Mobile robot, motion positioning control method, apparatus and system therefor, and medium

Abstract

Disclosed in the present application are a mobile robot, a motion positioning control method, apparatus and system therefor, and a medium, relating to the technical field of engineering machinery. The method comprises: when a mobile robot is within a deviation threshold range of a target position, performing attitude adjustment on the basis of point cloud data obtained by emitting linear structured light to a target workpiece, so that the emitted linear structured light is aimed at the target workpiece; and after attitude adjustment, controlling the mobile robot to move in a straight line parallel to the target workpiece and continuously emit linear structured light, and, on the basis of position changes of the continuously emitted linear structured light relative to the target workpiece, adjusting the transverse position of the mobile robot relative to the target workpiece, so that the mobile robot reaches the target position. In the embodiments of the present application, the linear structured light is used for attitude adjustment of the mobile robot, and the mobile robot is controlled to move laterally, thus achieving precise positioning of the mobile robot, and adapting to more scenarios.

Description

Mobile robots and their motion positioning and control methods, devices, systems and media

[0001] Cross-reference of related applications

[0002] This application claims the benefit of Chinese Patent Application No. 202411939122.7, filed on December 26, 2024, the contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of engineering machinery technology, specifically to a mobile robot and its motion positioning control method, device, system and medium. Background Technology

[0004] In the field of engineering machinery, the application of a large number of industrial robots has replaced some of the high-intensity, batch-based manual operations, but there are still problems that have not been solved. Taking welding operations as an example, there are the following problems: 1) In open and semi-open structural spaces, there are still a large number of discrete, all-position, small-sized welds that need to be welded manually; 2) Traditional industrial robots and their welding workstations have limited spatial movement range due to external tracks, resulting in a limited spatial working range, and they are also large in size, heavy in weight, and have high cost and energy consumption.

[0005] Mobile robots are favored for their lightweight, flexibility, convenience, and portability. For example, for discrete, all-position welding of large structures, the traditional large, heavy, high-cost, and high-energy-consuming gantry-type welding machines have been replaced by lightweight, flexible, low-cost, and low-energy-consuming mobile welding robots. This greatly increases the robot's operating space, saves space, and reduces costs.

[0006] Currently, there are many methods for mobile robot motion localization, such as electromagnetic guidance, which requires laying electromagnetic tracks on the ground, a cumbersome process, and making it difficult to change or extend the path. Another method is QR code guidance, which uses a camera to scan QR codes on the ground to obtain current location information, but requires laying a large number of QR codes on-site, and these codes are easily worn, resulting in high maintenance costs. Visual navigation uses onboard visual sensors to acquire image information of the operating area for navigation, but this method requires ground texture information, and due to the limited field of view of visual sensors, it is only suitable for small-area operations. LiDAR navigation models the environment by scanning it and specifying the target location, enabling navigation, localization, and obstacle avoidance in large areas. However, this method requires pre-specifying the target location and is limited by sensor accuracy, resulting in low positioning accuracy. Other methods include GPS navigation and inertial navigation, but these methods often have large accuracy errors.

[0007] Therefore, a new motion positioning and control scheme for mobile robots is needed. Summary of the Invention

[0008] The purpose of this application is to provide a mobile robot and its motion positioning control method, device, system and medium to at least partially solve the above-mentioned technical problems.

[0009] To achieve the above objectives, a first aspect of this application provides a motion positioning control method for a mobile robot, comprising: when the mobile robot reaches a target point position within a deviation threshold range, adjusting the attitude of the mobile robot based on point cloud data obtained by the mobile robot emitting line structured light towards a target workpiece, so that the emitted line structured light is aligned with the target workpiece; and after the attitude adjustment, controlling the mobile robot to move in a straight line parallel to the target workpiece and continuously emitting line structured light, and adjusting the lateral position of the mobile robot relative to the target workpiece based on the position change of the continuously emitted line structured light relative to the target workpiece, so that the mobile robot reaches the target point position.

[0010] In this embodiment of the application, the deviation threshold range is determined such that when the target workpiece is placed within the specified threshold area, it is within the field of view corresponding to the line structured light.

[0011] In this embodiment of the application, during the process of the mobile robot reaching the target point location within the deviation threshold range, the motion positioning control method further includes: determining the rotation angle of a proposed virtual wheel based on the deviation factor between the actual path and the planned path of the mobile robot, wherein the virtual wheel is located at the middle position of a pair of actual walking wheels of the mobile robot; solving for the rotation angle of the actual walking wheels of the mobile robot based on the determined rotation angle of the virtual wheel; and performing path tracking based on the rotation angle of the actual walking wheels to control the mobile robot to reach the target point location within the deviation threshold range.

[0012] In this embodiment, the posture adjustment of the mobile robot includes: performing linear fitting on the point cloud data and selecting a first straight line from the fitted straight lines; translating the first straight line along the Z-axis of the line structured light plane coordinate system to obtain a second straight line intersecting the X-axis of the line structured light plane coordinate system, wherein the optical axis corresponding to the line structured light is the Z-axis, and the axis perpendicular to the Z-axis is the X-axis; obtaining the angle between the second straight line and the X-axis of the line structured light plane coordinate system as the body rotation angle; and controlling the mobile robot to rotate in place around the body axis by the body rotation angle to complete the posture adjustment.

[0013] In this embodiment of the application, adjusting the lateral position of the mobile robot relative to the target workpiece includes: determining the transverse straight line intersecting the line structured light plane and the outer surface of the target workpiece; and controlling the mobile robot to move along the direction of the transverse straight line according to the current position of the mobile robot and the current position change of the line structured light relative to the transverse straight line, so that the mobile robot reaches the target point position.

[0014] In this embodiment of the application, the motion positioning control method further includes: determining the length of the cross-section line as the width of the target workpiece based on the moving distance of the mobile robot along the direction of the cross-section line and the distance between the endpoint of the cross-section line and the optical axis point of the current line structured light on the cross-section line; and determining the model of the target workpiece based on the width of the target workpiece.

[0015] In this embodiment, controlling the mobile robot to move along the direction of the transverse straight line includes: a first movement control step, whereby, if the line structured light emitted by the mobile robot at its current position after the attitude adjustment covers the first endpoint of the transverse straight line but not the second endpoint, the mobile robot is controlled to move along a first direction until the corresponding line structured light covers the second endpoint of the transverse straight line, and then the mobile robot is controlled to stop, wherein the first direction is the direction from the first endpoint to the second endpoint, and the second direction is opposite to the first direction; and a second movement control step, whereby the mobile robot is controlled to turn to the second direction and move until the optical axis point of the corresponding line structured light coincides with the midpoint of the transverse straight line, and then the mobile robot is controlled to stop, wherein the position of the mobile robot at the time of the coincidence is the target point position.

