Robot

Abstract

The utility model provides a robot, which relates to the field of intelligent robots and comprises a laser ranging sensor LDS, an artificial intelligence AI camera module, an infrared camera module and a double-line laser sensor which are positioned on the side surface of a machine body, the LDS is located in the center of the front side of the machine body, the AI camera module and the infrared camera module are located on any side of the periphery of the LDS, and the double-line laser sensors are located on the left side and the right side of the infrared camera module, so that the LDS is arranged in the center of the front side of the machine body; in combination with cooperative work of the AI camera module, the infrared camera module and the double-line laser sensor under the structural layout, the robot can perform environment modeling and path planning more quickly and accurately, so that the robot can adjust the position and path of the robot more flexibly when facing a complex environment, and the working efficiency of the robot is improved. Particularly, the performance is more excellent in a cleaning task in a low area.

Description

Technical Field

[0001] This utility model relates to the field of intelligent robots, and in particular to a robot. Background Technology

[0002] In the field of robotics, laser distance sensors (LDS) are widely used for environmental mapping, obstacle avoidance, and navigation. LDS measures the distance to surrounding objects by emitting lasers and receiving reflected signals, thereby constructing two-dimensional or three-dimensional maps of the environment. Especially when applied to robotic vacuum cleaners, LDS can help the vacuum cleaners autonomously plan their paths, avoid obstacles, and thus improve cleaning efficiency.

[0003] In related technologies, LDS components are usually installed on top of the robot vacuum cleaner, increasing the overall height of the robot vacuum cleaner. This makes it impossible for the robot vacuum cleaner to enter and clean low areas, such as under furniture and under sofas, which limits the application range of the robot.

[0004] However, the challenge of reducing the fuselage height lies in how to redesign the layout and installation of the LDS components while ensuring that their ranging and mapping capabilities are not affected. Utility Model Content

[0005] This invention provides a robot that, by placing the LDS at the center of the front side of the robot body, and setting the AI ​​camera module and infrared camera module on any side around the LDS, and installing dual-line laser sensors on the left and right sides of the infrared camera module, enables the robot to adjust its position and path more flexibly when facing complex environments, while ensuring that its ranging and mapping capabilities are not affected. It performs particularly well in cleaning tasks in low-lying areas.

[0006] This utility model provides a robot, which includes: a laser rangefinder (LDS), an artificial intelligence (AI) camera module, an infrared camera module, and a dual-line laser sensor located on the side of the robot body; the LDS is located at the center of the front side of the robot body, the AI ​​camera module and the infrared camera module are located on either side of the LDS, and the dual-line laser sensor is located on the left and right sides of the infrared camera module.

[0007] In this invention, placing the LDS at the front center of the robot body, rather than at the top, effectively reduces the robot's overall height. This allows the robot to more easily access low-lying areas, such as under furniture and sofas, for cleaning, thus expanding its application range. It should be noted that the LDS is positioned at the front center to obtain the maximum field of view, enabling it to directly perceive environmental information and provide accurate distance measurements. The AI ​​camera module and infrared camera module are located on either side of the LDS to ensure a sufficient field of view and improve measurement accuracy. The dual-line laser sensors are located on the left and right sides of the infrared camera module, making it more consistent with the triangulation principle and ensuring a more balanced field of view on both sides, thereby enhancing lateral environmental perception capabilities and providing a wider field of view and higher measurement accuracy.

[0008] Furthermore, traditional LDS are usually mounted on top of the robot and require 360-degree rotation to scan the surrounding environment. However, by moving the LDS to the center of the front of the robot, the design no longer requires a complex rotating structure. This not only simplifies the mechanical design and saves a significant amount of space inside the robot, but also reduces the wear and maintenance needs of moving parts.

[0009] Therefore, this invention integrates components such as LDS, AI camera module, infrared camera module and dual-line laser sensor together, which reduces the height of the robot and saves internal space, allowing it to accommodate more other devices, improving design redundancy. Furthermore, this multi-module integration facilitates unified software management and resource allocation, saves space, and makes the software more flexible in allocating hardware resources, thereby improving operating efficiency.

[0010] Optionally, the dual-line laser sensors are symmetrically located on the left and right sides of the LDS.

[0011] Understandably, symmetrically distributed dual-line laser sensors can provide a wider field of view coverage, ensuring effective distance measurement in the environment in front of and to the sides of the robot. Furthermore, with proper spacing, the overlapping fields of view between the dual-line laser sensors can minimize blind spots, ensuring that the robot can fully perceive surrounding obstacles in complex environments.

[0012] Therefore, the symmetrical layout makes the robot's field of vision on both sides more balanced, ensuring that the robot obtains balanced information input in the left and right directions, thereby enabling it to detect and locate obstacles more accurately and to navigate more stably, especially in narrow or complex paths.

[0013] Furthermore, the symmetrical design not only provides functional advantages but also offers a balanced and harmonious aesthetic. The symmetrically distributed dual-line laser sensors provide a degree of redundancy, ensuring that even if one sensor fails, the other can still provide the necessary environmental information, thus enhancing the robot's fault tolerance.

[0014] Optionally, the AI ​​camera module and the infrared camera module are located on the same side around the LDS.

[0015] In this invention, placing the AI ​​camera module and the infrared camera module on the same side of the LDS allows for a more compact design. This integrated layout helps reduce the overall size and weight of the robot, improves its flexibility and mobility, and makes assembly easier.

[0016] Furthermore, concentrating the modules on the same side simplifies internal wiring, thereby reducing manufacturing complexity and cost. Also, concentrating the AI ​​camera module and the infrared camera module on one side ensures that they have a consistent viewing angle, reducing the data processing complexity caused by differences in viewing angle. Therefore, integrating the AI ​​camera module and the infrared camera module on the same side makes it easier for the robot to perform data fusion, providing a more comprehensive environmental perception capability by combining visual and infrared information.

