleans along one side of the wall and continuously monitors the width of the passable path ahead through the forward line laser sensor; once it detects that the front is impassable, that is, the width of the passable path ahead is less than the preset safety threshold W safe The robot immediately moves backward until it reaches a safe distance d from the nearest obstacle. safe ; According to the current posture information and the point cloud data of the front, back, left and right, the minimum radius R required for rotation is calculated min The safe rotation space is: Where L is the length of the longest side of the robot, and θ is the angle that the robot needs to rotate. After confirming that there is enough space for turning, the robot completes the rotation and continues to clean along the other wall until it completely drives out of the narrowing area.

9. A method for identifying, cleaning and exiting a narrow area by a cleaning robot according to claim 8, characterized in that: When cleaning a narrow area in a gradually narrowing manner, the robot cleans along the wall on the other side, detects obstacles in front of it through the forward line laser sensor, obtains obstacle point cloud data, and calculates the obstacle point cloud data through the formula Calculate obstacle length Z obstacle , where (x k ,y k ) is the point cloud coordinate of the obstacle. The robot performs a translation operation, translates the width of the obstacle and then moves forward. The robot uses the radar to scan whether it has avoided the obstacle. If it has successfully avoided the obstacle, the robot performs a translation operation to bypass the obstacle and continue cleaning along the wall.

10. A method for recognizing, cleaning and exiting a narrow area by a cleaning robot according to claim 1, characterized in that: After the robot successfully exits the narrow area in S5, the location coordinates, type, cleaning path and obstacle distribution information of the narrow area encountered during the cleaning process are marked and stored in the robot's memory database; these data are updated to the robot's environmental model in the form of a map, including the specific boundaries of the narrow area, the cleaning strategy adopted, and any special processing measures, to ensure that known narrow areas can be effectively avoided or the cleaning path can be optimized in future cleaning tasks.

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