Automatic driving system for photovoltaic module laying robot

Abstract

The invention provides an automatic driving system for a photovoltaic module laying robot, which comprises a ground obstacle algorithm module, a power evaluation algorithm module, a self-adaptive track module and an intelligent controllable track suspension module, and is characterized in that the ground obstacle algorithm module is used for identifying an obstacle in front of a walking road surface of the robot in real time; the power evaluation algorithm module is in communication connection with the ground obstacle algorithm module and is used for acquiring driving force according to the position and size of the identified obstacle and the safe walking route; the self-adaptive track module is in communication connection with the ground obstacle algorithm module and is used for adjusting the tension and the grounding area of a track according to the position and the size of an obstacle and the safe driving route; and the intelligent controllable track suspension module is in communication connection with the ground obstacle algorithm module and is used for adjusting the track suspension height and track section suspension sections according to the position and size of the obstacle and the safe driving route. The method can effectively cope with complex terrain environments such as sandstorm grass beaches and depressions, and the assembly laying efficiency is improved.

Description

Technical Field

[0001] This application relates to the technical field of photovoltaic engineering, and particularly to an autonomous driving system for a photovoltaic module laying robot. Background Art

[0002] The laying of photovoltaic modules is one of the key links in the construction of photovoltaic power stations. At present, the laying of photovoltaic modules mainly relies on manual operation, which has problems such as low efficiency and high cost. With the continuous expansion of the scale of photovoltaic power stations, the disadvantages of manual operation have become increasingly prominent.

[0003] In a complex terrain environment, the laying of photovoltaic modules faces greater challenges. Geomorphologies such as sandy grasslands and depressions pose severe tests for the movement of robots. The existing technologies cannot effectively cope with these complex terrains, resulting in low efficiency of photovoltaic module laying. Therefore, there is an urgent need for an autonomous driving system that can overcome complex terrain environments such as sandy grasslands and depressions to improve the efficiency of photovoltaic module laying and reduce labor costs.

[0004] This autonomous driving system can adopt technical means such as an adaptive track module, an intelligent controllable track suspension module, an intelligent robot chassis, a power evaluation algorithm module, and a ground obstacle algorithm module. Through these means, the system can automatically adjust the track tension, ground contact area, and suspension height according to the terrain, has a dust and waterproof function, can evaluate the required power in real time and adjust the power output, identify obstacles and plan a detour route, so as to effectively overcome the complex terrain environment and ensure the efficient laying of photovoltaic modules.

[0005] Regarding the solution to the problem of overcoming complex terrain environments such as sandy grasslands and depressions, there are already some invention patents. For example:

[0006] CN112007890A discloses an AGV cleaning robot applied to the photovoltaic field, including a chassis for walking along a predetermined route, a multi-joint robotic arm, and a cleaning brush assembly. This patent realizes the automatic path-following movement of the robot through the adoption of an autonomous driving sensing system, and through the cooperation of the robotic arm motion control host and the brush sensing system, it realizes that the robot can also adjust the posture of the robotic arm to ensure the cleaning effect of the brush assembly on the photovoltaic panel on an uneven ground surface. However, this patent cannot effectively cope with complex terrain environments such as sandy grasslands and depressions, resulting in low efficiency of photovoltaic module laying.

[0007] CN219666630U discloses an unmanned intelligent installation robot for photovoltaic modules, including an electric crawler chassis mechanism, a vehicle body, a hydraulic support mechanism, and a grasping and installation mechanism. This patent can solve problems such as component hidden cracks and scratches caused by humans during the installation process, as well as the installation efficiency problem caused by the lack of labor, greatly improving the installation efficiency and qualification rate of photovoltaic modules. However, this patent cannot effectively cope with complex terrain environments such as sandy grasslands and depressions, resulting in low laying efficiency of photovoltaic modules.

