Intelligent monitoring control system and method for operation of cleaning and caring robot

Abstract

The invention relates to the technical field of robots, in particular to a cleaning robot operation intelligent monitoring control system and method, and the system comprises a map building and positioning module, a path planning module, an obstacle detection module, an obstacle analysis module, a static obstacle avoidance module, a dynamic obstacle avoidance module, a path modification module, and a management database. The system constructs an environment map by acquiring an environment image around the cleaning robot, plans an optimal advancing path of the cleaning robot according to each fixed task point position of a cleaning task, judges whether an object at each scanning angle is an obstacle according to each time point position coordinate of the object at each scanning angle, and classifies each obstacle. According to the method and the system, the cleaning robot is used for carrying out obstacle avoidance on various types of obstacles, the obstacles are updated into an environment map according to the obstacle avoidance times of the cleaning robot on the static obstacles, and the optimal advancing path of the cleaning robot is periodically updated, so that tasks can be smoothly completed under various conditions without being obstructed.

Description

Technical Field

[0001] The present invention relates to the technical field of robots, and more specifically, it is an intelligent monitoring and control system and method for the operation of a washing and care robot. Background Technique

[0002] With the progress of technology, people's demand for the application of robots is increasing continuously, especially in some scenarios that require efficient and precise operations, such as home services, industrial production, etc. In these scenarios, robots face complex and changeable environments, and how to move safely and accurately in them and complete tasks has become a key issue.

[0003] For example, the existing Chinese patent with the publication number CN106200516A discloses a control system for a household intelligent humanoid service robot. The system includes a mobile terminal and a cloud server; the mobile terminal includes a central processing unit and a human-computer interaction interface, an alarm module, a household appliance control system, a voice recognition module, a detection system, and an indoor trajectory recognition module that are connected to the central processing unit. The detection system includes an air quality detection unit, a temperature detection unit, and a lighting detection unit. Through the ingenious combination of the mobile terminal and the cloud server, the present invention enables the service robot to have perfect service functions, intelligently and real-time adjust the air quality, lighting, and temperature in the room, reduce the input of labor, improve a certain quality of life, and the entire system has a simple structure and is suitable for popularization and use.

[0004] The existing Chinese patent with the application number CN103984315A discloses a household multifunctional intelligent robot. This solution identifies and locates the environment where the robot is located through a positioning module, and controls the movement of the robot through a driving module; the data acquisition system includes a vision module, a voice module, and a data collection module. The vision module includes a camera device and acquires video images through the camera device; the voice module includes a microphone that acquires audio information; the communication system includes a wireless communication module to achieve remote communication of the robot; the processing and control system includes a processing module and a control module. The processing module receives the data in the multiple functional subsystems in real time, processes it according to a predetermined algorithm, and based on the processing result, the control module issues control instructions to each functional subsystem to control the actions of the robot.

[0005] Although the above-mentioned existing technical solutions also solve some problems in the intelligent monitoring and control of household robots such as cleaning, nursing, or maintenance during operation, it is crucial to ensure the precise and accurate movement and positioning of the robot in scenarios such as homes. For example, the subsequent route adjustment based on dynamic planning of obstacles is not comprehensive enough, which may lead to problems such as unreasonable route planning after obstacle avoidance and inability to flexibly adjust in a timely manner according to newly emerging obstacles in some complex and changeable scenarios, thereby affecting work efficiency and safety. Summary of the Invention

[0006] To overcome the deficiencies in the background technology, the embodiments of the present invention provide an intelligent monitoring and control system and method for the operation of a washing and care robot, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] The object of the present invention can be achieved through the following technical solutions: The present invention provides an intelligent monitoring and control system for the operation of a washing and care robot, including: a map construction and positioning module, configured to obtain the environmental image around the washing and care robot in real time through a camera, thereby constructing an environmental map and marking each fixed task point, and at the same time positioning the position of the robot in the environmental map.

[0008] A path planning module, configured to plan the optimal travel path of the washing and care robot according to the positions of each fixed task point of the washing and care task.

[0009] An obstacle detection module, configured to emit a laser beam to scan the surrounding area through a laser emitter built in the washing and care robot to obtain the position coordinates of objects at each time point at each scanning angle.

[0010] An obstacle analysis module, configured to determine whether the objects at each scanning angle are obstacles according to the position coordinates of objects at each time point at each scanning angle and classify each obstacle.

[0011] A static obstacle avoidance module, configured to obtain the distances from the washing and care robot to each static obstacle, and then control the washing and care robot to turn and avoid obstacles based on this.

[0012] A dynamic obstacle avoidance module, configured to generate the movement trajectory of a specified dynamic obstacle, obtain the moving speeds of each segment of the movement trajectory of the specified dynamic obstacle from it, and then judge the movement regularity of the specified dynamic obstacle and avoid obstacles.

[0013] A path modification module, configured to update the obstacles into the environmental map according to the number of obstacle avoidance times of the washing and care robot for each static obstacle, and periodically update the optimal travel path of the washing and care robot.

