Intelligent floor sweeping robot system and intelligent floor sweeping robot

Abstract

The system comprises an upper computer module, a bottom layer control module, a direct current gear motor, a motor driving module, a laser radar and a gyroscope, a single-chip microcomputer is connected with a Raspberry Pi 3B through a serial port, the single-chip microcomputer is connected with a motor driving chip, the laser radar and the gyroscope, and the motor driving chip, the laser radar and the gyroscope are connected with the upper computer module. And the motor driving chip is connected with the direct-current gear motor. According to the invention, obstacle avoidance information is collected through the laser radar, positioning is carried out based on an AMCL algorithm in the upper computer module, and a two-dimensional grid map is constructed through a Gmapping algorithm and a Bresenham algorithm, so that high-precision positioning and map construction of the sweeping robot are realized, and the navigation precision of the sweeping robot is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent household appliances, and particularly to an intelligent floor sweeping robot system and an intelligent floor sweeping robot. Background Art

[0002] With the rapid development of science and technology, more and more families begin to use robots to help with housework. In recent years, smart home has entered people's lives. Floor sweeping robots can automatically clean the floor, bringing many conveniences to home cleaning.

[0003] Floor sweeping robots need to build an indoor map and perform planning to complete the cleaning task. However, traditional floor sweeping robots are restricted by factors such as physical space and control methods, and cannot autonomously sense and view the surrounding environment, resulting in poor positioning and map construction accuracy of the floor sweeping robot, and further poor navigation accuracy, affecting the user experience. Therefore, there is an urgent need to propose an intelligent floor sweeping robot system with high positioning and map construction accuracy. Summary of the Invention

[0004] In view of this, it is necessary to provide an intelligent floor sweeping robot system and an intelligent floor sweeping robot to solve the technical problem that the existing floor sweeping robot has poor positioning and map construction accuracy, resulting in poor navigation accuracy.

[0005] To solve the above problems, the present invention provides an intelligent floor sweeping robot system, which includes a host computer module, a bottom control module, a DC geared motor, a motor drive module, a lidar and a gyroscope; Among them, the bottom control module is respectively connected to the host computer module, the motor drive module, the lidar and the gyroscope, and the motor drive module is connected to the DC geared motor; The bottom control module is used to transmit the obstacle avoidance information and wheel speed information collected by the lidar and the gyroscope to the host computer module; The host computer module is used to locate the floor sweeping robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information, then use the Gmapping algorithm and the Bresenham algorithm to construct a two-dimensional grid map, and perform path planning through the dynamic window method to obtain a planned path; The host computer module is also used to issue a motion control instruction to the bottom control module according to the wheel speed information, the current position information and the planned path; The bottom control module is also used to analyze the motion control instruction to obtain the wheel speed control signal of the floor sweeping robot, and transmit the wheel speed control signal to the motor drive module; The motor drive module drives the DC geared motor to operate according to the wheel speed control signal, thereby controlling the sweeping robot to move to the target position.

[0006] Optionally, the host computer module includes a positioning unit, a map construction unit, a path planning unit, and a mileage calculation unit; The positioning unit is used to position the sweeping robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information; The map construction unit is used to construct an initial map using the Gmapping algorithm, and then perform occupancy labeling on the initial map using the Bresenham algorithm to obtain the two-dimensional grid map; The path planning unit is used to perform indoor path planning on the sweeping robot based on the two-dimensional grid map using the dynamic window method to obtain the planned path; The mileage calculation unit is used to issue a motion control instruction to the underlying control module according to the wheel speed information, the current position information, and the planned path.

[0007] Optionally, it further includes a wireless network module connected to the underlying control module; The wireless network module is used to establish a wireless communication connection between the underlying control module, the user terminal, and the home network.

[0008] Optionally, the wireless network module is a hardware development board of model ESP8266NodeMCU.

[0009] Optionally, it further includes a temperature and humidity sensor and a display panel connected to the wireless network module; The temperature and humidity sensor is used to collect the temperature value and humidity value of the room in real time; The wireless network module is also used to obtain the temperature value and the humidity value and send them to the user terminal and the display panel; The display panel is used to display the room temperature and humidity in real time according to the temperature value and the humidity value.

[0010] Optionally, it further includes a voice recognition module connected to the underlying control module; The voice recognition module is used to recognize the user's voice and generate a corresponding voice control instruction, and send the voice control instruction to the underlying control module; The underlying control module is also used to control the sweeping robot to perform corresponding actions according to the voice control instruction.