[0017] Optionally, the robot also includes a supplemental light located between the infrared camera module and the dual-line laser sensor.

[0018] Because supplemental lighting can provide additional illumination in low-light environments, it significantly improves the image quality captured by AI camera modules and infrared camera modules. This helps improve the accuracy of object recognition and classification. By improving lighting conditions, supplemental lighting can also help sensors measure distances and identify objects more accurately, especially in complex or dynamic environments. Therefore, the illumination provided by supplemental lighting enables sensors and modules to work together better, providing more comprehensive environmental perception capabilities. Furthermore, better visual information and distance measurement help robots to perform more accurate path planning, avoid obstacles, and improve navigation efficiency.

[0019] In addition, the use of supplemental lighting in low-light conditions can reduce the risk of accidental collisions and improve the operational safety of robots.

[0020] Optionally, the robot may also include a voice module located on the top of the robot body, which is used to receive voice commands to control the robot to perform corresponding operations.

[0021] It should be noted that in the prior art, in addition to setting the LDS module on the top of the device, a voice module is also set. The LDS module originally generated noise when running on the top of the device. However, in this utility model, by removing the LDS module and setting the LDS in the center of the front side of the device, the noise generated by the original LDS module running on the top of the device is greatly reduced, thereby reducing interference with the voice module. The original LDS module integrated a rotating mechanism, while the LDS in this utility model does not require a rotating mechanism.

[0022] Therefore, by moving the LDS to the center of the front of the robot body, away from the voice module, noise interference to the voice module can be significantly reduced. Reducing noise interference helps improve the recognition accuracy of the voice module, enabling it to receive and process user voice commands more reliably. In turn, more accurate voice recognition can improve the robot's response speed, allowing the robot to execute user commands more quickly.

[0023] In summary, this utility model provides a robot designed to solve the problem of increased height caused by the LDS (Local Disk System) being installed on the top of traditional robotic vacuum cleaners. To address this, the LDS is redesigned and installed at the center of the front side of the robot body, rather than on the top. This layout effectively reduces the overall height of the robot, allowing it to more easily access low-ceilinged areas. Furthermore, when the LDS is installed on the top, blind spots can easily occur due to partial obstruction by the robot body. By installing the LDS at the center of the front side of the robot body, the maximum field of view can be obtained, reducing blind spots. Moreover, since the field of view is better the closer to the center of the front side, the AI ​​camera module and infrared camera module are placed accordingly. Positioning the dual-line laser sensor at any location near the front center, i.e., on any side of the LDS, allows for higher accuracy in data acquisition by the AI ​​camera module and infrared camera module. Furthermore, the combination of the dual-line laser sensor and infrared camera module provides more precise distance measurement and obstacle detection capabilities. The lasers emitted by the dual-line laser sensor are intersecting, with the left dual-line laser sensor emitting a laser to the right and the right dual-line laser sensor emitting a laser to the left. The infrared camera module captures the image of the laser reflection. Therefore, mounting the dual-line laser sensor on both sides of the infrared camera module not only minimizes blind spots but also makes it more consistent with the triangulation principle, thereby improving measurement accuracy. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the present invention and, together with the description, serve to explain the principles of the present invention.

[0025] Figure 1 A partial structural schematic diagram of a robot provided by this utility model;

[0026] Figure 2 A positional structure distribution diagram of a robot provided by this utility model;

[0027] Figure 3 A schematic diagram of the structure of a robot provided by this utility model;

[0028] Figure 4 A schematic diagram of an application scenario provided by this utility model;

[0029] Figure 5 A flowchart illustrating a robot control method provided by this utility model;

[0030] Figure 6 A flowchart illustrating another robot control method provided by this utility model;

[0031] Figure 7 A schematic diagram of the structure of a robot control device provided by this utility model;

[0032] Figure 8 A schematic diagram of another robot control device provided by this utility model;

[0033] Figure 9 This is a schematic diagram of the structure of an electronic device provided by this utility model.

[0034] The accompanying drawings have illustrated specific embodiments of the present invention, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the present invention in any way, but rather to illustrate the concept of the present invention to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0035] To facilitate a clear description of the technical solution of this utility model, the terms "first" and "second" are used in the embodiments of this utility model to distinguish identical or similar items with essentially the same function and effect. For example, "first device" and "second device" are merely used to distinguish different devices and do not limit their order of execution. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0036] It should be noted that in this utility model, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in this utility model should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0037] In this invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0038] In related technologies, LDS components are usually installed on top of the robot vacuum cleaner, increasing the overall height of the robot vacuum cleaner. This makes it impossible for the robot vacuum cleaner to enter and clean low areas, such as under furniture and under sofas, which limits the application range of the robot.

[0039] However, the challenge of reducing the fuselage height lies in how to redesign the layout and installation of the LDS components while ensuring that their ranging and mapping capabilities are not affected.

[0040] To address the aforementioned problems, this utility model provides a robot designed to solve the increased height issue caused by the LDS (Local Distributor) being installed on the top of traditional robotic vacuum cleaners. To this end, the LDS is redesigned and installed at the center of the front side of the robot body, rather than on the top. This layout effectively reduces the overall height of the robot, allowing it to more easily access low-ceilinged areas. Furthermore, when the LDS is installed on the top, blind spots can easily occur due to partial obstruction by the robot body. By installing the LDS at the center of the front side of the robot body, the maximum field of view can be obtained, reducing blind spots. Moreover, since the field of view is better the closer to the center of the front side, the AI ​​camera module and infrared camera module are placed... By placing the dual-line laser sensor at any position near the front center, i.e., on any side around the LDS, the accuracy of data acquisition by the AI ​​camera module and the infrared camera module is higher. Furthermore, the combination of the dual-line laser sensor and the infrared camera module can provide more accurate distance measurement and obstacle detection functions. The lasers emitted by the dual-line laser sensor are crossed, i.e., the dual-line laser sensor on the left emits a laser to the right, and the dual-line laser sensor on the right emits a laser to the left. The infrared camera module is used to capture the image of the laser reflection. Therefore, installing the dual-line laser sensor on the left and right sides of the infrared camera module not only minimizes the blind zone to the greatest extent, but also makes it more in line with the triangulation principle, thereby improving the measurement accuracy.