[0014] A management database, configured to store each washing and care task and the corresponding images of each task point.

[0015] Preferably, the present invention provides a path planning and obstacle avoidance navigation method for a washing and care robot. The specific steps of this method are as follows: S1. Map construction and positioning: The environmental image around the washing and care robot is obtained in real time through a camera, and based on this, an environmental map is constructed and each fixed task point is marked. At the same time, the position of the robot in the environmental map is located.

[0016] S2. Path planning: According to the positions of each fixed task point of the washing and care task, the optimal traveling path of the washing and care robot is planned.

[0017] S3. Obstacle detection: The laser emitter built in the washing and care robot emits laser beams to scan the surrounding area, and the position coordinates of objects at each time point at each scanning angle are obtained.

[0018] S4. Obstacle analysis: According to the position coordinates of objects at each time point at each scanning angle, it is judged whether the objects at each scanning angle are obstacles and the categories of each obstacle are classified.

[0019] S5. Static obstacle avoidance: The distance from the washing and care robot to each static obstacle is obtained, and based on this, the washing and care robot is controlled to turn and avoid obstacles.

[0020] S6. Dynamic obstacle avoidance: The moving trajectory of a specified dynamic obstacle is generated, and the moving speed of each segment of the moving trajectory of the specified dynamic obstacle is obtained from it. Then, the moving regularity of the specified dynamic obstacle is judged and obstacle avoidance is carried out.

[0021] S7. Path modification: According to the number of obstacle avoidance times of the washing and care robot for each static obstacle, the obstacles are updated into the environmental map, and the optimal traveling path of the washing and care robot is updated periodically.

[0022] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: First, the present invention obtains the environmental image around the washing and care robot in real time through a camera to construct an environmental map, and plans the optimal traveling path of the washing and care robot according to the positions of each fixed task point of the washing and care task, which can improve the working efficiency and accuracy of the washing and care robot, enabling it to reach the task point more quickly and accurately.

[0023] Second, the present invention judges whether the objects at each scanning angle are obstacles and classifies the categories of each obstacle according to the position coordinates of objects at each time point at each scanning angle, which can more effectively identify obstacles, help to adopt more appropriate obstacle avoidance strategies, and ensure the safe operation of the robot.

[0024] Third, the present invention obtains the distance from the washing and care robot to each static obstacle, controls the washing and care robot to turn and avoid obstacles, judges the moving regularity of the specified dynamic obstacle by generating the moving trajectory of the specified dynamic obstacle and performs obstacle avoidance, which can improve the robot's ability to cope with complex environments and ensure that it can successfully complete tasks without being hindered in various situations.

[0025] 4. The present invention updates obstacles into the environmental map according to the obstacle avoidance times of the washing and care robot for each static obstacle, and periodically updates the optimal travel path of the washing and care robot, so that the robot can continuously adapt to environmental changes and improve its adaptability and intelligence level. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0027] Figure 1 It is a module connection diagram of an intelligent monitoring and control system for the operation of a washing and care robot.

[0028] Figure 2 is Figure 1 a schematic flowchart of the method of the path planning module in

[0029] Figure 3 a flowchart of a path planning and obstacle avoidance navigation method for a washing and care robot. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0031] Please refer to Figure 1 As shown, an intelligent monitoring and control system for the operation of a washing and care robot, the navigation system includes a map construction and positioning module, a path planning module, an obstacle detection module, an obstacle analysis module, a static obstacle avoidance module, a dynamic obstacle avoidance module, a path modification module, and a management database.

[0032] The management database is connected to the map construction and positioning module, the path planning module, the obstacle analysis module, and the path modification module. The obstacle analysis module is connected to the obstacle detection module, the static obstacle avoidance module, and the dynamic obstacle avoidance module. The map construction and positioning module is connected to the path planning module.

[0033] The map construction and positioning module is used to obtain the environmental image around the washing and care robot in real time through a camera, thereby constructing an environmental map and marking each fixed task point, and at the same time positioning the position of the robot in the environmental map.

[0034] The specific analysis method of the map construction and positioning module is as follows: In the first step, when the washing and care robot moves, the camera installed on the washing and care robot is used to obtain the environmental images within the field of view in real time, obtaining continuous images of the surrounding environment. The continuous images of the surrounding environment are stitched together using image processing algorithms to construct a preliminary environmental map.

[0035] In the second step, each washing and care task and the corresponding task point images are read from the management database. The task point images of each washing and care task are recognized using image recognition technology, and the task point positions of each washing and care task are located and marked in the environmental map, denoted as each fixed task point.

[0036] In the third step, the real-time position coordinates of the washing and care robot are obtained using the built-in positioning sensor of the washing and care robot, and it is matched with the environmental map to obtain the real-time position of the washing and care robot in the environmental map; this improves the working efficiency and accuracy of the washing and care robot, reduces errors and delays caused by unfamiliar environments or inaccurate positioning, enhances the autonomy and adaptability of the washing and care robot, and enables it to better cope with different environmental and task requirements.