[0016] In this embodiment, controlling the mobile robot to move along the direction of the transverse straight line further includes: a third movement control step, in which, if the line structured light emitted by the mobile robot at its current position after the attitude adjustment cannot cover any endpoint of the transverse straight line and does not generate point cloud data, the mobile robot is controlled to move along the first direction until the corresponding line structured light covers the first endpoint, at which point the first movement control step is executed; and a fourth movement control step, in which, if the line structured light emitted by the mobile robot at its current position after the attitude adjustment cannot cover any endpoint of the transverse straight line and can generate point cloud data, the mobile robot is controlled to move along the second direction until the corresponding line structured light covers the first endpoint, at which point the first movement control step is executed.

[0017] A second aspect of this application provides a motion positioning control device for a mobile robot, comprising: a memory configured to store instructions; and a processor configured to retrieve the instructions from the memory and, when executing the instructions, to implement any of the aforementioned motion positioning control methods.

[0018] A third aspect of this application provides a motion positioning control system for a mobile robot, comprising: a sensing component, the sensing component including at least a line structured light sensor mounted on the mobile robot for emitting line structured light to scan the surface of a target workpiece to obtain corresponding point cloud data; and the aforementioned motion positioning control device for controlling the mobile robot to move to a target point position based on the point cloud data.

[0019] In this embodiment of the application, the sensing component further includes a multi-line lidar sensor and / or an ultrasonic sensor mounted on the mobile robot, wherein the multi-line lidar sensor is used to assist the mobile robot in path planning, obstacle avoidance, or positioning, and the ultrasonic sensor is used to assist the mobile robot in obstacle avoidance.

[0020] The fourth aspect of this application provides a mobile robot, including the motion positioning control system of any of the mobile robots described above.

[0021] The fifth aspect of this application provides a machine-readable storage medium storing instructions for causing a machine to execute any of the motion positioning control methods described above for mobile robots.

[0022] Through the above technical solution, the embodiments of this application combine line structured light to adjust the posture of the mobile robot and control its lateral movement, so that the mobile robot can eventually reach the target point. This achieves precise positioning of the mobile robot without the need for additional electromagnetic tracks, ground QR codes, vehicle-mounted vision sensors and various navigation devices, which not only improves positioning accuracy but also adapts to more scenarios.

[0023] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0024] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0025] Figure 1 schematically illustrates a flow chart of a motion positioning control method for a mobile robot according to an embodiment of this application;

[0026] Figure 2 schematically illustrates the structure of a mobile welding robot system according to an example embodiment of this application;

[0027] Figure 3 schematically illustrates a coarse positioning diagram of a mobile welding robot according to an example embodiment of this application;

[0028] Figure 4 schematically illustrates the main flow diagram of motion positioning control of an example mobile welding robot according to an embodiment of this application;

[0029] Figure 5 schematically illustrates a flowchart of a navigation motion precision positioning control strategy employed by an example mobile welding robot according to an embodiment of this application;

[0030] Figure 6 schematically illustrates a mobile welding robot path tracking example according to an embodiment of this application;

[0031] Figure 7 schematically illustrates the principle of displacement tracking and rotation angle calculation for a mobile welding robot according to an example embodiment of this application;

[0032] Figure 8 schematically illustrates a point cloud line fitting diagram according to an example of an embodiment of this application;

[0033] Figure 9 schematically illustrates a mobile chassis attitude adjustment diagram according to an example of an embodiment of this application;

[0034] Figure 10 schematically illustrates a diagram of lateral movement of a robot according to an example embodiment of this application;

[0035] Figures 11(1)-11(4) schematically illustrate the robot movement control principle in a first scenario according to an embodiment of this application;

[0036] Figures 12(1)-12(4) schematically illustrate the robot movement control principle in a second scenario according to an example of an embodiment of this application;

[0037] Figure 13 schematically illustrates a structural diagram of motion positioning control for a mobile robot according to an embodiment of this application; and

[0038] Figure 14 schematically illustrates a structural block diagram of a motion positioning control system for a mobile robot according to an embodiment of this application.

[0039] Figure Reference Numerals: 100 Sensing Component; 200 Motion Positioning Control Device; 1 Box Steel Structure Component; 2 Structured Light Beam; 3 Weld Seam Tracking Sensor; 4 Welding Robotic Arm and Welding Torch; 5 Multi-line LiDAR Sensor; 6 Linear Structured Light Sensor; 7 Ultrasonic Sensor; 8 Mobile Chassis; 9 Welding Machine and Welding System; 10 Rope Winding Winch Mechanism; 11 Power Supply Line; 12 Power Supply Column; 13 Threshold Area Range; 14 Deviation Threshold Range Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0041] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0042] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0043] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0044] Figure 1 schematically illustrates a flow chart of a motion positioning control method for a mobile robot according to an embodiment of this application. As shown in Figure 1, the motion positioning control method may include the following steps S100-S200.

[0045] Step S100: When the mobile robot reaches the target point position within the deviation threshold range, the attitude of the mobile robot is adjusted according to the point cloud data obtained by the mobile robot emitting line structured light to the target workpiece, so that the emitted line structured light is aligned with the target workpiece.

[0046] The phrase "controlling the mobile robot to reach the target point within a deviation threshold range" refers to coarse positioning of the mobile robot. Furthermore, aligning the emitted line structured light with the target workpiece specifically means ensuring that the optical axis of the line structured light is perpendicular to the outer surface of the target workpiece being illuminated. Therefore, step S100, based on the coarse positioning of the mobile robot, adjusts the robot's posture so that the line structured light emitted by the mobile robot can perpendicularly illuminate the outer surface of the target workpiece.

[0047] Step S200: After the posture adjustment, control the mobile robot to move in a straight line parallel to the target workpiece and continuously emit line structured light. Adjust the lateral position of the mobile robot relative to the target workpiece according to the position change of the continuously emitted line structured light relative to the target workpiece so that the mobile robot reaches the target point position.