[0041] In summary, by placing the LDS at the center of the front of the robot body, and combining the collaborative work of the AI ​​camera module, infrared camera module, and dual-line laser sensor under the above structural layout, the robot can perform environmental modeling and path planning more quickly and accurately. This layout allows the robot to adjust its position and path more flexibly when facing complex environments, and it performs particularly well in cleaning tasks in low-ceilinged areas.

[0042] Furthermore, traditional LDS are usually mounted on top of the robot and require 360-degree rotation to scan the surrounding environment. However, by moving the LDS to the center of the front of the robot, the design no longer requires a complex rotating structure. This not only simplifies the mechanical design and saves a significant amount of space inside the robot, but also reduces the wear and maintenance needs of moving parts.

[0043] Therefore, this invention integrates components such as LDS, AI camera module, infrared camera module and dual-line laser sensor together, which reduces the height of the robot and saves internal space, allowing it to accommodate more other devices, improving design redundancy. Furthermore, this multi-module integration facilitates unified software management and resource allocation, saves space, and makes the software more flexible in allocating hardware resources, thereby improving operating efficiency.

[0044] For example, Figure 1 This is a partial structural diagram of a robot provided by this utility model, such as... Figure 1 As shown, the robot 100 includes: a laser rangefinder LDS 102, an artificial intelligence (AI) camera module 103, an infrared camera module 104, and a dual-line laser sensor 105 located on the side of the body 101; the LDS 102 is located at the center of the front side of the body 101, the AI ​​camera module 103 and the infrared camera module 104 are located on either side of the LDS 102, and the dual-line laser sensor 105 is located on the left and right sides of the infrared camera module 103.

[0045] The LDS102 is used to measure the distance to surrounding objects. By emitting a laser and measuring its return time, the LDS102 can accurately calculate the distance to the object. Therefore, the LDS102 can be used for mapping, positioning and navigation based on the acquired second sensor data. Optionally, the LDS102 can be a C91S lidar, a time-of-flight (ToF) sensor, a pulsed laser sensor, etc. This utility model does not specifically limit the type of LDS102.

[0046] The AI ​​camera module 103 combines computer vision technology to identify and analyze objects and scenes in the environment. Therefore, the AI ​​camera module 103 can be used to identify the type of obstacle and the type of dirt in the area in front of it based on the image data. Optionally, the AI ​​camera module 103 can be an AI camera. This utility model does not specifically limit the type of AI camera module 103.

[0047] The dual-line laser sensor 105 consists of two laser sensors. The dual-line laser sensor 105 can provide a wider field of view and higher measurement accuracy. The dual-line laser sensor 105 is usually used in conjunction with an infrared camera module 104. The dual-line laser sensor 105 is used to emit a laser beam to an object such as an obstacle in the front area. The infrared camera module 104 is used to capture the infrared image corresponding to the reflection of the laser beam and determine the first sensor data.

[0048] In addition, the infrared camera module 104 can also be used to determine the type of stain in the area in front based on the identified infrared image. Optionally, the infrared camera module 104 can be an infrared camera, and the dual-line laser sensor 105 can be a dual-line triangulation sensor. This utility model does not specifically limit the types of the infrared camera module 104 and the dual-line laser sensor 105.

[0049] It should be noted that the LDS102, AI camera module 103, infrared camera module 104, and dual-line laser sensor 105 are all located at the front of the body 101 and are close to each other, thus achieving a high degree of integration and facilitating installation.

[0050] For example, Figure 2 A positional structure distribution diagram of a robot provided by this utility model, such as Figure 2 As shown in the top view of robot 100, region C is the front center of the body 101, region A is the left side of the body 101, and region B is the right side of the body 101. Correspondingly, the dual-line laser sensor 105 is located on the left and right sides of the infrared camera module 104, which is located on either side closer to region C. For example, if the infrared camera module 104 is located in region A, the dual-line laser sensor 105 can be located in either region A or region B, or simultaneously in region A. This invention does not limit the specific distribution of the dual-line laser sensor 105.

[0051] Optionally, the AI ​​camera module 103 and the infrared camera module 104 can be located at any position on the side of the LDS 102. They can be simultaneously on the right side, simultaneously on the left side, or separately on the left and right sides. This utility model does not limit the specific distribution position of the AI ​​camera module 103 and the infrared camera module 104.

[0052] As can be seen from the above embodiments, placing the LDS102 at the front center of the body 101, rather than at the top, can effectively reduce the overall height of the robot 100. This allows the robot 100 to more easily enter low-lying areas, such as under furniture and sofas, for cleaning, thus expanding its application range. It should be noted that the LDS102 is located at the front center to obtain the maximum field of view, enabling it to directly perceive environmental information in front and provide accurate distance measurement. The AI ​​camera module 103 and the infrared camera module 104 are located on either side of the LDS102 to ensure a sufficient field of view and improve measurement accuracy. The dual-line laser sensor 105 is located on the left and right sides of the infrared camera module 104, making it more in line with the triangulation principle and ensuring a relatively balanced field of view on both sides, thereby enhancing the lateral environmental perception capability and providing a wider field of view and higher measurement accuracy.

[0053] It should also be noted that since the components LDS102, AI camera module 103, infrared camera module 104 and dual-line laser sensor 105 are located close to each other, material compatibility needs to be considered when selecting materials. Therefore, it is advisable to choose a supplier that can provide a variety of sensors and modules, which can simplify the procurement process and make material preparation more convenient.