[0037] The path planning module is used to plan the optimal travel path of the washing and care robot according to the positions of each fixed task point of the washing and care task.

[0038] Please refer to Figure 2 As shown, the specific analysis method of the path planning module is as follows: In the first step, each washing and care task is read, and the task points of each washing and care task are sorted in sequence according to the task order of each washing and care task to obtain the position coordinates of each task point, denoted as the positions of each fixed task point. At the same time, the real-time position of the washing and care robot in the environmental map is read, denoted as the initial position of the washing and care robot.

[0039] It should be noted that in a specific embodiment, there are three washing and care tasks, namely Task A, Task B, and Task C. The task points of Task A include Location A1 and A2, the task points of Task B include Location B1, B2, and B3, and the task point of Task C is Location C1. The preset task order is Task A, Task B, and Task C. Sorting the task locations according to the preset task order gives A1, A2, B1, B2, B3, C1.

[0040] In the second step, the first washing and care task is extracted from each washing and care task, and the fixed task point corresponding to the first washing and care task is obtained, denoted as the first task point. The shortest path from the initial position of the washing and care robot to the first task point is obtained using path planning technology while avoiding the existing objects in the environmental map, denoted as the shortest path of the first task; this greatly improves the working efficiency of the washing and care robot and avoids unnecessary path detours and time waste.

[0041] In the third step, analyze the remaining washing and care tasks one by one according to the method of analyzing the shortest path of the first task, and obtain the shortest paths of the fixed task points corresponding to two adjacent washing and care tasks, which are respectively recorded as the shortest path of the second task, the shortest path of the third task... the shortest path of the task, indicating the number of washing and care tasks; it can ensure that the robot completes the tasks in the optimal order, improving the coherence and logic of task execution.

[0042] In the fourth step, connect the shortest paths of each task in sequence to obtain the complete sequential path for the washing and care robot to execute the washing and care tasks, which is recorded as the optimal travel path, and output the optimal travel path to the washing and care robot; outputting the optimal travel path makes the robot's actions more intelligent and precise, improving the overall work quality and effect.

[0043] The obstacle detection module is used to emit laser beams to scan the surrounding area through the laser emitter built in the washing and care robot, and obtain the position coordinates of objects at each time point at each scanning angle.

[0044] The specific analysis method of the obstacle detection module is as follows: in the first step, read the initial position of the washing and care robot, set a number of scanning angles for the laser according to the set angle, and obtain the distance from the washing and care robot to the object contacted by the laser beam at each scanning angle through laser scanning, which is recorded as , that is, the distance from the washing and care robot to the object at each scanning angle, indicating the number of the th scanning angle; enabling the robot to more accurately perceive the surrounding environment, timely detect potential obstacles, and improve safety and obstacle avoidance capabilities.

[0045] It should be noted that the specific analysis method for the distance from the washing and care robot to the object contacted by the laser beam at each scanning angle is as follows: according to a number of set scanning angles, emit laser beams to scan the surrounding area through the laser emitter built in the washing and care robot respectively, record the emission time of the laser beam at each scanning angle, which is recorded as , and use the receiver to receive the laser signals of the laser beams reflected by the object at each scanning angle, record the reception time of the laser beam at each scanning angle, which is recorded as , and substitute it into the formula to obtain the distance from the washing and care robot to the object contacted by the laser beam at each scanning angle , indicating the set laser propagation speed.

[0046] In the second step, record each scanning angle as , while obtaining the images of the objects contacted by the laser beams at each scanning angle of the washing and care robot, and obtaining the inclination angles of the objects contacted by the laser beams at each scanning angle through computer vision algorithms, denoted as , converting each scanning angle into a direction vector , while obtaining the coordinates of the initial position of the washing and care robot, denoted as , substituting it together with the distances from the washing and care robot to the objects at each scanning angle into the three-dimensional coordinate system to obtain the position coordinates of the objects at each scanning angle ; This allows the washing and care robot to better understand the layout of the surrounding environment, so as to move, operate and avoid collisions more intelligently, improving the accuracy and efficiency of its work.

[0047] It should be noted that the specific analysis method for converting each scanning angle into a direction vector is: reading each scanning angle and denoted as , in the three-dimensional space, the component of each scanning angle in the X direction can be expressed as , the component in the Y direction can be expressed as , the component in the Z direction can be expressed as , thus converting each scanning angle into a direction vector, denoted as .

[0048] In the third step, select time points at set interval durations, record the position coordinates of the objects at each scanning angle as the initial position coordinates of the objects at each scanning angle, and emit laser beams again to the surrounding area at each time point according to a set number of scanning angles and analyze to obtain the position coordinates of the objects at each scanning angle and each time point, denoted as , represents the number of the time point, , respectively represent the direction vectors in the X direction, Y direction, and Z direction of the th object at the th time point; enabling the washing and care robot to respond in a timely manner to the movement of objects in the environment, improving its ability to cope with dynamic environments, helping to more accurately plan action paths and operation strategies, and avoiding collisions with moving objects.

