Mowing robot and control system thereof

Abstract

The invention discloses a mowing robot and a control system thereof, relates to the technical field of mowing robots, and aims at solving the technical problems that a current wheel type mowing robot is poor in terrain adaptability, prone to clamping stagnation in complex terrains and incomplete in operation coverage. Supporting feet are arranged at the bottom of the moving carrier, and a mowing unit and an energy unit are arranged at the tops of the supporting feet. The four-footed mechanical dog is adopted as a mobile carrier, and a path-terrain collaborative optimization algorithm of the dynamic task planning unit is matched, so that the optimal mowing path can be automatically generated based on environment sensing data, gaits are dynamically adjusted according to terrain gradients, the defect that traditional wheel type equipment is poor in terrain adaptability is effectively overcome, and the mowing efficiency is improved. And stable movement and complete operation coverage under complex terrains such as sloping fields and potholes are ensured, and the operation scene range is greatly expanded.

Description

Technical Field

[0001] This invention relates to the field of lawn mowing robot technology, and more specifically, to a lawn mowing robot and its control system. Background Technology

[0002] A lawnmower is a gardening tool used to trim lawns. Traditional lawnmowers primarily use gasoline engines or AC mains power to mow the lawn, relying on human power to propel them back and forth across the lawn to perform the maintenance and trimming. The emergence of lawnmower robots has brought great convenience to users, freeing them from the heavy labor of gardening maintenance.

[0003] Traditional lawnmowers are mostly operated manually, which is not only labor-intensive and inefficient, but also poses operational risks, especially in large lawns or complex terrain areas where their operational limitations are extremely obvious. While wheeled lawnmower robots on the market have achieved basic automation, their terrain adaptability is poor due to their wheeled structure. When facing complex terrains such as slopes, potholes, and grass edges, they are prone to getting stuck, tipping over, or incomplete coverage, and cannot flexibly cope with diverse working environments. In view of this, we propose a lawnmower robot and its control system. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art, adapt to practical needs, and provide a lawn mowing robot and its control system to solve the technical problems of poor terrain adaptability, easy jamming in complex terrain, and incomplete coverage of current wheeled lawn mowing robots.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a lawnmower robot, comprising a mobile carrier and a mounting plate fixedly installed on the top of the mobile carrier. The bottom of the mobile carrier is provided with supporting legs, and the top of the supporting legs is provided with a mowing unit and an energy unit. The mobile carrier and the supporting legs constitute a quadrupedal mechanical dog. The supporting legs are equipped with multi-degree-of-freedom joints for terrain-adaptive gait control. The mowing unit is located on both sides of the torso of the mobile carrier and includes a radially extendable robotic arm and a mowing component located at the end of the robotic arm. The robotic arm has at least three sets of joints, and a joint motor for driving the joint rotation is provided at each joint position. The energy unit includes a support device, and a photovoltaic panel is provided on the top of the support device. The support device has a built-in angle adjustment mechanism that can drive the photovoltaic panel to rotate around the support point to achieve adaptive adjustment of the illumination angle.

[0006] Preferably, an electric push rod is fixedly installed on the top of the mounting plate, the top of the electric push rod is connected to the robotic arm, and a mounting bracket is fixedly installed at the end of the robotic arm. The electric push rod can drive the robotic arm to achieve vertical adjustment.

[0007] Preferably, the mowing assembly is disposed inside the mounting frame, and the mowing assembly includes a cutting blade and a drive motor for driving the cutting blade, wherein the drive motor can dynamically adjust its output power according to control commands.

[0008] Preferably, a force control sensor is installed on the supporting foot to collect force data when the supporting foot contacts the ground, providing a basis for terrain-adaptive gait control.