[0008] The existing photovoltaic laying technology has the following technical problems:

[0009] 1. The laying of photovoltaic modules mainly relies on manual operation, resulting in low efficiency and high costs;

[0010] 2. It lacks the function of an adaptive crawler module to adjust the crawler tension and grounding area, and cannot automatically adjust according to terrain changes;

[0011] 3. The crawler suspension system cannot automatically adjust the suspension height according to the terrain, affecting the driving performance;

[0012] 4. The chassis has poor protection performance and cannot effectively prevent dust and water, affecting the service life of the robot;

[0013] 5. It lacks a power evaluation algorithm module and cannot evaluate the required power in real time and adjust the power output, affecting the driving efficiency;

[0014] 6. It lacks an effective ground obstacle algorithm module, resulting in the inability to identify obstacles and plan a detour route. Summary of the Invention

[0015] This application provides an autonomous driving system for a photovoltaic module laying robot, which can solve the technical problem in the existing photovoltaic module robot that it cannot effectively cope with complex terrain environments such as sandy grasslands and depressions, resulting in low laying efficiency of photovoltaic modules.

[0016] In a first aspect, this application provides an autonomous driving system for a photovoltaic module laying robot, including:

[0017] A ground obstacle algorithm module, used to real-time identify obstacles in front of the robot's walking path, and when an obstacle is identified, plan a safe walking route for the robot according to the position and size of the obstacle;

[0018] A power evaluation algorithm module, communicatively connected to the ground obstacle algorithm module, used to obtain the driving force for the autonomous driving system to travel according to the position and size of the identified obstacle and the safe walking route;

[0019] An adaptive track module, communicatively connected to the ground obstacle algorithm module, for adjusting the tension and ground contact area of the tracks according to the position and size of the obstacles and the safe driving route;

[0020] Communicatively connected to the ground obstacle algorithm module, for adjusting the track suspension height and the suspension segments of the track links according to the position and size of the obstacles and the safe driving route.

[0021] In combination with the first aspect, in an embodiment, the adaptive track module includes a plurality of track segments, and a tension adjusting device is provided on each track segment, and the tension adjusting device is used to adjust the tension and ground contact area of the tracks according to the terrain of the safe driving route.

[0022] In combination with the first aspect, in an embodiment, the tension adjusting device adopts a hydraulic cylinder structure or a pneumatic motor structure.

[0023] In combination with the first aspect, in an embodiment, a plurality of protrusions are provided on the outer surface of the adaptive track module, and the protrusions are in a trapezoidal structure, a triangular structure or a semi-circular structure.

[0024] In combination with the first aspect, in an embodiment, the intelligent controllable track suspension module includes a plurality of independent suspension units, and a height adjusting mechanism is provided on each suspension unit, and the height adjusting mechanism is used to adjust the track suspension height and the suspension segments of the track links according to the position and size of the obstacles and the safe driving route.

[0025] In combination with the first aspect, in an embodiment, the height adjusting mechanism adopts a lead screw lifting structure or a hydraulic cylinder lifting structure.

[0026] In combination with the first aspect, in an embodiment, the intelligent robot chassis adopts a fully sealed design, and a dust removal and filtration system and a waterproof sealing device are provided inside.

[0027] In combination with the first aspect, in an embodiment, the dust removal and filtration system adopts a high-efficiency air filter.

[0028] In combination with the first aspect, in an embodiment, the waterproof sealing device adopts a rubber sealing ring and silicone sealant, a polyurethane sealing ring and nitrile rubber sealant, or a fluororubber sealing ring and silicone rubber sealant.

[0029] In combination with the first aspect, in an embodiment, the ground obstacle algorithm module includes a vision sensor and a lidar on the robot.

[0030] The beneficial effects brought by the technical solutions provided in the embodiments of the present application at least include:

[0031] Laying photovoltaic modules by a robot can effectively cope with complex terrain environments such as sandy grasslands and depressions, ensuring the efficient laying of photovoltaic modules;

[0032] The ground obstacle algorithm module can identify obstacles and plan a safe driving route, ensuring the driving safety of the robot;

[0033] The adaptive track module adapts to the terrain by adjusting the track tension and the grounding area, ensuring the driving stability of the robot;

[0034] The intelligent controllable track suspension module automatically adjusts the track suspension height according to the terrain, improving the obstacle-crossing ability of the robot;

[0035] The power evaluation algorithm module evaluates the power required for the robot to walk safely and adjusts the power output, improving the energy utilization rate. Description of the Drawings

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0037] Figure 1 It is a functional module block diagram of an automatic driving system for a photovoltaic module laying robot provided by the present application;

[0038] Figure 2 It is a schematic diagram of the structure of a robot in an automatic driving system for a photovoltaic module laying robot provided by an embodiment of the present application.