[0054] Optional, Figure 3 A schematic diagram of the structure of a robot provided by this utility model, such as... Figure 3 As shown, the dual-line laser sensors 105 are symmetrically distributed on the left and right sides of the LDS102.

[0055] In this invention, the dual-line laser sensors 105 are located on both sides of the center of the body 101, symmetrically distributed and spaced at a certain distance, so as to achieve the best ranging effect and the smallest recognition blind zone.

[0056] Understandably, the symmetrically distributed dual-line laser sensors 105 can provide a wider field of view coverage, ensuring effective distance measurement in the environment in front of and to the sides of the robot 100. Furthermore, through reasonable spacing settings, the overlapping fields of view between the dual-line laser sensors 105 can minimize blind spots, ensuring that the robot 100 can fully perceive surrounding obstacles in complex environments.

[0057] Therefore, the symmetrical layout makes the sensory field of view on both sides of the robot 100 more balanced, ensuring that the robot 100 obtains balanced information input in the left and right directions, thereby enabling it to detect and locate obstacles more accurately and to navigate more stably, especially in narrow or complex paths.

[0058] In addition, the symmetrical design not only provides functional advantages, but also offers a balanced and harmonious aesthetic. Furthermore, the symmetrically distributed dual-line laser sensors 105 provide a certain degree of redundancy, so that even if one sensor fails, the other sensor can still provide the necessary environmental information, enhancing the fault tolerance of the robot 100.

[0059] Optional, such as Figure 3 As shown, the AI ​​camera module 103 and the infrared camera module 104 are located on the same side around the LDS 102. Preferably, the AI ​​camera module 103 and the infrared camera module 104 can be located on the left side or on the right side at the same time. When they are located on the same side, they can be distributed vertically to facilitate installation and make the robot 100 more symmetrical and coordinated in the vertical direction, thereby enhancing the visual appeal of the product.

[0060] In this invention, placing the AI ​​camera module 103 and the infrared camera module 104 on the same side of the LDS 102 enables a more compact design. This integrated layout helps reduce the overall size and weight of the robot 100, improves its flexibility and mobility, and makes assembly easier.

[0061] Furthermore, concentrating the modules on the same side simplifies internal wiring, thereby reducing manufacturing complexity and cost. Also, concentrating the AI ​​camera module 103 and the infrared camera module 104 on one side ensures that they have a consistent viewing angle, reducing the data processing complexity caused by viewing angle differences. Therefore, integrating the AI ​​camera module 103 and the infrared camera module 104 on the same side makes it easier for the robot 100 to perform data fusion, providing a more comprehensive environmental perception capability by combining visual and infrared information.

[0062] Optional, such as Figure 3 As shown, the robot 100 also includes a fill light 106 located between the infrared camera module 104 and the dual-line laser sensor 105.

[0063] In this invention, two supplementary lights 106 can be provided. When the detection environment is relatively dark, the supplementary lights 106 can be turned on to illuminate the detection space so that other modules or sensors can better identify the detection object. For example, the dual-line laser sensor 105 can better identify obstacles.

[0064] It should be noted that the present invention does not specify the number of supplementary lights 106. For example, there may be two or more supplementary lights 106 located between the infrared camera module 104 and the dual-line laser sensor 105.

[0065] Since the supplementary light 106 can provide additional illumination in low-light environments, it significantly improves the image quality captured by the AI ​​camera module 103 and the infrared camera module 104. This helps improve the accuracy of object recognition and classification. By improving lighting conditions, the supplementary light 106 can also help the sensor to measure distances and identify objects more accurately, especially in complex or dynamic environments. Therefore, the illumination provided by the supplementary light 106 enables the sensor and module to work together better, providing a more comprehensive environmental perception capability. Furthermore, better visual information and distance measurement help the robot 100 to perform more accurate path planning, avoid obstacles, and improve navigation efficiency.

[0066] In addition, the use of supplemental lighting 106 in low-light conditions can reduce the risk of accidental collisions and improve the operational safety of robot 100.

[0067] Optional, such as Figure 3 As shown, the robot 100 also includes a voice module 107 located on the top of the body 101. The voice module 107 is used to receive voice commands to control the robot 100 to perform corresponding operations.

[0068] It should be noted that in the prior art, in addition to setting the LDS module on the top of the device, a voice module is also set. The LDS module originally generated noise when running on the top of the device. However, in this utility model, by removing the LDS module and setting the LDS102 at the front center of the device 101, the noise generated by the original LDS module running on the top of the device is greatly reduced, thereby reducing interference with the voice module 107. The original LDS module integrated a rotating mechanism, but the LDS102 in this utility model does not need to be set with a rotating mechanism, thus simplifying the structural setting of the LDS102.

[0069] For example, users can interact with the robot through voice commands. When a user issues a voice command, the voice module 107 receives the voice command and controls the robot to perform corresponding actions, such as cleaning, moving, or obstacle avoidance.

[0070] Therefore, by moving LDS102 to the center of the front side of the body 101, away from the voice module 107, noise interference to the voice module 107 can be significantly reduced. Reducing noise interference helps improve the recognition accuracy of the voice module 107, enabling it to receive and process user voice commands more reliably. In turn, more accurate voice recognition can improve the response speed of the robot 100, allowing the robot 100 to execute user commands more quickly.

[0071] For example, Figure 4 A schematic diagram of an application scenario provided by this utility model, such as Figure 4As shown, taking robot 100 performing a cleaning task as an example, the LDS of robot 100 is set close to or at the center of the body. The outer side of the LDS is an AI camera or an infrared camera, and the outermost side is a dual-line laser sensor. This application scenario includes robot 100 and TV cabinet 200.

[0072] During the cleaning process, the robot 100 can clean the area under the TV cabinet 200 by placing the LDS, AI camera, infrared camera and dual-line laser sensor on the side of the robot body, thereby improving the overall cleaning effect of the room.