[0049] An obstacle analysis module, used to determine whether the objects at each scanning angle are obstacles according to the position coordinates of the objects at each scanning angle and each time point and classify each obstacle.

[0050] The specific analysis method of the obstacle analysis module is: in the first step, read the position coordinates of the objects at each scanning angle and each time point, and calculate the change in the position coordinates of the objects at each scanning angle, denoted as , thereby classifying the objects at each scanning angle into static objects and dynamic obstacles, and counting the classification of the objects at each scanning angle; it can better understand the nature of the objects in the environment for subsequent action planning and decision-making.

[0051] It should be noted that the specific analysis method for the change amount of the position coordinates of the objects at each scanning angle is as follows: read the position coordinates of the objects at each scanning angle at each time point, extract the position coordinates of the objects at each scanning angle in the X direction, and substitute them into the formula to obtain the change amount of the position coordinates of the objects at each scanning angle in the X direction , represents the direction vector of the th object at the th time point in the X direction. It means that the change amounts of the position coordinates of the objects at each scanning angle in the Y and Z directions are respectively analyzed in the same way, denoted as , . Through the formula the change amount of the position coordinates of the objects at each scanning angle is obtained .

[0052] It should be noted that the specific analysis method for the classification of the objects at each scanning angle is as follows: read the change amount of the position coordinates of the objects at each scanning angle. If the change amount of the position coordinates of a certain object at a scanning angle is 0, it means that there is no position change for this object at the scanning angle, and it is initially classified as a static object. If the change amount of the position coordinates of a certain object at a scanning angle is not 0, it means that there is a position change for this object at the scanning angle, and it is classified as a dynamic obstacle. Count the classification of the objects at each scanning angle.

[0053] In the second step, read the position coordinates of the objects at each scanning angle, extract the position coordinates of each static object, and mark the position coordinates of each static object on the environmental map. If the position coordinates of a certain static object overlap with the existing objects on the environmental map, it means that this static object is not an obstacle. If the position coordinates of a certain static object do not overlap with the existing objects on the environmental map, it means that this static object is an obstacle and is further classified as a static obstacle; it helps the robot or related system to more accurately plan the path, avoid unnecessarily avoiding non-obstacle static objects, and improve the action efficiency.

[0054] The static obstacle avoidance module is used to obtain the distance from the washing and care robot to each static obstacle, and then control the washing and care robot to turn and avoid obstacles based on this.

[0055] The specific analysis method of the static obstacle avoidance module is as follows: Read the distances from the washing and care robot to objects at each scanning angle, extract the distances from the washing and care robot to each static obstacle, compare the distances from the washing and care robot to each static obstacle with a preset safety distance threshold. If the distance from the washing and care robot to a certain static obstacle is less than or equal to the preset safety distance threshold, mark this static obstacle as a specified obstacle, and control the washing and care robot to turn for obstacle avoidance; ensure that the washing and care robot can timely and effectively avoid static obstacles that may cause danger during operation, and reduce the probability of accidents.

[0056] It should be noted that the specific analysis method for controlling the washing and care robot to turn for obstacle avoidance is as follows: Emit infrared laser to the specified obstacle, mark the landing point of the laser on the specified obstacle as the relative position point of the specified obstacle, and measure the straight-line distances from the relative position point of the specified obstacle to the left and right ends of the specified obstacle respectively, denoted as If then judge that the turning direction of the washing and care robot is to the right, and take as the turning distance of the washing and care robot corresponding to the turning direction On the contrary, judge that the turning direction of the washing and care robot is to the left, and take as the turning distance of the washing and care robot corresponding to the turning direction At the same time, extract the distance from the washing and care robot to the specified obstacle from the distances from the washing and care robot to each static obstacle, denoted as Substitute it into the formula to obtain the turning angle of the washing and care robot Control the washing and care robot to turn according to the turning direction and turning angle of the washing and care robot.

[0057] The dynamic obstacle avoidance module is used to generate the moving trajectory of a specified dynamic obstacle, obtain the moving speeds of each segment of the moving trajectory of the specified dynamic obstacle from it, and then judge the moving regularity of the specified dynamic obstacle and perform obstacle avoidance; it can enable the system to more flexibly respond to dynamic obstacles, timely adjust its own action strategy to avoid collisions, and improve safety.