[0039] In the figure: 100, ground obstacle algorithm module; 200, power evaluation algorithm module; 300, adaptive track module; 400, intelligent controllable track suspension module; 500, manipulator. Detailed Embodiments

[0040] In order to enable those skilled in the art to better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0041] In the first aspect, as Figure 1As shown in the figure, the present application provides an autonomous driving system for a photovoltaic module laying robot, including a ground obstacle algorithm module 100, a power evaluation algorithm module 200, an adaptive track module 300, and an intelligent controllable track suspension module 400. The ground obstacle algorithm module 100 is used to identify obstacles in front of the robot's walking path in real time. When an obstacle is identified, it plans a safe walking route for the robot according to the position and size of the obstacle. The power evaluation algorithm module 200 is communicatively connected to the ground obstacle algorithm module 100, and is used to obtain the driving force for the autonomous driving system to travel according to the position and size of the identified obstacle and the safe walking route. The adaptive track module 300 is communicatively connected to the ground obstacle algorithm module 100, and is used to adjust the tension and grounding area of the track according to the position and size of the obstacle and the safe driving route. It is communicatively connected to the ground obstacle algorithm module 100, and is used to adjust the track suspension height and the suspension segment of the track joint according to the position and size of the obstacle and the safe driving route.

[0042] By laying photovoltaic modules with the robot, the present application can effectively cope with complex terrain environments such as sandy grasslands and depressions, ensuring the efficient laying of photovoltaic modules.

[0043] The ground obstacle algorithm module 100 can identify obstacles and plan a safe driving route, ensuring the driving safety of the robot.

[0044] The power evaluation algorithm module 200 evaluates the power required for the robot to walk safely and adjusts the power output, improving the energy utilization rate.

[0045] The adaptive track module 300 adapts to the terrain by adjusting the track tension and grounding area, ensuring the driving stability of the robot.

[0046] The intelligent controllable track suspension module 400 automatically adjusts the track suspension height according to the terrain, improving the obstacle-crossing ability of the robot.

[0047] In an embodiment, as Figure 2 shown, an autonomous driving system for a photovoltaic module laying robot provided by the present application includes carrying a robot to lay photovoltaic modules. A manipulator 500 is installed on the robot, which is used to grasp the photovoltaic modules and perform mobile laying under the action of electric control.

[0048] In an embodiment, the ground obstacle algorithm module 100 uses a vision sensor and a lidar on the robot to obtain surrounding environment information, detect and identify obstacles. The vision sensor uses a 1080P high-definition camera, a 4K ultra-high-definition camera, or a binocular stereo vision camera. The scanning range of the lidar is 200 meters to 500 meters, and the resolution is 2 centimeters to 5 centimeters.

[0049] In one embodiment, the driving force evaluation algorithm module 200 comprehensively calculates the driving force of the autonomous driving system based on the obstacles, safe driving routes, slip ratio of the crawlers, ground slope, load weight, temperature, wind speed, battery power, etc. identified by the ground obstacle algorithm module 100. Among them, the relationship between the obstacles, safe driving routes, slip ratio of the crawlers, ground slope, load weight, temperature, wind speed, and battery power is an AND / OR relationship. For example, when the size or position of the identified obstacle is not sufficient to cause the robot's driving route to be re-planned, the current driving route of the robot is used as the safe driving route, and the driving force evaluation algorithm module does not need to consider the position or size of the obstacle; when the size of the identified obstacle exceeds the size threshold that causes the robot to encounter driving obstacles or the position and size of the obstacle will cause the robot to drive unstably, it is necessary to bypass the obstacle and re-plan the safe driving route of the robot. In this case, the driving force evaluation algorithm module does not consider the size and position of the obstacle, but mainly considers the re-planned safe driving route; alternatively, the driving force evaluation algorithm module 200 can also consider the environmental temperature, wind speed, and even battery power to comprehensively calculate the driving force required for the autonomous driving system.