[0048] That is, after step S100, the mobile robot is already within the deviation threshold range of the target point position, and the emitted line structured light can vertically illuminate the outer surface of the target workpiece. Therefore, in step S200, the mobile robot is controlled to move laterally according to the positional changes of the continuously emitted line structured light relative to the target workpiece, so that the mobile robot finally reaches the target point position, achieving precise positioning of the mobile robot. In this process, the attitude adjustment and precise positioning of the mobile robot are performed by line structured light, eliminating the need for additional electromagnetic tracks, ground QR codes, vehicle-mounted vision sensors, and various navigation devices, which improves positioning accuracy and adapts to more scenarios.

[0049] The following uses the mobile welding robot shown in Figures 2-12(4) as an example to illustrate the application of the above-mentioned motion positioning control method in the embodiments of this application.

[0050] Figure 2 schematically illustrates the structure of a mobile welding robot system according to an example embodiment of this application. As shown in Figure 2, the entire mobile welding robot system consists of a large box-shaped steel structure 1, a structured light beam 2, a weld seam tracking sensor 3, a welding robotic arm and welding torch 4, a multi-line lidar sensor 5, a large field-of-view structured light sensor 6, an ultrasonic sensor 7, a mobile chassis 8, a welding machine and welding system 9, a rope winch mechanism 10, a power supply line 11, and a power column 12.

[0051] Figure 3 schematically illustrates a coarse positioning diagram of a mobile welding robot according to an embodiment of this application. Referring to Figures 2 and 3, the large box-shaped steel structure 1 is arbitrarily placed within a threshold region 13. The origin O of the coordinate system of the multi-line lidar sensor 5 is located on the perpendicular bisector of the mobile chassis 8. The mobile chassis 8 models the large-scale environment using the multi-line lidar sensor 5 and specifies the target point location B. A path-tracking PID navigation control algorithm can be developed for the multi-line lidar sensor 5 to assist in controlling the mobile chassis 8 to navigate, avoid obstacles, and perform coarse positioning at any location in the workshop (starting point A). The ultrasonic sensor 7 is used to assist in controlling the mobile chassis 8 to avoid obstacles and reduce blind spots. When the mobile chassis 8 moves along the path planned by the multi-line lidar sensor 5, the ultrasonic sensor 7 and the multi-line lidar sensor 5 detect obstacles, which can assist in controlling the mobile chassis 8 to bypass the obstacles and move to the target point location B. The power supply lines 11 of the mobile chassis 8 and the welding machine and welding system 9 are connected to the power column 12 via a rope winch mechanism 10. The rope winch mechanism 10 matches the moving speed of the mobile chassis 8 to release and wind the rope on the power supply line 11. The rope winch mechanism 10 can rotate freely within 360° around its own base along with the mobile chassis 8, ensuring that the angle of releasing and winding the rope by the rope winch mechanism 10 is always along the direction of the power supply line 11.

[0052] As shown in Figure 3, the mobile chassis 8 navigates from the starting point A to the target point B. Due to navigation and positioning deviations, the mobile chassis 8 and the placement position of the large box-shaped steel structure component 1 shift within the deviation threshold range 14. Furthermore, because the movement trajectory of the welding robotic arm and welding torch 4 is fixed, the welding position of the welding robotic arm and welding torch 4 becomes unreachable. Therefore, a secondary correction of the posture of the mobile chassis 8 is required, namely, performing the posture adjustment in step S100 and the fine positioning in step S200.

[0053] In a preferred embodiment of this application, the deviation threshold range is determined such that the target workpiece is placed within the field of view corresponding to the line structured light when placed within the specified threshold area. That is, corresponding to the example in Figure 3, the deviation threshold range 14 is determined such that the large box-shaped steel structure 1 is placed within the field of view corresponding to the line structured light sensor 6 when placed within the threshold area range 13. In this way, it can not only help solve the problem of low navigation and positioning accuracy of the mobile chassis 8, but also realize arbitrary placement of the large box-shaped steel structure 1 within the threshold area range 13.

[0054] Furthermore, based on the examples corresponding to Figures 2 and 3, a secondary fine positioning control strategy for the navigation motion of a mobile welding robot can be developed according to the motion positioning control method of the embodiments of this application to improve the navigation positioning accuracy of the mobile chassis 8. It should be noted that the development of this secondary fine positioning control strategy involves preferred embodiments of this application, and these embodiments should also fall within the protection scope of the embodiments of this application.

[0055] Specifically, Figure 4 schematically illustrates the main flow diagram of motion positioning control of an example mobile welding robot according to an embodiment of this application, and Figure 5 schematically illustrates the flowchart of the navigation motion precision positioning control strategy adopted by the example mobile welding robot according to an embodiment of this application. As shown in Figure 4, the following steps S1-S8 may be included, and each step is adaptively combined with the steps of the navigation motion precision positioning control strategy in Figure 5.

[0056] Step S1: Develop a path tracking control algorithm for the mobile welding robot to perform path navigation.

[0057] For example, Figure 6 schematically illustrates a path tracking diagram of a mobile welding robot according to an embodiment of this application, following the examples of Figures 2 and 3. The mobile welding robot is a four-wheeled vehicle, and will be simply referred to as a vehicle below. As shown in Figure 6, with O... G XY is the world coordinate system; O RXY is the travel coordinate system of the mobile chassis 8, with the vehicle's geometric center as the origin; (Xg, Yg) is the point on the planned path closest to the vehicle's geometric center, and r represents the closest distance on the planned path to the vehicle's geometric center; θ is the angle between the direction parallel to the vehicle's flight path and the road direction, which can be understood as the deviation angle between the current vehicle flight path and the road's travel direction.

[0058] In a preferred embodiment of this application, the path tracking scheme includes: determining the rotation angle of a proposed virtual wheel based on a deviation factor between the actual path and the planned path of the mobile robot, wherein the virtual wheel is located at the middle position of a pair of actual walking wheels of the mobile robot; solving for the rotation angle of the actual walking wheels of the mobile robot based on the determined rotation angle of the virtual wheel; and performing path tracking based on the rotation angle of the actual walking wheels to control the mobile robot to reach the target point within the deviation threshold range.