[0011] Optionally, it further includes a monitoring module connected to the wireless network module; The monitoring module is used to perform real-time video monitoring on the interior of the room and transmit the monitoring video to the user terminal through the wireless network module.

[0012] Optionally, the host computer module is composed of installing the ROS system on a Raspberry Pi.

[0013] Optionally, the underlying control module is a single-chip microcomputer of model STM32F405RGT6.

[0014] Furthermore, the present invention also provides an intelligent sweeping robot, which includes the above-mentioned intelligent sweeping robot system.

[0015] The beneficial effects of the present invention are as follows: The intelligent sweeping robot system provided by the present invention includes a host computer module, an underlying control module, a DC geared motor, a motor drive module, a lidar, and a gyroscope. The underlying control module transmits the obstacle avoidance information and wheel speed information collected by the lidar and the gyroscope to the host computer module, so that the host computer module locates the sweeping robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information, then constructs a two-dimensional grid map using the Gmapping algorithm and the Bresenham algorithm, and performs path planning through the dynamic window method to obtain the planned path; the host computer module is also used to issue motion control instructions to the underlying control module according to the wheel speed information, the current position information, and the planned path. The underlying control module then analyzes the motion control instructions to obtain the wheel speed control signal of the sweeping robot and transmits the wheel speed control signal to the motor drive module, so that the motor drive module drives the DC geared motor to act according to the wheel speed control signal, thereby controlling the sweeping robot to move to the target position. The present invention collects obstacle avoidance information through a lidar, performs positioning using the AMCL algorithm, and constructs a two-dimensional grid map using the Gmapping algorithm and the Bresenham algorithm, realizing high-precision positioning and map construction of the sweeping robot and improving the navigation accuracy of the sweeping robot. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those skilled in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0017] Figure 1 It is a schematic structural diagram of an embodiment of the intelligent sweeping robot system provided by the present invention; Figure 2 It is a schematic diagram of the software operation logic flow of an embodiment of the intelligent sweeping robot system provided by the present invention; Figure 3 Schematic diagram of the startup node process of an embodiment of the host computer module in the intelligent floor cleaning robot system provided by the present invention; Figure 4 Schematic diagram of the principle of an embodiment of the wireless network module, display panel, and temperature and humidity sensor in the intelligent floor cleaning robot system provided by the present invention; Figure 5 Schematic diagram of the principle of an embodiment of the voice recognition module in the intelligent floor cleaning robot system provided by the present invention. Detailed implementation manners

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0019] It should be understood that the schematic drawings are not drawn to actual scale. The flowcharts used in the present invention illustrate the operations implemented according to some embodiments of the present invention. It should be understood that the operations in the flowchart may not be implemented in sequence, and steps without logical context relationships may be reversed or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart or remove one or more operations from the flowchart under the guidance of the content of the present invention.

[0020] Referring to "embodiments" herein means that the specific features, structures, or characteristics described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The phrase appears at various positions in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0021] The embodiments of the present invention provide an intelligent floor cleaning robot system and an intelligent floor cleaning robot, which will be described separately below.

[0022] Figure 1 Schematic diagram of the structure of an embodiment of the intelligent floor cleaning robot system provided by the present invention, as Figure 1 shown, the system includes a host computer module 101, a bottom layer control module 102, a DC geared motor 103, a motor drive module 104, a lidar 105, and a gyroscope 106; Among them, the bottom layer control module 102 is respectively connected to the host computer module 101, the motor drive module 104, the lidar 105, and the gyroscope 106, and the motor drive module 104 is connected to the DC geared motor 103; The underlying control module 102 is used to transmit the obstacle avoidance information and wheel speed information collected by the lidar 105 and the gyroscope 106 to the host computer module 101; The host computer module 101 is used to locate the sweeping robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information, then use the Gmapping algorithm and the Bresenham algorithm to construct a two-dimensional grid map, and perform path planning through the dynamic window method to obtain the planned path; The host computer module 101 is also used to issue a motion control instruction to the underlying control module 102 according to the wheel speed information, the current position information and the planned path; The underlying control module 102 is also used to analyze the motion control instruction to obtain the wheel speed control signal of the sweeping robot, and transmit the wheel speed control signal to the motor drive module 104; The motor drive module 104 drives the DC reduction motor 103 to act according to the wheel speed control signal, thereby controlling the sweeping robot to move to the target position.