[0058] The specific analysis method for the moving speed of each segment of the specified dynamic obstacle is as follows: The distance from the washing and care robot to each dynamic obstacle is monitored in real time. When the distance from the washing and care robot to a certain dynamic obstacle reaches the set safety distance threshold, this dynamic obstacle is recorded as the specified dynamic obstacle. The specified dynamic obstacle is video-recorded through the built-in camera of the washing and care robot to obtain the movement video of the specified dynamic obstacle. The center point of the specified dynamic obstacle is selected as the detection point, and the position points of each frame of the specified dynamic obstacle in the movement video of the specified dynamic obstacle are marked. The movement trajectory of the specified dynamic obstacle is obtained by connecting the position points of each frame of the specified dynamic obstacle video. The movement trajectory of the specified dynamic obstacle is divided into several segments at fixed time intervals, and the moving speed of each segment of the movement trajectory of the specified dynamic obstacle is obtained from them; it can comprehensively record the movement of the dynamic obstacle, help formulate a more reasonable obstacle avoidance strategy, and improve the adaptability and working efficiency of the washing and care robot in a complex dynamic environment.

[0059] It should be noted that the specific analysis method for the moving speed of each segment of the specified dynamic obstacle is as follows: The movement trajectory of the specified dynamic obstacle is divided into several segments at fixed time intervals, denoted as each segment of the movement trajectory. The moving distance of each segment of the movement trajectory of the specified dynamic obstacle is obtained. By dividing the moving distance of each segment of the movement trajectory of the specified dynamic obstacle by the fixed time, the moving speed of each segment of the movement trajectory of the specified dynamic obstacle is obtained.

[0060] The specific analysis method of the dynamic obstacle avoidance module is as follows: In the first step, read the moving speed of each segment of the specified dynamic obstacle, denoted as , indicating the number of the th segment of the movement trajectory, , and obtain the degree of fluctuation of the moving speed of the specified dynamic obstacle through the formula , , where represents the number of segments of the movement trajectory.

[0061] In the second step, compare the degree of fluctuation of the moving speed of the specified dynamic obstacle with the preset degree of fluctuation threshold of the moving speed. If the degree of fluctuation of the moving speed of the specified dynamic obstacle is less than the preset degree of fluctuation threshold of the moving speed, it means that the specified dynamic obstacle moves regularly, and control the washing and care robot to perform regular obstacle turning and avoidance; for regularly moving obstacles, a relatively simple turning and avoidance method can be adopted in a timely manner to respond efficiently and reasonably.

[0062] It should be noted that the specific analysis method for controlling the washing and care robot to perform regular obstacle avoidance by turning is as follows: Analyze the turning direction and turning angle of the washing and care robot to obtain the turning direction and turning angle for regular obstacle avoidance of the washing and care robot. At the same time, read the moving speeds of each segment of the moving trajectory of the specified dynamic obstacle, and extract the maximum moving speed of each segment of the moving trajectory of the specified dynamic obstacle, which is denoted as the maximum regular moving speed of the washing and care robot. Control the washing and care robot to move for obstacle avoidance at the maximum regular moving speed of the washing and care robot according to the turning direction and turning angle for regular obstacle avoidance of the washing and care robot.

[0063] In the third step, if the degree of fluctuation of the moving speed of the specified dynamic obstacle is greater than or equal to the preset threshold of the degree of fluctuation of the moving speed, it indicates that the specified dynamic obstacle moves irregularly. Control the washing and care robot to perform turning obstacle avoidance. And when the specified dynamic obstacle suddenly appears within the set safety distance threshold, judge the moving direction of the specified dynamic obstacle according to the moving trajectory of the specified dynamic obstacle, so as to control the washing and care robot to avoid obstacles; it can better handle complex irregular moving situations, avoid collisions, and improve safety, especially effectively ensuring the safety of the robot and the environment when the obstacle suddenly appears.

[0064] It should be noted that the specific analysis method for judging the moving direction of the specified dynamic obstacle is as follows: Select a number of time points at the set interval, denoted as each moving time point. Sequentially obtain the positions of each moving time point of the specified dynamic obstacle from the moving trajectory of the specified dynamic obstacle, and detect the distances between the positions of each moving time point of the specified dynamic obstacle and the washing and care robot respectively, denoted as , indicating the number of the th moving time point, , and obtain the moving distance of the specified dynamic obstacle relative to the washing and care robot through the formula . represents the distance between the position of the th moving time point of the specified dynamic obstacle and the washing and care robot. If the moving distance of the specified dynamic obstacle relative to the washing and care robot is positive, it indicates that the specified dynamic obstacle is moving towards the direction of the washing and care robot. If the moving distance of the specified dynamic obstacle relative to the washing and care robot is negative, it indicates that the specified dynamic obstacle is not moving towards the direction of the washing and care robot.

[0065] It should be noted that the specific analysis method for controlling the washing and care robot to avoid obstacles is as follows: If the specified dynamic obstacle does not move towards the direction of the washing and care robot, control the washing and care robot to stop moving, and wait until the distance between the specified dynamic obstacle and the washing and care robot is greater than the set safety distance threshold before continuing to move. If the specified dynamic obstacle moves towards the direction of the washing and care robot, control the washing and care robot to quickly stop moving, and at the same time read the moving speeds of each section of the moving trajectory of the specified dynamic obstacle, extract the maximum moving speed of each section of the moving trajectory of the specified dynamic obstacle, and analyze the turning direction and turning angle of the dynamic obstacle avoidance of the washing and care robot according to the method of analyzing the turning direction and turning angle of the washing and care robot, so as to control the washing and care robot to turn and avoid obstacles at the maximum moving speed of the specified dynamic obstacle.