[0009] A lawnmower robot control system includes a perception layer module, a decision-making layer module, an execution layer module, a fault self-correction module, and an energy management module; The perception layer module is used to collect environmental data and equipment status data through multi-source sensors, including an environmental perception unit and a status monitoring unit; The environmental perception unit is equipped with a lidar and a vision camera, and the status monitoring unit is equipped with a force control sensor, a light sensor and a power sensor. The decision-making layer module is used to generate operation instructions and energy scheduling strategies, including a dynamic task planning unit, a lawn mowing control strategy unit, and an energy scheduling unit. The dynamic task planning unit is used to generate the optimal mowing path and adaptive gait control commands through a path-terrain co-optimization algorithm. The mowing control strategy unit is used to adjust the robotic arm parameters and cutting power according to the weed density and height using a weed parameter adaptive adjustment algorithm. The energy scheduling unit is used to execute a priority scheduling strategy based on the battery power range using a power-light intensity linkage priority scheduling algorithm. The execution layer module is used to convert the instructions of the decision layer module into equipment control signals, including a motion control unit, a work control unit, and an energy control unit; The motion control unit is used to control the movement and gait adjustment of the quadrupedal robotic dog, and the operation control unit is used to control the extension, angle adjustment and cutting operation of the robotic arm; The energy control unit is used to adjust the angle of the photovoltaic panel and manage battery charging and discharging. The fault self-correction module is used to detect abnormal equipment status and perform adaptive adjustment or safety protection operations through a fault level adaptive response algorithm. The energy management module is connected to the perception layer module, decision layer module, and execution layer module to realize dynamic energy allocation and optimization.

[0010] Preferably, the priority scheduling strategy of the energy scheduling unit is configured as follows: When the battery charge is ≥80%, the lawn mowing task is performed first, and the angle adjustment mechanism of the support device is controlled to make the photovoltaic panel at the maximum light-receiving angle to maximize the solar charging efficiency. When the battery charge is between 30% and 80%, the lawn mowing and solar charging are performed in parallel, and energy resources are dynamically allocated according to the light intensity. When the battery level is less than 30%, stop mowing, start the light-seeking charging mode, control the mobile carrier to move to an area with unobstructed sunlight, and adjust the photovoltaic panel to the optimal light-receiving angle. Restart the operation after the battery level recovers to 50%.

[0011] Preferably, the dynamic task planning unit generates the optimal mowing path and gait control instructions through a path-terrain co-optimization algorithm, the formula of which is: ; ; in, The optimal mowing path; The set of candidate paths; The length of the candidate path; For terrain cost weights; This represents the number of sub-regions. For the first The complexity of the terrain in each sub-region; This is the gait adjustment factor; This is the force calibration coefficient; This is the slope calibration factor. Weed density; The height of the weeds.

[0012] Preferably, the mowing control strategy unit generates robotic arm extension length commands and drive motor output power commands through a weed parameter adaptive adjustment algorithm. This algorithm is calculated based on weed density and height parameters collected by a visual camera. The formula for the weed parameter adaptive adjustment algorithm is as follows: ; ; in, The extension length of the robotic arm; Base length; This is the length adjustment factor; This refers to the output power of the drive motor. Base power; This is the power adjustment coefficient; Weed density; The height of the weeds.

[0013] Preferably, the fault self-correction module includes a status monitoring unit, a fault classification unit, and a response control unit. The fault classification unit is used to distinguish between minor faults and major faults. The response control unit performs adaptive adjustment operations for minor faults and performs safety protection operations and sends alarm information for major faults.

[0014] Preferably, the energy management module monitors the energy consumption status of the robotic arm, drive motor, and supporting foot joint components in real time, prioritizes the energy supply of core operating components according to the instructions of the decision-making module, and maximizes the charging efficiency of the photovoltaic panels.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention uses a quadrupedal mechanical dog as a mobile carrier and combines it with a path-terrain collaborative optimization algorithm of a dynamic task planning unit. It can autonomously generate the optimal mowing path based on environmental perception data and dynamically adjust its gait according to the terrain slope. This effectively overcomes the shortcomings of traditional wheeled equipment in terms of poor terrain adaptability, ensuring stable movement and complete operation coverage in complex terrains such as slopes and potholes. It greatly expands the range of operation scenarios and solves the problems of poor terrain adaptability, easy jamming in complex terrain, and incomplete operation coverage of current wheeled mowing robots.

[0016] 2. This invention also achieves dynamic matching between mowing parameters and weed growth status through an adaptive adjustment algorithm for weed parameters in the mowing control strategy unit. The system can intelligently adjust the extension length and cutting power of the robotic arm based on the identified weed density and height, ensuring thorough cutting in high-density weed areas while avoiding energy waste in low-density areas. This significantly improves energy efficiency and reduces operating costs while enhancing work quality.