[0059] For this path tracking scheme, taking Figure 6 as an example, a virtual tire is proposed, positioned between tires M1 and M4. δ represents the turning angle of the virtual tire. After large-scene environment modeling using the multi-line LiDAR sensor 5, an optimal path is planned from starting point A and navigated to the target point B. As shown in Figure 6, the multi-line LiDAR sensor 5 acquires r and θ from the actual path and the planned path. When both r and θ are 0, the turning angles of tires M1 and M4 are adjusted based on the deviation between r and θ, where the deviation e(t) = r + θ. According to classical PID control theory, the turning angle δ of the virtual tire can be obtained as follows:

[0060] Furthermore, Figure 7 schematically illustrates the principle of displacement tracking angle calculation for a mobile welding robot according to an example embodiment of this application. Based on the virtual tire angle δ obtained from equation (1), as shown in Figure 7, the real-time angle δ1 of the actual tire M1 and the real-time angle δ2 of the actual tire M4 can be obtained synchronously, thereby achieving high-precision navigation tracking. The corresponding angle calculation formula is as follows:

[0061] Where D is the wheelbase between the front and rear wheels, and d is the wheelbase between the left and right wheels. Equations (2) and (3) show the conventional method for solving the tire steering angle of the Ackermann chassis.

[0062] The accuracy of the mobile chassis 8 in navigating and positioning to the target point B is tested experimentally, and the deviation threshold range 14 of navigation and positioning can be determined accordingly. Then, based on the deviation threshold range 14 and the field of view of the large field-of-view structured light sensor 6, the threshold area range 13 for the placement of the large box-shaped steel structure component 1 is determined to ensure that the deviation threshold range 14 for the mobile chassis 8 in navigating to the target point B is within the threshold range 14. In this way, the large box-shaped steel structure component 1 can be placed arbitrarily within the threshold area range 13, and it will still be within the field of view of the large field-of-view structured light sensor 6.

[0063] Step S2: A single line structured light beam is emitted to scan the surface of the target workpiece.

[0064] As shown in Figure 3, within the deviation threshold range of the target point position B, the large field-of-view structured light sensor 6 is triggered once, and the effective point cloud data of the light illuminating the outer surface of the large box steel structure component 1 within the field of view is acquired.

[0065] Following step S2, the preferred embodiment of this application adjusts the attitude of the mobile robot through the following steps: linear fitting is performed on the point cloud data, and a first straight line is selected from the fitted lines; the first straight line is translated along the Z-axis of the line structured light plane coordinate system to obtain a second straight line intersecting the X-axis of the line structured light plane coordinate system, wherein the optical axis corresponding to the line structured light is the Z-axis, and the axis perpendicular to the Z-axis is the X-axis; the angle between the second straight line and the X-axis of the line structured light plane coordinate system is obtained as the body rotation angle; and the mobile robot is controlled to rotate in place around the body axis by the body rotation angle to complete the attitude adjustment. As shown in Figures 8 and 9, the line structured light plane coordinate system is an XOZ coordinate system, with the line structured light emission point O as the origin, the optical axis of the line structured light as the Z-axis, and the X-axis perpendicular to the Z-axis. It is easy to see that the X-axis is equivalent to the edge line of the mobile robot. The line structured light emitted by the mobile robot in its initial posture cannot be aligned with the target workpiece. However, after the robot rotates around its axis by the specified rotation angle, the X-axis of the robot's edge line becomes parallel to the target workpiece, thus enabling the emitted line structured light to be aligned with the target workpiece.

[0066] When this posture adjustment scheme is applied to the above example, it may specifically include the following steps S3, S4 and S5.

[0067] Step S3: Point cloud data processing.

[0068] The point cloud data undergoes secondary processing. For example, the point cloud is first classified using the density clustering (DBSCN) algorithm, and then a least-squares method is used to fit a straight line to each class of point clouds. Figure 8 schematically illustrates a point cloud straight line fitting diagram according to an embodiment of this application. As shown in Figure 8, the point cloud set {(X)} with the largest number of point clouds is selected as the straight line fg. c Z c ),(X c+1 Z c+1 ),……(X d Z d Furthermore, the slope k of the straight line can also be calculated. The straight line fg is the first straight line in the preferred embodiment of this application.

[0069] Step S4: Calculate the vehicle body rotation angle.

[0070] Figure 9 schematically illustrates a mobile chassis attitude adjustment diagram according to an example of an embodiment of this application. As shown in Figure 8, after triggering a single structured light scan of the outer surface of the large box-shaped steel structure 1 and performing point cloud data processing, a straight line fg is obtained in the coordinate system XOZ of the large field-of-view structured light sensor 6. The straight line fg is translated along the Z-axis to intersect the X-axis at point f', resulting in the straight line f′g′. This straight line f′g′ is the second straight line in the preferred embodiment of this application. Based on the slope k, the angle between the straight line f′g′ in Figure 8 and the X-axis of the large field-of-view structured light sensor 6 is calculated as: θ = tan -1 k (4)

[0071] Step S5: Adjust vehicle body posture.

[0072] In Figure 8, the angle θ between the straight line f′g′ and the X-axis of the large field-of-view structured light sensor 6 is the angle by which the mobile chassis 8 needs to rotate in place around the vehicle's axis. If θ > 0, the mobile chassis 8 rotates clockwise by θ° around the vehicle's axis. If θ < 0, the mobile chassis 8 rotates counterclockwise by θ° around the vehicle's axis, thus adjusting the attitude of the mobile chassis 8 and obtaining position C. As shown in Figure 9, after rotating θ°, the straight line f′g′ obtained under the new attitude is parallel to the edge line of the mobile robot and the target workpiece.

[0073] After the attitude adjustment is completed in step S5, the preferred embodiment of this application adjusts the lateral position of the mobile robot relative to the target workpiece through the following steps to achieve precise positioning: determining the transverse straight line intersecting the line structured light plane with the outer surface of the target workpiece; and controlling the mobile robot to move along the direction of the transverse straight line according to the current position of the mobile robot and the current position change of the line structured light relative to the transverse straight line, so that the mobile robot reaches the target point position.

[0074] When this precise positioning scheme is applied to the above example, it may specifically include the following steps S6, S7 and S8.

[0075] Step S6: Determine the transverse straight line that intersects the line structured light plane with the outer surface of the target workpiece.

[0076] After adjusting the vehicle posture of the mobile chassis 8, the large field-of-view line structured light sensor 6 is continuously triggered to scan the outer surface of the large box-shaped steel structure component 1. Figure 10 schematically shows a diagram of the robot's lateral movement according to an embodiment of this application. The large field-of-view line structured light sensor 6 is set to use the XOZ coordinate system, i.e., the line structured light plane coordinate system mentioned above. Through this coordinate system, the transverse straight line intersecting the outer surface of the large box-shaped steel structure component 1 is ab, and the midpoint of ab is e.