[0023] It should be noted that in the embodiment of the present invention, the host computer module 101 can be implemented by Raspberry Pi 3B, and a single chip microcomputer with the model STM32F405RGT6 is used as the underlying control module 102, and serial communication is used between the underlying control module 102 and the host computer module 101; both the lidar 105 and the gyroscope 106 belong to sensors and are directly connected to the underlying control module 102. Among them, the lidar 105 is mainly used to emit laser beams to the surrounding environment, receive reflected signals, sense the position information of objects, and provide high-precision and high-resolution data. In order to improve the positioning accuracy and mapping accuracy of the sweeping robot, the lidar 105 needs to have extremely high accuracy, while the gyroscope 106 collects the current wheel speed information, including running speed, acceleration, angular velocity, etc., and the gyroscope 106 of model MPU6050 can be selected; since the sweeping robot not only needs to move but also needs to clean, at least two DC reduction motors 103 are required, so the motor drive module 104 can select the motor drive chip of model L298N. This type of motor drive chip can simultaneously control two DC reduction motors 103 to perform different actions and has strong driving ability. In addition, this motor drive chip can also detect the temperature of the motor and automatically disconnect the power supply to protect the sweeping robot when the motor temperature is too high.

[0024] It can be understood that in the embodiments of the present invention, the reason for selecting the STM32F405RGT6 single-chip microcomputer as the underlying control module 102 is that the STM32F405RGT6 adopts the Cortex-M4 kernel, which has the characteristics of high performance and low power consumption, and can meet the computing requirements of the high-precision lidar 105. In addition, the STM32F405RGT6 integrates multiple common peripherals, such as serial peripheral interfaces, buses, universal synchronous / asynchronous serial receivers / transmitters, etc. Through these peripherals, data interaction and communication can be carried out with the lidar 105; since the intelligent sweeping robot needs to process a large amount of data, a chip with a large-capacity storage needs to be selected, and the STM32F405RGT6 is used for 512KB of Flash storage and 192KB of SRAM storage, which can support the operation and storage of complex algorithms and application programs. At the same time, the STM32F405RGT6 has built-in multiple protection mechanisms, such as stack protection, cyclic redundancy check, etc., which can effectively protect the lidar 105 from external noise interference, ensuring the accuracy and stability of the sweeping robot's navigation.

[0025] Referring to Figure 2 , Figure 2 is a schematic diagram of the software operation logic flow of an embodiment of the intelligent sweeping robot system provided by the present invention; the PID speed control function in the figure is a program pre-set in the underlying control module 102. IIC is a bus transmission method supported by the STM32F405RGT6, and ROS is a robot system installed in the upper computer module 101, which refers to the upper computer module 101 in the figure. In the embodiments of the present invention, the lidar 105 and the gyroscope 106 collect the surrounding environment of the sweeping robot and its own motion information, and feedback it to the single-chip microcomputer. The single-chip microcomputer then uploads the obstacle avoidance signal and motion signal collected by the lidar 105 and the gyroscope 106 in real time to the Raspberry Pi 3B. The computer program in the Raspberry Pi 3B calculates to obtain the target speed of the sweeping robot, converts the target speed into a wheel speed control signal and outputs it to the single-chip microcomputer, so that the single-chip microcomputer controls the operation of the motor drive chip according to the wheel speed control signal, and further enables the motor drive chip to drive the wheel motor to perform corresponding actions, and the sweeping robot moves to the corresponding position at the target speed.

[0026] Compared with the prior art, the intelligent floor cleaning robot system provided by the embodiments of the present invention includes a host computer module 101, a bottom layer control module 102, a DC geared motor 103, a motor drive module 104, a lidar 105, and a gyroscope 106. The bottom layer control module 102 transmits the obstacle avoidance information and wheel speed information collected by the lidar 105 and the gyroscope 106 to the host computer module 101, so that the host computer module 101 locates the floor cleaning robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information, then constructs a two-dimensional grid map by using the Gmapping algorithm and the Bresenham algorithm, and performs path planning by using the dynamic window method to obtain the planned path. The host computer module 101 is also used to issue a motion control instruction to the bottom layer control module 102 according to the wheel speed information, the current position information, and the planned path. The bottom layer control module 102 then analyzes the motion control instruction to obtain the wheel speed control signal of the floor cleaning robot, and transmits the wheel speed control signal to the motor drive module 104, so that the motor drive module 104 drives the DC geared motor 103 to act according to the wheel speed control signal, thereby controlling the floor cleaning robot to move to the target position. By collecting obstacle avoidance information through the lidar 105, positioning by using the AMCL algorithm, and constructing a two-dimensional grid map by using the Gmapping algorithm and the Bresenham algorithm, the present invention realizes the high-precision positioning and map construction of the floor cleaning robot, and solves the technical problem of poor navigation accuracy caused by poor positioning and map construction accuracy of the floor cleaning robot.