[0017] 3. This invention also constructs a dynamic closed loop for operation and charging by using a power-light intensity linkage priority scheduling algorithm and a photovoltaic panel angle adaptive adjustment structure. The system can flexibly switch operation and charging priorities according to the battery power range and light intensity. When the battery is low, it automatically starts the light-seeking charging mode, quickly replenishes energy, and restarts operation. This effectively solves the pain points of traditional equipment that rely on fixed charging and have short battery life, ensuring the continuity of operation.

[0018] 4. This invention also relies on a fault level adaptive response algorithm and a multi-module collaborative architecture, enabling the equipment to monitor its operating status in real time, accurately distinguish between minor and major faults and execute corresponding processing. Minor faults can be self-repaired by adjusting power and angle, while major faults will immediately activate safety protection and alarm to prevent the fault from escalating. At the same time, the energy management module dynamically allocates energy, prioritizing the supply to core operating components. Combined with full-process automated control, it greatly reduces manual intervention and balances the intelligence level and operational reliability of the equipment. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the external structure of the present invention; Figure 2 This is a schematic diagram of the external structure of the lawn mowing unit of the present invention; Figure 3 This is a schematic diagram of the external structure of the lawn mowing component of the present invention; Figure 4 This is a flowchart of the overall control system of the present invention; Figure 5 This is a flowchart of the path planning and gait control process of the present invention; Figure 6 This is a flowchart of the adaptive control process for mowing parameters according to the present invention; Figure 7 This is a flowchart of the energy dispatch priority control process of the present invention; Figure 8 This is a flowchart of the fault self-correction process of the present invention.

[0020] The following are the labels in the diagram: 1. Mobile carrier; 101. Support foot; 102. Mounting plate; 3. Mowing unit; 301. Electric push rod; 302. Robotic arm; 3021. Joint motor; 303. Mounting frame; 304. Mowing assembly; 3041. Drive motor; 3042. Cutting blade; 4. Energy unit; 401. Support device; 402. Photovoltaic panel. Detailed Implementation

[0021] Example 1: As Figures 1 to 3 As shown, the present invention relates to a lawnmower robot, comprising a mobile carrier 1 and a mounting plate 102 fixedly installed on the top of the mobile carrier 1. The bottom of the mobile carrier 1 is provided with a support foot 101, and the top of the support foot 101 is provided with a lawnmower unit 3 and an energy unit 4. The mobile carrier 1 and the support foot 101 constitute a quadrupedal mechanical dog. The support foot 101 is equipped with multi-degree-of-freedom joints, which can adjust the gait through joint rotation to achieve terrain-adaptive movement. The lawnmower unit 3 is located on both sides of the torso of the mobile carrier 1, including a radially extendable robotic arm 302 and a lawnmower assembly 304 located at the end of the robotic arm 302. The robotic arm 302 has at least three sets of joints, and a joint motor 3021 for driving the joint rotation is provided at each joint position, which can flexibly adjust the extension length and working angle of the robotic arm 302.

[0022] Furthermore, an electric push rod 301 is fixedly installed on the top of the mounting plate 102, and a robotic arm 302 is set on the top of the electric push rod 301. The electric push rod 301 can drive the robotic arm 302 to achieve vertical lifting and adjustment, and with the joint rotation, achieve multi-dimensional operation coverage. A mounting frame 303 is fixedly installed at the end of the robotic arm 302, and the mowing component 304 is set inside the mounting frame 303. The mowing component 304 includes a cutting blade 3042 and a drive motor 3041 for driving the cutting blade 3042. The drive motor 3041 can drive the cutting blade 3042 to rotate at high speed to complete the weed cutting operation.

[0023] Furthermore, the energy unit 4 includes a support device 401, on the top of which is a photovoltaic panel 402. The support device 401 has a built-in angle adjustment mechanism that can drive the photovoltaic panel 402 to rotate around the support point, thereby achieving adaptive adjustment of the illumination angle.