[0066] A path modification module is used to update the obstacles into the environmental map according to the number of obstacle avoidance times of the washing and care robot for each static obstacle, and periodically update the optimal travel path of the washing and care robot.

[0067] The specific analysis method of the path modification module is as follows: In the first step, read the historical washing and care task records of the washing and care robot from the management database, count the number of obstacle avoidance times of the washing and care robot for each static obstacle, obtain the number of obstacle avoidance times of the washing and care robot for each static obstacle, and compare it with the preset obstacle avoidance times threshold. If the number of obstacle avoidance times of the washing and care robot for a certain static obstacle is greater than or equal to the preset obstacle avoidance times threshold, then mark this static obstacle as a fixed obstacle, screen out each fixed obstacle, obtain the position coordinates of each fixed obstacle and update each fixed obstacle into the environmental map based on this; it can accurately identify the static obstacles that are often encountered and mark them, making the environmental map more in line with the actual situation, providing more accurate information for subsequent path planning, and improving the robot's adaptability to the environment and work efficiency.

[0068] In the second step, divide the period according to the set duration, regularly update the environmental map according to the method of updating each fixed obstacle into the environmental map, obtain the environmental maps of each period, and then regularly re-plan the best travel path of the washing and care robot according to the method of planning the optimal travel path of the washing and care robot, and obtain the optimal travel paths of the washing and care robot in each period; adjust the robot's action strategy in a timely manner as the environment changes to ensure that it always travels along the optimized path, avoid the situation where the previous plan is no longer applicable due to environmental changes, and improve the intelligence and flexibility of the robot.

[0069] A management database is used to store each washing and care task and the corresponding images of each task point.

[0070] Please refer to Figure 3As shown, in addition, the present invention provides a path planning and obstacle avoidance navigation method for a washing and care robot. The specific steps of this method are as follows: S1. Map construction and positioning: The environmental image around the washing and care robot is obtained in real time through a camera, and based on this, an environmental map is constructed and each fixed task point is marked. At the same time, the position of the robot in the environmental map is located.

[0071] S2. Path planning: According to the positions of each fixed task point of the washing and care task, the optimal travel path of the washing and care robot is planned.

[0072] S3. Obstacle detection: A laser beam is emitted to scan the surrounding area through a laser emitter built in the washing and care robot, and the position coordinates of objects at each time point at each scanning angle are obtained.

[0073] S4. Obstacle analysis: According to the position coordinates of objects at each time point at each scanning angle, it is judged whether the objects at each scanning angle are obstacles, and the categories of each obstacle are classified.

[0074] S5. Static obstacle avoidance: The distance from the washing and care robot to each static obstacle is obtained, and based on this, the washing and care robot is controlled to turn and avoid obstacles.

[0075] S6. Dynamic obstacle avoidance: The movement trajectory of a specified dynamic obstacle is generated, and the movement speed of each segment of the movement trajectory of the specified dynamic obstacle is obtained from it. Then, the movement regularity of the specified dynamic obstacle is judged and obstacle avoidance is carried out.

[0076] S7. Path modification: According to the number of times of obstacle avoidance of the washing and care robot for each static obstacle, the obstacle is updated into the environmental map, and the optimal travel path of the washing and care robot is updated periodically.

[0077] The present invention constructs an environmental map by obtaining the environmental image around the washing and care robot, plans the optimal travel path of the washing and care robot according to the positions of each fixed task point of the washing and care task, judges whether the objects at each scanning angle are obstacles according to the position coordinates of objects at each time point at each scanning angle and classifies each obstacle, and then avoids obstacles for various types of obstacles. According to the number of times of obstacle avoidance of the washing and care robot for each static obstacle, the obstacle is updated into the environmental map, and the optimal travel path of the washing and care robot is updated periodically, ensuring that it can complete the task smoothly without being hindered in various situations.

[0078] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention, and still be covered by the protection scope of the present invention.

Claims

1. An intelligent monitoring and control system for washing robot operation, characterized in that: The system specifically includes the following modules: The map construction and positioning module is used to obtain the environmental image around the cleaning robot in real time through the camera, thereby constructing an environmental map and marking each fixed task point, and at the same time locating the position of the robot in the environmental map; The path planning module is used to plan the optimal travel path of the cleaning robot according to the positions of each fixed task point of the cleaning task; The obstacle detection module is used to scan the surrounding area with a laser beam emitted by the built-in laser transmitter of the cleaning robot to obtain the position coordinates of the object at each scanning angle and at each time point; The obstacle analysis module is used to determine whether the object at each scanning angle is an obstacle according to the position coordinates of the object at each scanning angle at each time point and to classify each obstacle; The static obstacle avoidance module is used to obtain the distance between the cleaning robot and each static obstacle, and then control the cleaning robot to turn and avoid obstacles; The dynamic obstacle avoidance module is used to generate the moving trajectory of the specified dynamic obstacle, obtain the moving speed of each segment of the moving trajectory of the specified dynamic obstacle, and then determine the moving regularity of the specified dynamic obstacle and avoid the obstacle; A path modification module is used to update the obstacles into the environment map according to the number of times the cleaning robot avoids each static obstacle, and to periodically update the optimal travel path of the cleaning robot; The management database is used to store each cleaning task and the corresponding image of each task point.