[0027] In some embodiments of the present invention, the host computer module 101 includes a positioning unit, a map construction unit, a path planning unit, and an odometry calculation unit; The positioning unit is used to locate the floor cleaning robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information; The map construction unit is used to construct an initial map by using the Gmapping algorithm, and then perform occupancy annotation on the initial map by using the Bresenham algorithm to obtain a two-dimensional grid map; The path planning unit is used to perform indoor path planning on the floor cleaning robot on the basis of the two-dimensional grid map by using the dynamic window method to obtain the planned path; The odometry calculation unit is used to issue a motion control instruction to the bottom layer control module 102 according to the wheel speed information, the current position information, and the planned path.

[0028] It should be noted that in the embodiments of the present invention, the positioning of the sweeping robot and the construction of the indoor map are mainly completed by the host computer module 101. The AMCL algorithm is an upgraded version of the Monte Carlo localization method (MCL). By sampling the sensor data around the robot and using a particle filter to calculate the probability distribution of the current position of the robot, the number of particles determines the accuracy of the algorithm. The positions of the particles are randomly scattered on the map, and each particle has a weight value indicating the likelihood that this position is the true position of the robot. This positioning algorithm can be understood as evenly scattering a handful of particles in the map space. By obtaining the actions of the robot to move the particles, when the robot moves forward one meter, all the particles move forward one meter. Regardless of whether the positions of the particles are accurate, the position of each particle is used to simulate a sensor information and compare it with the observed sensor information (generally the obstacle avoidance information of the lidar 105), so as to assign a probability to each particle, and then regenerate the particles according to the generated probability. The higher the probability, the greater the generation probability. After repeated iterations, all the particles gradually converge, and the exact position of the robot can be deduced. The core of the AMCL algorithm is resampling, that is, reordering the particle weight values after each movement of the robot, and copying the high-weight particles multiple times according to the particle weight values to increase their number, while the low-weight particles are deleted, so that the particles are concentrated in the more likely areas. As the robot continues to move and the sensor data is updated, the number of particles will gradually decrease, but the particles near the true position of the robot can still remain. Finally, the position of the robot can be estimated by the weighted average of the particles, so as to achieve adaptive positioning and obtain the current position information of the robot.

[0029] It can be understood that in the embodiments of the present invention, after constructing a preliminary map of the room through the Gmapping algorithm and determining the precise position of the sweeping robot, the coordinates of the obstacles can be calculated based on the obstacle avoidance information of the lidar 105 and the coordinates and orientation of the robot. Then, according to the Bresenham line segment scanning algorithm, the grid where the obstacle is located is marked as occupied, and a line is connected between the grid where the robot is located and the grid where the obstacle is located; all the grids on the line are marked as unoccupied, and each grid has an available probability value indicating the proportion it occupies. If a grid is occupied under both laser beam a and laser beam b scans, the occupancy probability of this grid increases; otherwise, the occupancy probability decreases. In this way, the environment where the robot is located can be represented by a two-dimensional grid map, and a two-dimensional grid map is obtained.

[0030] It should also be noted that in the embodiments of the present invention, the dynamic window method is adopted to perform path planning for the sweeping robot. By sampling multiple sets of speeds in the speed (v, w) space, the trajectories of the robot within a certain time period (Sim_period) at these speeds are simulated. After obtaining multiple sets of trajectories, these trajectories are evaluated to select the speed corresponding to the optimal path to drive the robot to move. According to the requirements of the robot working in the home environment, path planning and design are carried out on the obtained two-dimensional grid map, and the working area is gradually covered along the designed route by means of path following.

[0031] In specific implementation, referring to Figure 3 , Figure 3 is a schematic diagram of the startup node process of an embodiment of the upper computer module 101 in the intelligent sweeping robot system provided by the present invention. STM32 in the figure refers to the underlying control module 102, and the robot odometer is the motion control instruction; in the embodiments of the present invention, the upper computer module 101 will continuously obtain the actual speed and angle of the robot from the underlying control module 102, and then calculate the mileage of the robot, as well as the speed and angle of the robot according to the current position information and the pre-planned path, and transmit the kinematic formula containing the robot's motion mileage, motion speed, and motion angle to the underlying control module 102 in real time. The underlying control module 102 parses the kinematic formula, calculates the speed and angle corresponding to each wheel of the robot, and then controls the DC reduction motor 103 through the motor drive module 104. The motor drive module 104 also performs closed-loop control on the motor speed, counts the number of encoder pulses received per unit time, calculates the wheel speed, and reports it to the upper computer module 101 through the underlying control module 102, so that the upper computer obtains the actual wheel speed information.