[0077] Step S7, precise positioning implementation.

[0078] After determining the transverse line where the line structured light plane intersects the outer surface of the target workpiece in step S6, the current position of the mobile robot and the positional change of the current line structured light relative to the transverse line are further determined to control the mobile robot to move along the direction of the transverse line. In a preferred embodiment of this application, controlling the mobile robot to move along the direction of the transverse line may include the following first movement control step and second movement control step.

[0079] In the first movement control step, if the line structured light emitted by the mobile robot at its current position after the attitude adjustment covers the first endpoint of the cross-section line but not the second endpoint of the cross-section line, the mobile robot is controlled to move along a first direction until the corresponding line structured light covers the second endpoint of the cross-section line, and then the mobile robot is controlled to stop. The first direction is the direction from the first endpoint to the second endpoint, and the second direction is opposite to the first direction.

[0080] The second movement control step involves controlling the mobile robot to turn and move in the second direction until the optical axis point of the corresponding line structured light coincides with the midpoint of the transverse straight line, at which point the mobile robot stops. The position of the mobile robot at the point of coincidence is the target point position.

[0081] Furthermore, in other preferred embodiments, the following third and fourth movement control steps may also be included.

[0082] The third movement control step involves controlling the mobile robot to move along the first direction when the line structured light emitted by the mobile robot at its current position after the attitude adjustment cannot cover any endpoint of the transverse straight line and does not generate point cloud data. This continues until the corresponding line structured light covers the first endpoint, at which point the first movement control step is executed.

[0083] The fourth movement control step involves controlling the mobile robot to move along the second direction when the line structured light emitted by the mobile robot at its current position after the attitude adjustment cannot cover any endpoint of the transverse straight line and can generate point cloud data. The first movement control step is then executed when the corresponding line structured light covers the first endpoint.

[0084] In addition, during the execution of any of the above-mentioned movement control steps, the motion positioning control method of the preferred embodiment of this application may further include: determining the length of the cross-section line as the width of the target workpiece based on the moving distance of the mobile robot along the direction of the cross-section line and the distance between the endpoint of the cross-section line and the optical axis point of the current line structured light on the cross-section line; and determining the model of the target workpiece based on the width of the target workpiece.

[0085] Returning to the example of step S7, we will now describe the control scenarios corresponding to the four motion control steps described above. In step S7, as we know from step S5, after the moving chassis 8 adjusts the vehicle's posture and obtains position C, the large field-of-view structured light sensor 6 is continuously triggered. The continuously emitted current line structured light (light ray cd) will exhibit the following situations:

[0086] (1) Corresponding to the first movement control step above, as shown in Figure 11(1), if the position C of the moving chassis 8 is on the ae side, point c is to the left of point a, and a is to the left of the origin O, the large field-of-view structured light sensor 6 is turned off, and the moving chassis 8 is in a stationary state. The large field-of-view structured light sensor 6 is triggered once, and the distance of point a from the line segment ao in the large field-of-view structured light sensor 6 is recorded. The large field-of-view structured light sensor 6 is triggered continuously, and the moving chassis 8 is controlled to move along the line segment ao in the large field-of-view structured light sensor 6. The direction is to move in a straight line. When point d in the light ray cd emitted by the large field-of-view structured light sensor 6 is to the right of point b, and point b is to the right of the origin O, the moving chassis 8 stops and is in position D. The hub motor encoder of the moving chassis 8 records the moving distance of CD. The large field-of-view structured light sensor 6 is turned off, the moving chassis 8 is in a stationary state, the large field-of-view structured light sensor 6 is triggered once, and the distance of point b to line segment ob in the large field-of-view structured light sensor 6 is recorded. As shown in Figure 11(1), the width dimension ab=ao+CD+ob of the large box steel structure component 1 can be obtained. The model of the large box steel structure component 1 can be confirmed according to this width dimension. Finally, the moving chassis 8 is controlled to move along the direction of the large box steel structure component 1. The direction of movement is a straight line from position D to position E, where position E is the midpoint of line segment ab.

[0087] It is easy to see that, corresponding to the first movement control step, points a and b are the first and second endpoints of the horizontal line, respectively, and the first direction is... The direction, the second direction is Direction. It should be noted that the endpoints and movement directions of Figures 11(1)-11(4) are defined similarly, and will not be repeated below.

[0088] (2) Corresponding to the second movement control step, if the position C of the moving chassis 8 is on the ae side, point c is to the left of point a, point a is to the right of the origin O, and point d is to the right of the origin a. As shown in Figure 11(2), based on the width dimension calculated in (1) above, the width dimension ab = CD - oa + ob of the large box steel structure component 1 can be obtained similarly. Based on this width dimension, the model of the large box steel structure component 1 is confirmed. Finally, the moving chassis 8 is controlled along... The direction is a straight line from position D to position E, and position E is the midpoint of line segment ab. DE = ab / 2 - ob.

[0089] (3) Corresponding to the second movement control step, if the position C of the moving chassis 8 is on the ae side, point d is to the left of point a. As shown in Figure 11(3), the large field-of-view structured light sensor 6 is continuously triggered, and the moving chassis 8 is controlled to move along the ae side. The direction is straight-line movement. When point d in the light ray cd emitted by the large field-of-view structured light sensor 6 is to the right of point a, the moving chassis 8 stops, and the state is consistent with that in Figure 11(2). Based on the width dimension calculated in (2) above, the width dimension ab of the large box steel structure component 1 can be obtained by analogy: ab = CD - oa + ob. Based on this width dimension, the model of the large box steel structure component 1 can be confirmed. Finally, control the moving chassis 8 to move along the direction of the structured light sensor 6. The direction is a straight line from position D to position E, and position E is the midpoint of line segment ab. DE = ab / 2 - ob.

[0090] (4) Corresponding to the fourth movement control step, if the position C of the moving chassis 8 is on the ae side, point c is to the right of point a. As shown in Figure 11(4), the large field-of-view structured light sensor 6 is continuously triggered, and the moving chassis 8 is controlled to move along the ae side. The direction is straight-line movement. When point c in the light ray cd emitted by the large field-of-view structured light sensor 6 is to the left of point a, the moving chassis 8 stops. At this time, the state is consistent with that in Figure 11(1). Based on the width dimension calculated in (1) above, the width dimension ab=ao+CD+ob of the large box steel structure component 1 can be obtained by analogy. The model of the large box steel structure component 1 can be confirmed based on the width dimension. Finally, control the moving chassis 8 to move along the direction of the light ray cd. The direction is a straight line from position D to position E, and position E is the midpoint of line segment ab. DE = ab / 2 - ob.