[0073] It should be noted that robot 100 can be a cleaning robot such as a sweeping robot, an industrial mobile robot such as a material handling robot, a service robot such as a navigation robot, a detection and search and rescue robot, etc. This utility model does not specifically limit the type of robot.

[0074] It is understood that different types of robots can be applied to different application scenarios. This utility model does not specifically limit the application scenarios of the robot. The above are just examples. For example, it can also be applied to mapping scenarios, navigation scenarios, and search and rescue scenarios.

[0075] The control method for applying robots will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this utility model will now be described with reference to the accompanying drawings.

[0076] Figure 5 This is a flowchart illustrating a robot control method provided by this utility model, as shown below. Figure 5 As shown, the robot control method is applied to Figure 1 or Figure 3 The robot shown; the robot control method includes the following steps:

[0077] S501. During the robot's execution of the target task, the first height of the obstacle in the area in front is determined based on the first sensor data collected by the infrared camera module and the dual-line laser sensor; the dual-line laser sensor is used to emit a laser beam to the obstacle, and the infrared camera module is used to capture the infrared image corresponding to the reflection of the laser beam and determine the first sensor data.

[0078] Optionally, the target task can be any one of cleaning, navigation, mapping, or positioning tasks, and this utility model does not specifically limit it.

[0079] In this invention, the infrared image acquired by the infrared camera module contains information about laser reflection. Therefore, by analyzing the infrared image, the position and shape of the laser line on the obstacle can be determined. Then, based on the positional changes of the laser line in the image, combined with the known laser emission angle and the position of the dual-line laser sensor, the first height of the obstacle can be calculated.

[0080] S502. Determine a first obstacle avoidance strategy based on the first height, and control the robot to perform corresponding obstacle avoidance operations based on the first obstacle avoidance strategy.

[0081] Optionally, obstacles can be classified according to a preset height threshold, such as low obstacles, medium-height obstacles, and tall obstacles. Based on the obstacle height classification, different obstacle heights correspond to different obstacle avoidance strategies. For example, the obstacle avoidance strategy for low obstacles is to choose to cross or pass directly, the obstacle avoidance strategy for medium-height obstacles is to choose to detour or adjust the path, and the obstacle avoidance strategy for tall obstacles is to choose to stop and replan the path. This utility model does not specifically limit the obstacle avoidance strategies corresponding to obstacles of different heights.

[0082] For example, the height category of the obstacle is determined based on the first height of the obstacle, and then a suitable first obstacle avoidance strategy is determined based on the determined height category. Furthermore, the robot generates specific control instructions according to the selected first obstacle avoidance strategy to control the robot to perform the corresponding obstacle avoidance operation.

[0083] Optionally, during obstacle avoidance, the robot can continuously monitor changes in the surrounding environment and adjust its obstacle avoidance operations in real time to adapt to the dynamic environment.

[0084] Optionally, if the first height of an obstacle is determined to be greater than a preset threshold, such as 5cm, the robot is controlled to bypass the obstacle. If the first height of an obstacle is determined to be less than or equal to the preset threshold, the robot is controlled to cross the obstacle. This invention does not specifically limit the size of the preset threshold, which can be set based on the actual application scenario requirements.

[0085] Optionally, the combination of the dual-line laser sensor and the infrared camera module can also identify the height and type of steps, including horizontal steps, multi-level steps, sliding rails, and the height of each step, and then determine the first obstacle avoidance strategy based on the identified step height and type.

[0086] In this way, by using a dual-line laser sensor to provide high-precision distance and height measurements, combined with the image capture capability of an infrared camera module, the height of obstacles can be accurately identified. This allows the robot to effectively avoid potential collision risks, improving obstacle avoidance efficiency while ensuring safety. Therefore, this method enables the robot to perform tasks more intelligently and efficiently, especially when dealing with complex environments and diverse obstacles. It is more accurate than obstacle avoidance methods that use LDS or AI camera modules to identify obstacles.

[0087] Optionally, the method also includes:

[0088] When the first sensor data is detected to be inconsistent with the preset conditions, the second height of the obstacle is determined based on the second sensor data collected by LDS, and / or the type of obstacle is determined based on the image data identified by the AI ​​camera module;

[0089] A second obstacle avoidance strategy is determined based on the second height and / or the type of obstacle, and the robot is controlled to perform corresponding obstacle avoidance operations based on the second obstacle avoidance strategy.

[0090] In this invention, the LDS can emit downward-sloping light rays. The angle between the downward light rays and the horizontal line of the machine body parallel to the surface to be cleaned is α, where α can be 10°. This light ray is used to detect obstacles, such as detecting the second height of the obstacle. This invention does not specifically limit the value of α, but can determine it based on the product's design requirements and performance.

[0091] Optionally, the field of view of the light emitted by the LDS is at an angle b in the horizontal direction, and b can be 120°. This horizontal direction is parallel to the surface to be cleaned, and the emitted light is symmetrical about the center of the machine. This utility model does not specifically limit the value of b, and it can be determined based on the product design requirements and product performance.

[0092] In this invention, LDS can detect point cloud data based on emitted light, and use the point cloud data for mapping, positioning, and navigation.

[0093] Optionally, the AI ​​camera module is used to identify objects in front, such as determining the type of obstacles in the area in front based on the identified image data, or determining the type of dirt on the surface to be cleaned in the area in front based on the identified image data. The image data can be grayscale images, color images, etc., and this utility model does not specifically limit it in this regard.

[0094] Different obstacle types can be set with different obstacle avoidance strategies, and different obstacles have different avoidance distances. For example, for living obstacles such as pets and wire harnesses or obstacles that are easy to get tangled in, the corresponding obstacle avoidance strategy is to avoid the obstacle at a certain distance; for fixed obstacles such as table and chair legs, the corresponding obstacle avoidance strategy is to avoid the obstacle when getting close.