[0050] In one embodiment, the adaptive crawler module 300 includes a plurality of crawler segments, and a tension adjusting device is arranged on each crawler segment. The tension adjusting device is used to adjust the tension and ground contact area of the crawlers according to the terrain of the safe driving route, so as to adaptively change the tension and ground contact area of the entire crawler.

[0051] In one embodiment, the tension adjusting device adopts a hydraulic cylinder structure or a pneumatic motor structure and can adjust the tension within a predetermined range. The predetermined range is from 3 tons to 12 tons.

[0052] In one embodiment, a plurality of protrusions are arranged on the outer surface of the adaptive crawler module 300. The protrusions are trapezoidal structures, triangular structures, or semi-circular structures, and are used to increase the friction with the ground.

[0053] In one embodiment, the intelligent controllable crawler suspension module 400 includes a plurality of independent suspension units, and a height adjusting mechanism is arranged on each suspension unit. The height adjusting mechanism is used to adjust the crawler suspension height and the suspension segments of the crawler segments according to the position and size of the obstacle and the safe driving route, so as to adaptively change the suspension height of the entire crawler to smoothly cross smaller obstacles.

[0054] In one embodiment, the height adjusting mechanism adopts a lead screw lifting structure or a hydraulic cylinder lifting structure and can adjust the suspension height within a range of 10 cm to 60 cm.

[0055] In one embodiment, the intelligent robot chassis adopts a fully sealed design, and is internally provided with a dust removal and filtration system and a waterproof sealing device. The dust removal and filtration system is used to filter dust particles inside the vehicle body, and the waterproof sealing device is used to prevent moisture from seeping into the vehicle body.

[0056] In one embodiment, the dust removal and filtration system adopts a high-efficiency air filter, which can filter particulate matter with a diameter greater than 0.2 microns, 0.3 microns or 0.5 microns.

[0057] In one embodiment, the waterproof sealing device adopts a rubber sealing ring and silicone sealant, a polyurethane sealing ring and nitrile rubber sealant, or a fluororubber sealing ring and silicone rubber sealant.

[0058] The following gives specific embodiments to further elaborate several different implementation forms of an automatic driving system for a photovoltaic module laying robot provided by the present application:

[0059] Embodiment 1

[0060] An automatic driving system based on a photovoltaic module laying robot includes an adaptive crawler module 300, an intelligent controllable crawler suspension module 400, an intelligent robot chassis, a power evaluation algorithm module 200, a ground obstacle algorithm module 100, etc.

[0061] The adaptive crawler module 300 can automatically adjust the crawler tension and grounding area according to the terrain, improving the driving stability. Specifically, the adaptive crawler module 300 includes a plurality of crawler segments, and each crawler segment is provided with a tension adjusting device, which can automatically adjust the tension of the segment according to the terrain change, so that the tension and grounding area of the entire crawler change adaptively. At the same time, a plurality of protrusions are arranged on the outer surface of the adaptive crawler module 300 to increase the friction with the ground. For example, the adaptive crawler module 300 can be composed of 10 crawler segments, each segment is 50 cm long, and the tension adjusting device adopts a hydraulic cylinder structure, which can adjust the tension in the range of 5 to 10 tons. The protrusions on the outer surface of the crawler are trapezoidal structures, with a height of 2 cm and a spacing of 5 cm.

[0062] The intelligent controllable crawler suspension module 400 can automatically adjust the crawler suspension height according to the terrain, improving the obstacle-crossing ability. The suspension system includes 6 independent suspension units, and each suspension unit is provided with a height adjusting mechanism, which can automatically adjust the suspension height of the unit according to the terrain change, so that the suspension height of the entire crawler changes adaptively. For example, the height adjusting mechanism adopts a lead screw lifting structure, which can adjust the suspension height in the range of 10 cm to 50 cm.