[0091] (5) The case where point c coincides with point a, origin O coincides with point a, and point d coincides with point a is not considered because the sensor accuracy cannot achieve such an ideal state.

[0092] (6) Relative to the endpoints and movement directions of Figures 11(1)-11(4), Figures 12(1)-12(4) are for the opposite movement directions. That is, in Figures 12(1)-12(4), corresponding to the first movement control step, points b and a are the first and second endpoints of the transverse straight line, respectively, and the first direction is... The direction, the second direction is direction.

[0093] Thus, corresponding to the first motion control step, as shown in Figure 12(1), if the position C of the moving chassis 8 is on the be side, point d is to the right of point b, and b is to the right of the origin O, then the large field-of-view structured light sensor 6 is turned off, and the moving chassis 8 is in a stationary state. The large field-of-view structured light sensor 6 is triggered once, and the distance of point b to line segment bo in the large field-of-view structured light sensor 6 is recorded. The large field-of-view structured light sensor 6 is triggered continuously, and the moving chassis 8 is controlled to move along the line segment bo. The direction is to move in a straight line. When point c in the light ray cd emitted by the large field-of-view structured light sensor 6 is to the left of point a, and point a is to the left of the origin O, the moving chassis 8 stops and is in position D. The hub motor encoder of the moving chassis 8 records the moving distance of CD. The large field-of-view structured light sensor 6 is turned off, the moving chassis 8 is in a stationary state, the large field-of-view structured light sensor 6 is triggered once, and the distance of point a in the line segment oa in the large field-of-view structured light sensor 6 is recorded. From Figure 12(1), the width dimension ab=oa+CD+ob of the large box steel structure component 1 can be obtained, and the model of the large box steel structure component 1 can be confirmed according to this width dimension. Finally, the moving chassis 8 is controlled to move along the direction of the large box steel structure component 1. The direction is a straight line from position D to position E, and position E is the midpoint of line segment ab. DE = ab / 2 - oa.

[0094] (7) Corresponding to the second movement control step, as shown in Figure 12(2), if the position C of the moving chassis 8 is on the be side, point d is to the right of point b, b is to the left of the origin O, and c is to the left of point b. Based on the width dimension calculation in (6) above, the width dimension ab = CD + oa - ob of the large box steel structure component 1 can be obtained similarly. Based on this width dimension, the model of the large box steel structure component 1 can be confirmed. Finally, control the moving chassis 8 along The direction is a straight line from position D to position E, and position E is the midpoint of line segment ab. DE = ab / 2 - oa.

[0095] (8) Corresponding to the third movement control step, as shown in Figure 12(3), if the position C of the moving chassis 8 is on the be side, and point c is to the right of point b, the large field-of-view structured light sensor 6 is continuously triggered, and the moving chassis 8 is controlled to move along the line. The direction is straight-line movement. When point c in the light ray cd emitted by the large field-of-view structured light sensor 6 is to the left of point b, the moving chassis 8 stops, and the state is consistent with Figure 12(2). According to the width dimension calculated in (7) above, the width dimension ab = CD + oa - ob of the large box steel structure component 1 can be obtained. According to the width dimension, the model of the large box steel structure component 1 can be confirmed. Finally, control the moving chassis 8 to move along the direction. The direction is a straight line from position D to position E, and position E is the midpoint of line segment ab. DE = ab / 2 - oa.

[0096] (9) Corresponding to the fourth movement control step, as shown in Figure 12(4), if the position C of the moving chassis 8 is on the be side, and point d is to the left of point b. As shown in Figure 12(4), the large field-of-view structured light sensor 6 is continuously triggered, and the moving chassis 8 is controlled to move along the line. The direction is to move in a straight line. When point d in the light ray cd emitted by the large field-of-view structured light sensor 6 is to the right of point b, the moving chassis 8 stops. At this time, the state is consistent with that in Figure 12(1). According to the width dimension calculated in (6) above, the width dimension ab = oa + CD + ob of the large box steel structure component 1 can be obtained. According to the width dimension, the model of the large box steel structure component 1 can be confirmed. Finally, control the moving chassis (8) to move along the direction of the structured light sensor 6. The direction is a straight line from position D to position E, and position E is the midpoint of line segment ab. DE = ab / 2 - oa.

[0097] (10) The case where point c and point b, origin O and point b, and point d and point b just coincide is not considered because the sensor accuracy cannot achieve such an ideal state.

[0098] Step S8: Control the mobile robot to work.

[0099] According to steps S5 and S7, as shown in Figures 11(1)-12(4), the current posture of the mobile chassis 8 is such that its perpendicular bisector is perpendicular to the plane containing the ab line of the large box-shaped steel structure 1, and the position of the perpendicular bisector of the mobile chassis 8 is at the midpoint e of the ab line. At this time, the expected target point B has been reached. The large field-of-view structured light sensor 6 is triggered once to confirm the distance between the mobile chassis 8 and the large box-shaped steel structure 1, and the mobile chassis 8 is adjusted to move forward or backward to the preset position to perform the work.

[0100] Therefore, the example of this application embodiment completes the pose adjustment of the mobile chassis 8 through steps S1-S8, and realizes the model identification of the large box-shaped steel structure component 1 and the secondary precise positioning of the vehicle body, solving the problem of welding work that cannot be carried out according to the preset robot trajectory due to poor navigation accuracy, inaccurate positioning, and workpiece placement position deviation. Specifically, the example of this application embodiment includes at least the following innovative technical solutions:

[0101] 1. A proposal is made to create a virtual tire and simultaneously solve the actual tire turning angle through the virtual tire, thereby realizing PID closed-loop control for path tracking of mobile robots.

[0102] 2. Point cloud data is acquired by scanning the workpiece surface with line structured light. Interference point clouds are filtered using methods such as density clustering, and straight lines are fitted using the least squares method to obtain straight line point clouds. Then, the angle θ between the vehicle body and the horizontal plane of the workpiece is calculated, and the vehicle body is controlled to rotate around the predetermined angle θ to achieve attitude adjustment.