2. According to claim 1, the intelligent monitoring and control system for washing robot operation is characterized in that: The specific analysis method of the map construction and positioning module is as follows: The first step is to obtain the environmental image in the field of view in real time through the camera installed on the cleaning robot when it moves, obtain continuous images of the surrounding environment, and use the image processing algorithm to splice the continuous images of the surrounding environment to construct a preliminary environmental map; The second step is to read each cleaning task and the corresponding task point image from the management database, use image recognition technology to identify the task point image of each cleaning task, locate and mark the task point position of each cleaning task in the environment map, and record it as each fixed task point; The third step is to use the built-in positioning sensor of the cleaning robot to obtain the real-time position coordinates of the cleaning robot, match them with the environmental map, and obtain the real-time position of the cleaning robot in the environmental map.

3. The intelligent monitoring and control system for cleaning robot operation according to claim 1 is characterized in that: The specific analysis method of the path planning module is: The first step is to read each cleaning task, sort the task points of each cleaning task in turn according to the task order of each cleaning task, obtain the position coordinates of each task point, record them as the position of each fixed task point, and read the real-time position of the cleaning robot in the environment map at the same time, record them as the initial position of the cleaning robot; The second step is to extract the first cleaning task from each cleaning task, and obtain the fixed task point corresponding to the first cleaning task, which is recorded as the first task point. The path planning technology is used to avoid existing objects in the environment map to obtain the shortest path from the initial position of the cleaning robot to the first task point, which is recorded as the shortest path of the first task. The third step is to analyze the remaining cleaning tasks in turn according to the method of analyzing the shortest path of the first task, and obtain the shortest paths of the fixed task points corresponding to the two adjacent cleaning tasks, which are recorded as the shortest path of the second task, the shortest path of the third task, and so on. The shortest path to the task, Indicates the number of cleaning tasks; The fourth step is to connect the shortest paths of each task in sequence to obtain the complete sequential path for the cleaning robot to perform the cleaning task, record it as the optimal travel path, and output the optimal travel path to the cleaning robot.

4. The intelligent monitoring and control system for cleaning robot operation according to claim 3 is characterized by: The specific analysis method of the obstacle detection module is: The first step is to read the initial position of the cleaning robot, set several scanning angles for the laser according to the set angle, and obtain the distance from the cleaning robot to the object contacted by the laser beam at each scanning angle through laser scanning, which is recorded as , that is, the distance from the cleaning robot to the object at each scanning angle, Indicates The number of scanning angles, ; In the second step, each scanning angle is recorded as At the same time, the image of the object contacted by the laser beam at each scanning angle of the cleaning robot is obtained, and the inclination angle of the object contacted by the laser beam at each scanning angle is obtained through the computer vision algorithm, which is recorded as , convert each scanning angle into a direction vector , and at the same time obtain the coordinates of the initial position of the cleaning robot, recorded as , and compare it with the distance between the cleaning robot and the object at each scanning angle Substitute them into the three-dimensional coordinate system to obtain the position coordinates of the object at each scanning angle ; In the third step, a time point is selected according to the set interval duration, and the position coordinates of the object at each scanning angle are marked as the initial position coordinates of the object at each scanning angle. According to the set scanning angles, the laser beam is emitted to the surrounding area again at each time point and the position coordinates of the object at each scanning angle are obtained by analyzing the method of analyzing the initial position coordinates of the object at each scanning angle, which are recorded as , Indicates The number of the time point, , Respectively represent Scan angle object The direction vectors in the X, Y, and Z directions at a time point.

5. The intelligent monitoring and control system for cleaning robot operation according to claim 4 is characterized in that: The specific analysis method of the obstacle analysis module is: The first step is to read the position coordinates of the object at each scanning angle at each time point, and calculate the change in the position coordinates of the object at each scanning angle, which is recorded as , so as to classify objects at each scanning angle into static objects and dynamic obstacles, and count the classification of objects at each scanning angle; The second step is to read the position coordinates of objects at each scanning angle, extract the position coordinates of each static object, and mark the position coordinates of each static object in the environment map. If the position coordinates of a static object overlap with existing objects in the environment map, it means that the static object is not an obstacle. If the position coordinates of a static object do not overlap with existing objects in the environment map, it means that the static object is an obstacle and is further classified as a static obstacle.