[0095] Optionally, determining the second obstacle avoidance strategy based on the second height of the obstacle determined by the second sensor data collected by LDS is considered backup scheme one; determining the second obstacle avoidance strategy based on the type of obstacle determined by the image data identified by the AI ​​camera module is considered backup scheme two; and combining the above two schemes is considered backup scheme three. In this way, when there are problems with the first sensor data collected by the infrared camera module and the dual-line laser sensor, the system can flexibly switch to backup scheme one, backup scheme two, or backup scheme three based on the application scenario requirements, thereby improving the flexibility of the application.

[0096] For example, the robot first uses first sensor data collected by an infrared camera module and a dual-line laser sensor to detect the first height of an obstacle. If the first sensor data does not meet preset conditions, such as incomplete or inaccurate data, the robot identifies possible anomalies. In this case, some functions in the LDS are activated to determine the second height of the obstacle based on the collected second sensor data, and / or some functions in the AI ​​camera module analyze image data of the surrounding environment to identify the type of obstacle. Further, a second obstacle avoidance strategy is determined based on the second height and / or the type of obstacle, and the robot is controlled to perform corresponding obstacle avoidance operations according to the second obstacle avoidance strategy to ensure safe and effective avoidance of obstacles.

[0097] It should be noted that the preset conditions are set to determine that the first sensor data is inaccurate. For example, if the first sensor data is not collected due to a malfunction of the infrared camera module or the dual-line laser sensor, or if the first sensor data is not collected, the first sensor data is determined to be inconsistent with the preset conditions. This utility model does not limit the specific content corresponding to the preset conditions.

[0098] Therefore, when the robot detects an abnormality in an obstacle, it can quickly switch to a backup plan, namely using LDS or AI camera modules for obstacle avoidance. This redundant design improves the overall reliability of the robot, ensuring the continuity and stability of obstacle avoidance tasks.

[0099] Optionally, a first obstacle avoidance strategy is determined based on the first height, including:

[0100] The second height of the obstacle is determined based on the second sensor data collected by LDS, and the type of obstacle is determined based on the image data identified by the AI ​​camera module;

[0101] The first obstacle avoidance strategy is determined based on the first height, the second height, and the type of obstacle.

[0102] In this step, the AI ​​camera module determines the type of obstacle, the infrared camera module and the dual-line laser sensor combine to determine the height of the obstacle, and the LDS determines the distance between the obstacle and the robot. By fusing the obstacle type, height, distance, etc. together, detailed obstacle information can be determined. Detailed obstacle information helps the robot better understand the surrounding environment, and then uses this detailed obstacle information to determine a more accurate first obstacle avoidance strategy.

[0103] By combining data from multiple sensors, the height and type of obstacles can be measured more accurately, improving detection precision and reliability. Moreover, multi-sensor data provides comprehensive environmental information, enabling robots to better understand and cope with complex scenarios. Therefore, by combining height and type information for obstacle avoidance, more precise obstacle avoidance strategies can be formulated with higher accuracy, reducing unnecessary actions and improving efficiency. Furthermore, more accurate obstacle identification and strategy formulation help avoid potential collision risks, thereby improving the flexibility and safety of obstacle avoidance.

[0104] Optionally, the method also includes:

[0105] The type of dirt in the area in front is determined based on image data identified by the AI ​​camera module;

[0106] Based on the type of dirt, a first cleaning strategy is determined during the obstacle avoidance operation, and the robot is controlled to clean the surface to be cleaned in the area in front based on the first cleaning strategy.

[0107] Different types of dirt may require different cleaning strategies, such as vacuuming, wiping, and mopping. Optionally, the types of dirt may include solid dirt, wet dirt, dust dirt, and mixed solid-liquid dirt. This utility model does not make specific limitations on the classification of dirt types.

[0108] In this invention, the robot's next action can be determined based on the image data recognized by the AI ​​camera module, i.e., whether to perform obstacle-crossing action or to implement different cleaning strategies, such as directly cleaning or bypassing stains, or performing obstacle avoidance actions while cleaning, thereby improving the cleaning effect.

[0109] For example, the AI ​​camera module captures image data of the area in front and analyzes this data through image recognition algorithms to identify the type of dirt on the surface to be cleaned, such as dust, liquid stains, solid waste, etc. Furthermore, based on the identified type of dirt, a corresponding first cleaning strategy is formulated, and then combined with obstacle avoidance operations, the cleaning path and method are optimized, so that the robot can clean the surface to be cleaned in the area in front according to the first cleaning strategy to improve cleaning efficiency and effect.

[0110] Optionally, for the location of obstacles such as pets or humanoid figures, a dynamic re-scanning strategy can be adopted, that is, after the obstacle leaves the location, the robot is controlled to return to the location to perform re-scanning.

[0111] In this way, by identifying the type of dirt through the AI ​​camera module, the robot can adopt appropriate cleaning strategies to ensure the effective removal of different types of stains, improve the cleaning effect, and clean the surface to be cleaned in the area in front of it while avoiding obstacles. The robot can plan its path more intelligently to ensure that all areas are effectively cleaned without having to repeatedly cover already cleaned areas, reducing unnecessary stops and path adjustments during the robot's work, thereby improving the overall cleaning efficiency.

[0112] Furthermore, through intelligent obstacle avoidance, the robot can better approach edge and corner areas, ensuring that these areas, which are usually difficult to clean, are also effectively covered. Especially in dynamic environments, such as homes with pets or children, the robot can flexibly cope with constantly changing obstacles while continuing to perform cleaning tasks, enhancing its adaptability and obstacle avoidance flexibility. Moreover, by reducing unnecessary movement and path adjustments, the robot can also reduce energy consumption, thereby extending battery life and working time.