[0063] The intelligent robot chassis adopts a fully sealed design, with a dust removal and filtration system and a waterproof sealing device inside. The dust removal and filtration system uses a high-efficiency air filter, which can filter particulate matter with a diameter greater than 0.3 microns. The waterproof sealing device uses rubber gaskets and silicone sealants to ensure 100% waterproofing inside the vehicle body.

[0064] Based on parameters such as the slip ratio of the crawler, the ground slope, and the load weight, the power evaluation algorithm module 200 calculates the optimal power value required for driving and controls the drive motor to output the corresponding power. For example, when the crawler slip ratio is 10%, the ground slope is 20 degrees, and the load weight is 500 kilograms, the algorithm calculates that the required power is 30 kilowatts and sends this value to the drive motor for power adjustment.

[0065] The ground obstacle algorithm module 100 uses the vision sensors and lidar on the robot to obtain information about the surrounding environment, detect and identify obstacles. Once an obstacle is detected, the algorithm plans a safe detour route based on information such as the position and size of the obstacle. For example, the vision sensor uses a 1080P high-definition camera, and the scanning range of the lidar is 200 meters with a resolution of 5 centimeters. When a stone obstacle with a diameter of 1 meter is detected, the algorithm plans a detour route with a radius of 2 meters.

[0066] Embodiment 2

[0067] An automatic driving system based on a photovoltaic module laying robot includes modules such as an adaptive crawler module 300, an intelligent controllable crawler suspension module 400, an intelligent robot chassis, a power evaluation algorithm module 200, and a ground obstacle algorithm module 100.

[0068] The adaptive crawler module 300 consists of 12 crawler segments, each segment being 40 centimeters long. The tension adjustment device uses a pneumatic motor structure and can adjust the tension in the range of 3 tons to 8 tons. The protrusions on the outer surface of the crawler are triangular structures, with a height of 1.5 centimeters and a spacing of 4 centimeters.

[0069] The intelligent controllable crawler suspension module 400 includes 8 independent suspension units. The height adjustment mechanism uses a hydraulic cylinder lifting structure and can adjust the suspension height in the range of 15 centimeters to 40 centimeters.

[0070] The dust removal and filtration system of the intelligent robot chassis uses a high-efficiency air filter, which can filter particulate matter with a diameter greater than 0.5 microns. The waterproof sealing device uses polyurethane gaskets and nitrile rubber sealants to ensure 100% waterproofing inside the vehicle body.

[0071] The parameters considered by the power evaluation algorithm module 200 also include factors such as ambient temperature and wind speed. For example, when the crawler slip rate is 15%, the ground slope is 25 degrees, the load weight is 600 kg, the ambient temperature is 40 °C, and the wind speed is 5 m / s, the algorithm calculates that the required power is 35 kW and sends this value to the drive motor for power adjustment.

[0072] The vision sensor of the ground obstacle algorithm module 100 uses a 4K ultra-high-definition camera, and the scanning range of the lidar is 300 m with a resolution of 3 cm. When detecting a ditch obstacle with a length of 2 m and a width of 1 m, the algorithm will plan a detour route with a length of 5 m.

[0073] Embodiment III

[0074] An autonomous driving system based on a photovoltaic module laying robot includes modules such as an adaptive crawler module 300, an intelligent controllable crawler suspension module 400, an intelligent robot chassis, a power evaluation algorithm module 200, and a ground obstacle algorithm module 100.

[0075] The adaptive crawler module 300 consists of 8 crawler segments, each segment having a length of 60 cm. The tension adjustment device uses a hydraulic cylinder structure and can adjust the tension in the range of 6 tons to 12 tons. The protrusions on the outer surface of the crawler are semi-circular structures with a height of 2.5 cm and a spacing of 6 cm.

[0076] The intelligent controllable crawler suspension module 400 includes 4 independent suspension units. The height adjustment mechanism uses a lead screw lifting structure and can adjust the suspension height in the range of 20 cm to 60 cm.