6. The intelligent monitoring and control system for washing robot operation according to claim 5 is characterized in that: The specific analysis method of the static obstacle avoidance module is: Read the distance between the washing robot and the object at each scanning angle, extract the distance between the washing robot and each static obstacle, compare the distance between the washing robot and each static obstacle with the preset safety distance threshold, if the distance between the washing robot and a static obstacle is less than or equal to the preset safety distance threshold, then the static obstacle is recorded as the designated obstacle, and the washing robot is controlled to turn to avoid the obstacle.

7. The intelligent monitoring and control system for washing robot operation according to claim 6 is characterized in that: The specific analysis method of the moving speed of each segment of the moving trajectory of the specified dynamic obstacle is: The distance between the washing robot and each dynamic obstacle is monitored in real time. When the distance between the washing robot and a dynamic obstacle reaches the set safety distance threshold, the dynamic obstacle is recorded as a designated dynamic obstacle. The designated dynamic obstacle is recorded by the built-in camera of the washing robot to obtain a motion video of the designated dynamic obstacle. The center point of the designated dynamic obstacle is selected as the detection point, and the position points of each frame of the designated dynamic obstacle in the motion video of the designated dynamic obstacle are marked. The moving trajectory of the designated dynamic obstacle is obtained by connecting the position points of each frame of the designated dynamic obstacle video. The moving trajectory of the designated dynamic obstacle is divided into several segments according to fixed time intervals, and the moving speed of each segment of the moving trajectory of the designated dynamic obstacle is obtained.

8. The intelligent monitoring and control system for washing robot operation according to claim 7 is characterized in that: The specific analysis method of the dynamic obstacle avoidance module is: The first step is to read the moving speed of each segment of the moving trajectory of the specified dynamic obstacle, recorded as , Indicates The number of the segment moving trajectory, , through the formula Get the moving speed fluctuation degree of the specified dynamic obstacle , Indicates the number of segments of the moving trajectory; The second step is to compare the movement speed fluctuation degree of the specified dynamic obstacle with the preset movement speed fluctuation degree threshold. If the movement speed fluctuation degree of the specified dynamic obstacle is less than the preset movement speed fluctuation degree threshold, it means that the specified dynamic obstacle moves regularly, and the cleaning robot is controlled to turn to avoid the obstacle. In the third step, if the fluctuation degree of the moving speed of the specified dynamic obstacle is greater than or equal to the preset moving speed fluctuation degree threshold, it means that the specified dynamic obstacle is moving irregularly, and the washing robot is controlled to turn to avoid the obstacle. When the specified dynamic obstacle suddenly appears at the set safety distance threshold, the moving direction of the specified dynamic obstacle is judged according to the moving trajectory of the specified dynamic obstacle, so as to control the washing robot to avoid the obstacle.

9. The intelligent monitoring and control system for cleaning robot operation according to claim 1, characterized in that: The specific analysis method of the path modification module is: The first step is to count the number of times the cleaning robot avoids each static obstacle, obtain the number of times the cleaning robot avoids each static obstacle, and compare it with the preset obstacle avoidance number threshold. If the number of times the cleaning robot avoids a static obstacle is greater than or equal to the preset obstacle avoidance number threshold, the static obstacle is recorded as a fixed obstacle, and the fixed obstacles are screened out, and the position coordinates of each fixed obstacle are obtained and updated into the environment map. The second step is to divide the cycle according to the set time length, and regularly update the environmental map by updating each fixed obstacle into the environmental map to obtain the environmental map of each cycle, and then regularly re-plan the optimal travel path of the washing and care robot by planning the optimal travel path of the washing and care robot to obtain the optimal travel path of the washing and care robot in each cycle.

10. An intelligent monitoring and control method for a cleaning robot operation, characterized in that: The specific steps of the control method are as follows: S1. Map construction and positioning: The camera obtains the environmental image around the cleaning robot in real time, thereby constructing an environmental map and marking each fixed task point, and positioning the robot in the environmental map; S2. Path planning: planning the optimal path of the cleaning robot according to the positions of each fixed task point of the cleaning task; S3. Obstacle detection: The laser transmitter built into the cleaning robot emits a laser beam to scan the surrounding area to obtain the position coordinates of the object at each scanning angle and at each time point; S4. Obstacle analysis: determine whether the object at each scanning angle is an obstacle based on the position coordinates of the object at each scanning angle at each time point and classify each obstacle; S5. Static obstacle avoidance: obtaining the distance between the cleaning robot and each static obstacle, and then controlling the cleaning robot to turn and avoid obstacles; S6. Dynamic obstacle avoidance: Generate a moving trajectory of a specified dynamic obstacle, obtain the moving speed of each segment of the moving trajectory of the specified dynamic obstacle, and then determine the moving regularity of the specified dynamic obstacle and avoid the obstacle; S7. Path modification: Update the obstacles into the environment map according to the number of occurrences of each static obstacle, and periodically update the optimal travel path of the cleaning robot.

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