[0113] Optionally, the method also includes:

[0114] The type of stain in the area in front is determined based on the infrared image identified by the infrared camera module;

[0115] Based on the type of stain, a second cleaning strategy is determined when performing obstacle avoidance operations, and the robot is controlled to clean the surface to be cleaned in the area in front based on the second cleaning strategy.

[0116] In this invention, the infrared camera module can capture infrared images of the area in front. The data in the infrared images can reveal temperature differences and surface features that are invisible to the naked eye. Furthermore, by analyzing the temperature distribution and reflection characteristics in the infrared images, different types of stains, such as liquid stains, can be identified. Therefore, the infrared camera module can also be used to identify liquid stains, which facilitates robot identification and determination of cleaning strategies.

[0117] For example, the robot uses an infrared camera module to scan the area in front of it and capture infrared images. By analyzing the temperature distribution and reflection characteristics in the infrared images, it can identify different types of stains. Furthermore, based on the identified stain types, it selects a corresponding second cleaning strategy. The robot can then clean the surface to be cleaned in the area in front of it according to the second cleaning strategy. During the cleaning process, it performs corresponding obstacle avoidance operations according to the first obstacle avoidance strategy.

[0118] Because infrared images can reveal temperature differences and surface features, robots can more accurately identify stain types and ensure the adoption of appropriate cleaning strategies. Therefore, by combining infrared images to identify stain types in real time, robots can dynamically adjust their cleaning strategies, enabling them to efficiently handle different types of stains while avoiding obstacles. This not only improves the overall cleaning effect but also enhances the robot's adaptability to different environments.

[0119] However, for robot mapping, mapping can also be based on the robot's structure as described above. For example, Figure 6 A flowchart illustrating another robot control method provided by this utility model is shown below. Figure 6 As shown, the robot control method is applied to Figure 1 or Figure 3 The robot shown; the robot control method includes the following steps:

[0120] S601. During the process of the robot performing the target task, the first positioning result is determined based on the second sensor data collected by LDS, and the second positioning result is determined based on the image data recognized by the AI ​​camera module.

[0121] In this step, the target task refers to the mapping task. Thus, the LDS emits a laser beam to measure the distance to the surrounding environment and generate second sensor data of the environment. This second sensor data is used to determine the robot's position and posture, forming a first localization result. The AI ​​camera module captures image data of the environment and analyzes the image data through image recognition algorithms to identify feature points and landmarks in the environment, forming a second localization result.

[0122] For example, LDS transmits the acquired second sensor data to a Simultaneous Localization and Mapping (SLAM) node, so that the SLAM node processes the second sensor data to determine a first localization result. Correspondingly, the AI ​​camera module transmits the recognized image data to the SLAM node, so that the SLAM node processes the image data to determine a second localization result.

[0123] It should be noted that the modules or nodes for determining the first and second positioning results in this utility model are not specifically limited. Optionally, the LDS includes a first SLAM module for determining the first positioning result based on the second sensor data, and the AI ​​camera module includes a second SLAM module for determining the second positioning result based on the image data.

[0124] The process of determining the first localization result includes: based on LDS point cloud data, the robot can construct a map of the surrounding environment and determine its position and orientation in the environment by matching the current point cloud with the known map to obtain the first localization result; the second sensor data is point cloud data.

[0125] The process of determining the second positioning result includes: using image data identified by the AI ​​camera module, the robot can identify specific environmental features, further calibrate and confirm its position, and obtain the second positioning result.

[0126] Optionally, the robot can update its positioning results in real time to quickly respond to environmental changes and improve its adaptability in dynamic environments.

[0127] S602. Merge the first and second positioning results to construct a grid map.

[0128] Optionally, the grid map is updated in real time based on the first and second localization results of different frames, thereby reflecting the dynamic changes in the environment and enabling the robot to quickly adapt to new situations.

[0129] For example, the first and second positioning results are transformed into the same coordinate system to ensure that the two types of data can be compared and fused under the same spatial reference frame. Then, under the unified coordinate system, common features in the first and second positioning results are identified and matched. The feature information in the first positioning result is used to correct the error in the second positioning result, thereby improving the positioning accuracy. Finally, the corrected data is converted into a raster map.

[0130] It should be noted that this utility model does not limit the specific process of fusing the first positioning result and the second positioning result; the above is merely an example.

[0131] Optionally, a first positioning result is determined based on the second sensor data collected by LDS, and a grid map is constructed based on the first positioning result. If the first positioning result does not meet the predefined conditions, a second positioning result is determined using image data recognized by the AI ​​camera module, and a grid map is constructed based on the second positioning result.

[0132] The predefined conditions can include data loss, excessive noise, signal interference, or inability to accurately determine the pose of the data. This utility model does not impose specific limitations on the predefined conditions.

[0133] Therefore, by combining data from LDS and AI camera modules, this invention can provide more accurate positioning results, reduce errors that may be caused by a single sensor, and further correct errors that may be caused by a single sensor through data fusion, thereby improving the accuracy of overall positioning and map building. More accurate grid map construction helps optimize path planning, reduce unnecessary detours and stops, and improve task execution efficiency. In addition, through accurate environmental perception and map building, the robot can perform tasks more safely and avoid collisions and other potential risks.

[0134] In the foregoing embodiments, the robot control method provided by this utility model has been described. To achieve the functions of the method provided by this utility model, the robot, as the executing entity, may include hardware structures and / or software modules, implementing the aforementioned functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0135] For example, Figure 7 This is a schematic diagram of the structure of a robot control device provided by this utility model, as shown below. Figure 7 As shown, the robot includes: a laser rangefinder (LDS), an artificial intelligence (AI) camera module, an infrared camera module, and a dual-line laser sensor located on the side of the robot body; the LDS is located at the center of the front side of the robot body, the AI ​​camera module and the infrared camera module are located on either side of the LDS, and the dual-line laser sensor is located on the left and right sides of the infrared camera module; the robot control device 700 includes:

[0136] The first determining module 701 is used to determine the first height of obstacles in the area in front of the robot based on the first sensor data collected by the infrared camera module and the dual-line laser sensor during the robot's execution of the target task; the dual-line laser sensor is used to emit a laser beam, the infrared camera module is used to capture the infrared image corresponding to the laser beam, and determine the first sensor data;

[0137] The control module 702 is used to determine a first obstacle avoidance strategy based on a first height, and control the robot to perform corresponding obstacle avoidance operations based on the first obstacle avoidance strategy.