[0103] 3. The workpiece surface is continuously scanned using line structured light, and the mobile robot is controlled to move in a straight line along the horizontal direction of the workpiece surface. Abrupt changes in point cloud data are used to confirm that the mobile robot has reached the horizontal end position of the workpiece. Then, the robot statically photographs the point cloud at both ends of the workpiece to obtain the coordinate positions within the sensor, and calculates the distance to the encoder of the mobile robot. In this way, the distance between the two ends of the workpiece's horizontal plane can be calculated, and the robot can be controlled to move within the threshold range of the workpiece's horizontal X-axis. The abrupt change in point cloud data, as explained above, mainly refers to the process of point cloud appearing or disappearing from view. For example, within the field of view of the line structured light, when it hits the workpiece, a point cloud is generated; conversely, if it does not hit the workpiece or is outside the field of view, the point cloud disappears, exhibiting a point cloud abrupt change phenomenon.

[0104] 4. Scan the workpiece with line structured light to confirm the distance between the workpiece and the mobile robot in the Z-axis direction, and control the positioning of the mobile robot in the Z-axis direction.

[0105] Therefore, in the application scenario of the mobile welding robot system in this example, the solution of the embodiment of this application can solve the problems of low navigation accuracy and inability to converge the target position in traditional navigation; it can realize the identification of the model of large box steel structure and the adjustment of the vehicle body posture to achieve secondary fine positioning, and solve the problem that the workpiece placement position is offset and cannot be welded according to the preset robot trajectory; it can also solve the problems of traditional workpiece identification and positioning schemes, which require pre-modeling of large workpieces, using multiple cameras and multiple positions to take pictures of workpieces, filtering and stitching a large amount of workpiece point cloud data, and then registering it with the model point cloud, resulting in high cost, large amount of point cloud data, complex algorithm, low stability, and low registration success rate.

[0106] It should be noted that, in addition to the four-wheeled mobile welding robot shown in the above example, the solutions of this application embodiment can also be applied to two-wheeled mobile robots, as well as mobile robots that can perform other tasks (such as painting walls, laying bricks, carrying materials, etc.).

[0107] Furthermore, the line structured light sensor in the above example is not limited to the type of line structured light. Other sensors capable of acquiring point cloud coordinates (x, z) values ​​of straight lines or planar point clouds can be used as substitutes, and all should fall within the protection scope of the embodiments of this application.

[0108] In summary, through the above examples and referring back to Figure 1, the motion positioning control method for mobile robots in this application essentially provides a scheme of "coarse positioning of target point + robot posture adjustment + fine positioning of target point," which can be specifically described as follows:

[0109] First, a virtual tire for the mobile chassis is created. The environment is scanned using 3D vision sensors such as LiDAR sensors. The path is planned and the steering angle of the Ackerman chassis tire is solved simultaneously. The mobile robot path tracking PID closed-loop control is then used to achieve coarse positioning of the target point.

[0110] Second, at the coarse positioning position, line structured light is used to scan the surface of the workpiece, noise is filtered by point cloud processing algorithm, and a straight line is fitted by least squares method to obtain the straight line vector of the point cloud on the workpiece surface. The angle θ between the X-axis vector of the line structured light coordinate axis and the straight line vector is solved, which is the body rotation attitude angle, to realize the body attitude adjustment.

[0111] Third, after adjusting the vehicle's posture, the workpiece surface is continuously scanned using line structured light, and the mobile chassis is controlled to move laterally in a straight line along the workpiece surface. By analyzing point cloud data abrupt changes, it is determined whether the mobile chassis has reached the end position of the workpiece, and it stops moving at the end position. Static scanning of the point clouds at both ends of the workpiece is performed to obtain the coordinates of both ends within the sensors, and the distance traveled by the mobile chassis when moving to both ends is recorded simultaneously. The distance dimensions at both ends of the workpiece are calculated comprehensively and matched with the workpiece model from the process library. Additionally, the relative positional relationship between the mobile chassis and the workpiece in the X-axis and Z-axis coordinate systems is determined, and the robot is controlled to move to the preset target point position, achieving secondary precision positioning of the mobile chassis.

[0112] Furthermore, based on the scheme of "coarse target point positioning + robot posture adjustment + fine target point positioning", the embodiments of this application have at least the following advantages:

[0113] First, this application proposes a scheme for implementing PID closed-loop control of navigation path based on virtual tire path tracking control strategy, which solves the problems of low accuracy and inability to converge target position in traditional navigation.

[0114] Secondly, this application proposes a scheme for identifying the model of large workpieces based on a visual sensor, and can develop a corresponding mobile robot motion secondary fine positioning control strategy, which can realize the model identification of the target workpiece and perform secondary fine positioning based on the vehicle body posture adjustment, thus solving the problem that the robot cannot work according to the preset trajectory due to poor navigation accuracy, inaccurate positioning, workpiece placement position deviation and other reasons.

[0115] Third, compared to traditional workpiece identification and positioning schemes, the embodiments of this application do not require pre-modeling of large workpieces, nor do they require using multiple cameras and multiple camera positions to capture workpieces and then filter, stitch, and register the large amount of workpiece point cloud data. Compared to the problems of high cost, large amount of point cloud data, complex algorithms, low stability, and low registration success rate of traditional workpiece identification and positioning schemes, the solutions of the embodiments of this application have lower cost, smaller amount of point cloud data, simpler algorithms, higher stability, and higher registration success rate.

[0116] Figure 13 schematically illustrates a structural block diagram of a motion positioning control device for a mobile robot according to an embodiment of this application. As shown in Figure 13, the motion positioning control device may include: a memory configured to store instructions; and a processor configured to retrieve instructions from the memory and, when executing the instructions, to implement the aforementioned motion positioning control method for the mobile robot.

[0117] The motion positioning control device can be a controller integrated on the mobile robot or a remote controller.

[0118] For more details on the implementation and effects of the motion positioning control device, please refer to the motion positioning control method of the mobile robot in the above embodiments, which will not be repeated here.

[0119] Figure 14 schematically illustrates a structural block diagram of a motion positioning control system for a mobile robot according to an embodiment of this application. The system includes: a sensing component 100, which includes at least a line structured light sensor mounted on the mobile robot for emitting line structured light to scan the surface of the target workpiece to obtain corresponding point cloud data; and the aforementioned motion positioning control device 200 for controlling the mobile robot to move to the target point position based on the point cloud data.