[0032] In some embodiments of the present invention, it further includes a wireless network module 107 connected to the underlying control module 102; The wireless network module 107 is used to establish a wireless communication connection between the underlying control module 102, the user terminal, and the home network.

[0033] Referring to Figure 4 , Figure 4 is a schematic diagram of the principle of an embodiment of the wireless network module, the display panel, and the temperature and humidity sensor in the intelligent sweeping robot system provided by the present invention.

[0034] It should be noted that in the embodiments of the present invention, the wireless network module 107 selects a hardware development board with the model of ESP8266NodeMCU. This hardware development board not only supports wireless transmission, but also has functions such as serial communication and PWM control. It can be programmed using Arduino, has various Arduino library functions and a large number of reusable codes, which greatly improves the development efficiency. At the same time, it supports a variety of sensors and expansion board interfaces, facilitating users to expand and perform secondary development. Through the above wireless network module 107, users can send control instructions to the underlying control module 102 through the mobile phone APP to control the sweeping robot to execute corresponding commands.

[0035] In some embodiments of the present invention, it further includes a temperature and humidity sensor 108 and a display panel 109 connected to the wireless network module 107; The temperature and humidity sensor 108 is used to collect the temperature value and humidity value of the room in real time; The wireless network module 107 is also used to obtain the temperature value and humidity value and send them to the user terminal and the display panel 109; The display panel 109 is used to display the room temperature and humidity in real time according to the temperature value and humidity value.

[0036] It should be noted that in the embodiments of the present invention, after the above wireless network module 107 is installed on the sweeping robot, the temperature and humidity sensor 108 and the display panel 109 can be installed through the expansion interface on the wireless network module 107. The temperature and humidity sensor 108 is used to collect the indoor temperature and humidity, and the display panel 109 is used to display it. It can also be pushed to the user's mobile phone through the wireless network module 107, so that users can obtain the indoor temperature and humidity information in real time.

[0037] It can be understood that in the embodiments of the present invention, the model of the temperature and humidity sensor 108 used is DHT11, which is a digital temperature and humidity sensor 108. It has the advantages of low price, stable output, high response rate and strong anti-interference ability, and is very suitable for home temperature and humidity monitoring. The wireless network module 107 can read the temperature and humidity data through the serial port and output it to the display panel 109 at the same time. The display panel 109 can use a liquid crystal screen with the model of ILI9341. It supports both SPI bus interface and parallel interface at the same time, and the transmission rate can reach 50MHz, and the display speed is very fast. In addition, the liquid crystal screen supports the highest resolution of 320x240, supports 16-bit color depth and RGB565 color format, and the display effect is very clear and vivid. In addition, the liquid crystal screen also has a power-saving function and can automatically enter the sleep mode. The model of the display panel 109 used is TFT2.8-ILI9341.

[0038] In some embodiments of the present invention, it further includes a voice recognition module 110 connected to the underlying control module 102; The voice recognition module 110 is used to recognize the user's voice and generate corresponding voice control instructions, and send the voice control instructions to the underlying control module 102; The underlying control module 102 is further used to control the sweeping robot to perform corresponding actions according to the voice control instructions.

[0039] It should be noted that in the embodiments of the present invention, reference Figure 5 , Figure 5 is a schematic diagram of the principle of an embodiment of the voice recognition module 110 in the intelligent sweeping robot system provided by the present invention. The model of the voice recognition module adopted in the embodiments of the present invention is SU-03T, which is a low-cost, low-power, and small-size offline voice recognition module. The built-in Hummingbird M (US516P) chip is a low-cost pure offline voice recognition chip launched by Yunzhisheng for a large number of pure offline control scenarios and products, and is widely used in various intelligent small household appliances, toys, lamps, etc. This voice recognition module supports bilingual recognition of English and Chinese, and has high recognition efficiency. It can be awakened by customizing the wake-up word, and the configuration is simple. Only by customizing the wake-up word and corresponding control instructions on the corresponding web page can voice control be realized. Through this voice recognition module, the user can issue instructions to the single-chip microcomputer through voice, and then control the sweeping robot to perform corresponding actions.