[0138] Optionally, the robot control device 700 further includes a third determining module, which is used for:

[0139] When the first sensor data is detected to be inconsistent with the preset conditions, the second height of the obstacle is determined based on the second sensor data collected by LDS, and / or the type of obstacle is determined based on the image data identified by the AI ​​camera module;

[0140] A second obstacle avoidance strategy is determined based on the second height and / or the type of obstacle, and the robot is controlled to perform corresponding obstacle avoidance operations based on the second obstacle avoidance strategy.

[0141] Optional, control module 702, specifically used for:

[0142] The second height of the obstacle is determined based on the second sensor data collected by LDS, and the type of obstacle is determined based on the image data identified by the AI ​​camera module;

[0143] The first obstacle avoidance strategy is determined based on the first height, the second height, and the type of obstacle.

[0144] Optionally, the robot control device 700 further includes a first cleaning module, which is used for:

[0145] The type of dirt in the area in front is determined based on image data identified by the AI ​​camera module;

[0146] Based on the type of dirt, a first cleaning strategy is determined during the obstacle avoidance operation, and the robot is controlled to clean the surface to be cleaned in the area in front based on the first cleaning strategy.

[0147] Optionally, the robot control unit 700 further includes a second cleaning module, which is used for:

[0148] The type of stain in the area in front is determined based on the infrared image identified by the infrared camera module;

[0149] Based on the type of stain, a second cleaning strategy is determined when performing obstacle avoidance operations, and the robot is controlled to clean the surface to be cleaned in the area in front based on the second cleaning strategy.

[0150] It should be noted that the specific implementation principle and effect of the above-mentioned robot control device can be found in the relevant description and effect of the above embodiments, and will not be elaborated further here.

[0151] For example, this utility model also provides a robot control device. Figure 8 This is a schematic diagram of another robot control device provided by this utility model, as shown below. Figure 8 As shown, the robot includes: a laser rangefinder (LDS), an artificial intelligence (AI) camera module, an infrared camera module, and a dual-line laser sensor located on the side of the robot body; the LDS is located at the center of the front side of the robot body, the AI ​​camera module and the infrared camera module are located on either side of the LDS, and the dual-line laser sensor is located on the left and right sides of the infrared camera module; the robot control device 800 includes:

[0152] The second determining module 801 is used to determine the first positioning result based on the second sensor data collected by the LDS and to determine the second positioning result based on the image data recognized by the AI ​​camera module during the robot's execution of the target task.

[0153] Module 802 is used to fuse the first and second positioning results to construct a raster map.

[0154] It should be noted that the specific implementation principle and effect of the above-mentioned robot control device can be found in the relevant description and effect of the above embodiments, and will not be elaborated further here.

[0155] This utility model also provides a structural schematic diagram of an electronic device. Figure 9 A schematic diagram of the structure of an electronic device provided by this utility model, such as... Figure 9 As shown, the electronic device may include: a processor 901 and a memory 902 communicatively connected to the processor; the memory 902 stores a computer program; the processor 901 executes the computer program stored in the memory 902, causing the processor 901 to perform the method described in any of the above embodiments.

[0156] The memory 902 and the processor 901 can be connected via bus 903.

[0157] The present invention also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in any of the foregoing embodiments of the present invention.

[0158] This invention also provides a chip for executing instructions, which is used to perform the methods described in any of the foregoing embodiments of this invention as performed by a robot.

[0159] This utility model also provides a computer program product, which includes a computer program that, when executed by a processor, can implement the method described in any of the foregoing embodiments of this utility model as performed by a robot.

[0160] In the several embodiments provided by this utility model, it should be understood that the disclosed apparatus and method can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0161] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0162] Furthermore, in the various embodiments of this utility model, the functional modules can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0163] The integrated modules implemented as software functional modules described above can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this utility model.

[0164] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method described in this utility model can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0165] The memory may include high-speed random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0166] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings of this utility model are not limited to a single bus or a single type of bus.

[0167] The aforementioned storage media can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage media can be any available medium accessible to general-purpose or special-purpose computers.

[0168] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components within a cleaning device or a main control device.

[0169] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0170] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0171] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0172] Other embodiments of the present invention will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments described herein. The present invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art that are not covered by the invention. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

[0173] The above description is merely a specific embodiment of this utility model, but the protection scope of this utility model is not limited thereto. Any changes or substitutions within the technical scope disclosed in this utility model should be included within the protection scope of this utility model. Therefore, the protection scope of this utility model should be determined by the protection scope of the claims.

Claims

1. A robot, characterized in that, The robot comprises a laser ranging sensor (LDS) located on the side of the fuselage, an artificial intelligence (AI) camera module, an infrared camera module and a double-line laser sensor; the LDS is located at the center of the front side of the fuselage, the AI camera module and the infrared camera module are respectively located at any one side position around the LDS, and the double-line laser sensor is located at the left and right sides of the infrared camera module.

2. The robot of claim 1, wherein, The double-line laser sensors are symmetrically distributed at the left and right sides of the LDS.

3. The robot of claim 1, wherein, The AI camera module and the infrared camera module are located at the same side position around the LDS.

4. The robot of claim 1, wherein, The robot further comprises a light supplement lamp located between the infrared camera module and the double-line laser sensor.

5. The robot of claim 1, wherein, The robot further comprises a voice module located at the top of the fuselage, which is used to receive voice instructions to control the robot to perform corresponding operations.

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