[0120] The motion positioning control system is, for example, the mobile welding robot system shown in Figure 2. The sensing components 100 include, for example, a weld seam tracking sensor 3, a multi-line lidar sensor 5, a large field-of-view structured light sensor 6, and an ultrasonic sensor 7. The motion positioning control device 200 can be, for example, a vehicle control unit (VCU) on a mobile chassis 8, or a remote controller. The working components on the mobile robot include, for example, a welding robotic arm and welding torch 4, a welding machine and welding system 9, etc. Furthermore, the motion positioning control system may also include, for example, a power assembly consisting of a rope winch mechanism 10, a power supply line 11, and a power column 12.

[0121] This application also provides a mobile robot, including a motion positioning control system for any of the mobile robots described above. The mobile robot can be, for example, the mobile welding robot shown in Figure 2, or a mobile robot that performs tasks such as painting walls, laying bricks, and transporting materials.

[0122] This application also provides a machine-readable storage medium storing instructions that cause a machine to execute the motion positioning control method for the mobile robot described above.

[0123] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0124] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0127] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0128] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0129] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0130] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0131] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A motion positioning control method for a mobile robot, characterized in that, include: When the mobile robot reaches the target point position within the deviation threshold range, the mobile robot is adjusted in attitude based on the point cloud data obtained by the mobile robot emitting line structured light to the target workpiece, so that the emitted line structured light is aligned with the target workpiece. as well as After the posture adjustment, the mobile robot is controlled to move in a straight line parallel to the target workpiece and continuously emit line structured light. Based on the position change of the continuously emitted line structured light relative to the target workpiece, the lateral position of the mobile robot relative to the target workpiece is adjusted so that the mobile robot reaches the target point.

2. The motion positioning control method according to claim 1, characterized in that, The deviation threshold range is determined such that when the target workpiece is placed within the specified threshold area, it is within the field of view corresponding to the line structured light.

3. The motion positioning control method according to claim 1, characterized in that, During the process of the mobile robot reaching the target point location within the deviation threshold range, the motion positioning control method further includes: Based on the deviation factor between the actual path and the planned path of the mobile robot, the rotation angle of the proposed virtual wheel is determined, wherein the virtual wheel is located at the middle position of a pair of actual walking wheels of the mobile robot. The rotation angle of the actual walking wheels of the mobile robot is calculated based on the determined rotation angle of the virtual wheels; and Based on the actual turning angle of the walking wheels, path tracking is performed to control the mobile robot to reach the target point within the deviation threshold range.

4. The motion positioning control method according to claim 1, characterized in that, The posture adjustment of the mobile robot includes: Perform linear fitting on the point cloud data, and select the first straight line from the fitted lines; The first straight line is translated along the Z-axis of the line structured light plane coordinate system to obtain a second straight line that intersects the X-axis of the line structured light plane coordinate system, wherein the optical axis corresponding to the line structured light is the Z-axis, and the axis perpendicular to the Z-axis is the X-axis; Obtain the angle between the second straight line and the X-axis of the line structured light plane coordinate system, as the fuselage rotation angle; and The mobile robot is controlled to rotate around its axis in place by the rotation angle of its body to complete the attitude adjustment.

5. The motion positioning control method according to claim 1, characterized in that, Adjusting the lateral position of the mobile robot relative to the target workpiece includes: Determine the transverse straight line intersecting the line structured light plane with the outer surface of the target workpiece; and Based on the current position of the mobile robot and the position change of the current line structured light relative to the transverse straight line, the mobile robot is controlled to move along the direction of the transverse straight line so that the mobile robot reaches the target point.

6. The motion positioning control method according to claim 5, characterized in that, The motion positioning control method further includes: The length of the transverse line is determined based on the distance the mobile robot travels along the transverse line and the distance between the endpoint of the transverse line and the optical axis point of the current line structured light on the transverse line, and is used as the width of the target workpiece; and The model of the target workpiece is determined based on its width.

7. The motion positioning control method according to claim 5, characterized in that, The control of the mobile robot to move along the direction of the transverse straight line includes: In the first motion control step, if the line structured light emitted by the mobile robot at its current position after the attitude adjustment covers the first endpoint of the transverse straight line but not the second endpoint, the mobile robot is controlled to move along a first direction until the corresponding line structured light covers the second endpoint of the transverse straight line, at which point the mobile robot stops. The first direction is the direction from the first endpoint to the second endpoint, and the second direction is opposite to the first direction. The second movement control step involves controlling the mobile robot to turn and move in the second direction until the optical axis point of the corresponding line structured light coincides with the midpoint of the transverse straight line, at which point the mobile robot stops, wherein the position of the mobile robot at the point of coincidence is the target point position.

8. The motion positioning control method according to claim 7, characterized in that, The control of the mobile robot to move along the direction of the transverse straight line also includes: The third movement control step involves controlling the mobile robot to move along the first direction when the line structured light emitted from its current position after the attitude adjustment cannot cover any endpoint of the transverse straight line and does not generate point cloud data. This continues until the corresponding line structured light covers the first endpoint, at which point the first movement control step is executed. The fourth movement control step involves controlling the mobile robot to move along the second direction when the line structured light emitted by the mobile robot at its current position after the attitude adjustment cannot cover any endpoint of the transverse straight line and can generate point cloud data. The first movement control step is then executed when the corresponding line structured light covers the first endpoint.

9. A motion positioning control device for a mobile robot, characterized in that, include: The memory is configured to store instructions; as well as The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the motion positioning control method according to any one of claims 1 to 8.

10. A motion positioning control system for a mobile robot, characterized in that, include: The sensing component includes at least a line structured light sensor mounted on the mobile robot for emitting line structured light to scan the surface of the target workpiece to obtain corresponding point cloud data. as well as The motion positioning control device according to claim 9 is used to control the mobile robot to move to the target point position based on the point cloud data.

11. The motion positioning control system according to claim 10, characterized in that, The sensing components also include a multi-line lidar sensor and / or an ultrasonic sensor mounted on the mobile robot, wherein the multi-line lidar sensor is used to assist the mobile robot in path planning, obstacle avoidance, or positioning, and the ultrasonic sensor is used to assist the mobile robot in obstacle avoidance.

12. A mobile robot, characterized in that, Includes the motion positioning control system as described in claim 10 or 11.

13. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the motion positioning control method according to any one of claims 1 to 8.

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