[0077] The dust removal and filtration system of the intelligent robot chassis uses a high-efficiency air filter, which can filter particles with a diameter greater than 0.2 microns. The waterproof sealing device uses fluororubber seals and silicone rubber sealants to ensure 100% waterproofing inside the vehicle body.

[0078] The power evaluation algorithm module 200 also considers factors such as battery power. For example, when the crawler slip rate is 20%, the ground slope is 30 degrees, the load weight is 700 kg, and the battery power is 60%, the algorithm calculates that the required power is 40 kW and sends this value to the drive motor for power adjustment.

[0079] The vision sensor of the ground obstacle algorithm module 100 uses a binocular stereo vision camera, and the scanning range of the lidar is 500 m with a resolution of 2 cm. When detecting a grassland obstacle with a width of 3 m, the algorithm will plan a detour route with a width of 5 m.

[0080] In the description of the present application, it should be noted that the orientation or positional relationship indicated by terms such as "upper" and "lower" is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present application. Unless otherwise clearly specified and defined, the terms "installed", "connected" and "coupled" shall be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0081] It should be noted that in the present application, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variation thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

[0082] The above are only specific embodiments of the present application, enabling those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features claimed herein.

Claims

1. An automatic driving system for a photovoltaic module laying robot, characterized in that, Comprising: A ground obstacle algorithm module for real-time identification of obstacles in front of the walking path of the robot. When an obstacle is identified, it plans a safe walking route for the robot according to the position and size of the obstacle. A power evaluation algorithm module communicatively connected to the ground obstacle algorithm module for obtaining the driving force of the autonomous driving system according to the position and size of the identified obstacle and the safe walking route. An adaptive track module communicatively connected to the ground obstacle algorithm module for adjusting the tension and ground contact area of the track according to the position and size of the obstacle and the safe driving route. An intelligent controllable track suspension module communicatively connected to the ground obstacle algorithm module for adjusting the track suspension height and the suspension segment of the track joint according to the position and size of the obstacle and the safe driving route.

2. The automatic driving system for a photovoltaic module laying robot according to claim 1, characterized in that, The adaptive track module includes a plurality of track segments, and a tension adjusting device is arranged on each track segment. The tension adjusting device is used to adjust the tension and ground contact area of the track according to the terrain of the safe driving route.

3. The automatic driving system for a photovoltaic module laying robot according to claim 2, characterized in that, The tension adjusting device adopts a hydraulic cylinder structure or a pneumatic motor structure.

4. The automatic driving system for a photovoltaic module laying robot according to claim 2, characterized in that, A plurality of protrusions are arranged on the outer surface of the adaptive track module, and the protrusions are trapezoidal structures, triangular structures or semi-circular structures.

5. The automatic driving system for a photovoltaic module laying robot according to claim 1, characterized in that, The intelligent controllable track suspension module includes a plurality of independent suspension units, and a height adjusting mechanism is arranged on each suspension unit. The height adjusting mechanism is used to adjust the track suspension height and the suspension segment of the track joint according to the position and size of the obstacle and the safe driving route.

6. The automatic driving system for a photovoltaic module laying robot according to claim 5, characterized in that, The height adjusting mechanism adopts a lead screw lifting structure or a hydraulic cylinder lifting structure.

7. The automatic driving system for a photovoltaic module laying robot according to claim 1, characterized in that, The intelligent robot chassis adopts a fully sealed design, and a dust removal and filtration system and a waterproof sealing device are arranged inside.

8. The automatic driving system for a photovoltaic module laying robot according to claim 7, characterized in that, The dust removal and filtration system adopts a high-efficiency air filter.

9. The automatic driving system for a photovoltaic module laying robot according to claim 7, characterized in that, The waterproof sealing device adopts a rubber sealing ring and silicone sealant, a polyurethane sealing ring and nitrile rubber sealant, or a fluororubber sealing ring and silicone rubber sealant.

10. The automatic driving system for a photovoltaic module laying robot according to claim 1, characterized in that, The ground obstacle algorithm module includes a vision sensor and a lidar on the robot.

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