[0040] In some embodiments of the present invention, it further includes a monitoring module 111 connected to the wireless network module 107; The monitoring module 111 is used to perform real-time video monitoring of the indoor environment, and transmit the monitoring video to the user terminal through the wireless network module 107.

[0041] It should be noted that in the embodiments of the present invention, the monitoring module 111 can be implemented by a camera. The camera can be used to perform video monitoring of the house from the perspective of the sweeping robot, and upload the monitoring video to the home network or the user terminal (such as a mobile phone, a computer, etc.) through the wireless network module 107 to achieve the security protection of the home.

[0042] Furthermore, the embodiments of the present invention also propose an intelligent sweeping robot, which includes the above-mentioned intelligent sweeping robot system. For specific embodiments of this intelligent sweeping robot, reference can be made to the embodiments of the above-mentioned intelligent sweeping robot system, and details will not be elaborated here.

[0043] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention.

Claims

1. An intelligent floor cleaning robot system, characterized in that, It includes a host computer module, a bottom control module, a DC geared motor, a motor drive module, a lidar, and a gyroscope; Among them, the bottom control module is respectively connected to the host computer module, the motor drive module, the lidar, and the gyroscope, and the motor drive module is connected to the DC geared motor; The bottom control module is used to transmit the obstacle avoidance information and wheel speed information collected by the lidar and the gyroscope to the host computer module; The host computer module is used to locate the sweeping robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information, then use the Gmapping algorithm and the Bresenham algorithm to construct a two-dimensional grid map, and perform path planning through the dynamic window method to obtain the planned path; The host computer module is also used to issue a motion control instruction to the bottom control module according to the wheel speed information, the current position information, and the planned path; The bottom control module is also used to analyze the motion control instruction to obtain the wheel speed control signal of the sweeping robot, and transmit the wheel speed control signal to the motor drive module; The motor drive module drives the DC geared motor to act according to the wheel speed control signal, thereby controlling the sweeping robot to move to the target position.

2. The intelligent floor-sweeping robot system according to claim 1, wherein, The host computer module includes a positioning unit, a map construction unit, a path planning unit, and a mileage calculation unit; The positioning unit is used to locate the sweeping robot according to the obstacle avoidance information and the AMCL algorithm to obtain the current position information; The map construction unit is used to construct an initial map using the Gmapping algorithm, and then perform occupancy marking on the initial map using the Bresenham algorithm to obtain the two-dimensional grid map; The path planning unit is used to perform indoor path planning on the sweeping robot based on the two-dimensional grid map using the dynamic window method to obtain the planned path; The mileage calculation unit is used to issue a motion control instruction to the bottom control module according to the wheel speed information, the current position information, and the planned path.

3. The intelligent floor sweeping robot system according to claim 2, characterized in that, It also includes a wireless network module connected to the bottom control module; The wireless network module is used to establish a wireless communication connection between the bottom control module, the user terminal, and the home network.

4. The intelligent floor sweeping robot system according to claim 3, characterized in that The wireless network module is a hardware development board of model ESP8266NodeMCU.

5. The intelligent floor sweeping robot system according to claim 4, characterized in that, It also includes a temperature and humidity sensor and a display panel connected to the wireless network module; The temperature and humidity sensor is used to collect the temperature value and humidity value of the room in real time; The wireless network module is also used to obtain the temperature value and the humidity value and send them to the user terminal and the display panel; The display panel is used to display the room temperature and humidity in real time according to the temperature value and the humidity value.

6. The intelligent floor sweeping robot system according to claim 5, wherein It also includes a voice recognition module connected to the bottom control module; The voice recognition module is used to recognize the user's voice and generate a corresponding voice control instruction, and send the voice control instruction to the bottom control module; The underlying control module is further configured to control the sweeping robot to perform corresponding actions according to the voice control instruction.

7. The intelligent floor sweeping robot system according to claim 6, wherein It further includes a monitoring module connected to the wireless network module; The monitoring module is used to perform real-time video monitoring of the interior of the room and transmit the monitoring video to the user terminal through the wireless network module.

8. The intelligent floor sweeping robot system according to claim 7, characterized in that The host computer module is composed of installing the ROS system on a Raspberry Pi.

9. The intelligent floor-sweeping robot system according to claim 7, wherein The underlying control module is a single-chip microcomputer of model STM32F405RGT6.

10. An intelligent floor cleaning robot, characterized in that, It includes the intelligent sweeping robot system according to any one of claims 1-9.

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