[0024] Example 2: As Figures 4 to 8 As shown, a lawnmower robot control system includes a perception layer module, which is used to collect environmental data and equipment status data through multi-source sensors to provide comprehensive and accurate input support for the decision-making layer. The perception layer module includes: The environmental perception unit is equipped with a LiDAR and a vision camera. The LiDAR and vision camera are mounted on the top of the mobile carrier 1. The LiDAR is used for 3D environmental modeling of the work area, constructing a complete terrain and obstacle distribution map. The vision camera is used for real-time weed identification, weed density statistics, and obstacle detection, accurately outputting weed density. Weed height Key operational parameters, such as those for mowing unit 3, provide a basis for motion control. The condition monitoring unit is equipped with a force control sensor, a light sensor, and a power sensor. The force control sensor is installed at position 101 of the mechanical dog's support foot to collect the force exerted on the leg when it contacts the ground in real time. Based on this feedback, the terrain slope can be deduced. A light sensor is installed on the side of the support device 401. The light sensor is used to detect the real-time light intensity. Including solar azimuth information; a power sensor is installed inside the battery pack of energy unit 4 to collect real-time battery power data. It simultaneously monitors the charging and discharging status of batteries, providing data support for energy dispatch.

[0025] Includes a decision-making module for generating work instructions and energy dispatching strategies; The decision-making module includes a dynamic task planning unit, a lawn mowing control strategy unit, and an energy scheduling unit; The dynamic task planning unit generates the optimal mowing path and adaptive gait control commands. Combined with the environmental map built by LiDAR, it automatically generates the optimal mowing path with complete coverage and the shortest path, avoiding repetitive work and path omissions. At the same time, based on the terrain data fed back by the force control sensor, it adjusts the gait of the mechanical dog in real time. For example, it adopts a low center of gravity gait to ensure stability on slopes and switches to an efficient movement gait on flat ground to improve work efficiency, ensuring smooth passage and work coverage in complex terrain. Specifically, by combining the environmental map from the lidar and the terrain data from the force control sensor, the optimal mowing path and gait control commands for supporting foot 101 are generated through a path-terrain co-optimization algorithm: ; ; in, The optimal mowing path; The set of candidate paths; The length of the candidate path; For terrain cost weights; This represents the number of sub-regions. For the first The complexity of the terrain in each sub-region; This is the gait adjustment factor; This is the force calibration coefficient; This is the slope calibration factor. Weed density; The height of the weeds.

[0026] The command controls the rotation of 101 multi-degree-of-freedom joints in the foot, employing a large-stride, efficient gait on flat ground and switching to a low-center-of-gravity, stable gait on slopes to ensure stability along the path. The path moves smoothly, covering the entire work area.

[0027] The mowing control strategy unit obtains weed density based on visual recognition. and weed height The robot arm 302 parameters and cutting power are adaptively adjusted. Specifically, based on the weed parameters from the visual camera, control commands for the robotic arm 302 and the drive motor 3041 are generated through an adaptive adjustment algorithm for the weed parameters: ; ; in, The extension length of robotic arm 302; Base length; This is the length adjustment factor; This is to drive the 3041 motor output power; Base power; This is the power adjustment coefficient; Weed density; The height of the weeds.

[0028] The command controls the lifting and lowering of the electric push rod 301, and the joint motor 3021 of the robotic arm 302 drives the joint to rotate, causing the robotic arm 302 to press... Extend to the target position; simultaneously control drive motor 3041 to press The output power drives the cutting blade 3042 to rotate, achieving an adaptive effect of efficient cutting of high-density weeds and energy-saving cutting of low-density weeds.

[0029] When the weeds are dense and tall, the robotic arm 302 is extended to increase its working range, while the output power of the drive motor 3041 is increased to improve cutting efficiency. When the weeds are sparse and short, the length of the robotic arm 302 can be appropriately shortened and the cutting power reduced to achieve energy-saving operation. The energy dispatching unit is used to execute priority dispatching strategies based on battery power ranges. The energy dispatch unit is configured to be based on battery power. The control commands for energy unit 4 are generated through a power-light linkage priority scheduling algorithm: ; in, For energy efficiency; This represents the maximum charging efficiency of the 402 photovoltaic panel. To maximize work efficiency; Rated light intensity When the battery charge is ≥80%, the lawn mowing task is executed first. The angle adjustment mechanism of the support device 401 is controlled to drive the photovoltaic panel 402 to rotate to the maximum light-receiving angle, maximizing the solar charging efficiency, while ensuring the full-load operation of the lawn mowing unit 3. When the battery level is between 30% and 80%, the lawn mowing unit 3 operates in parallel while the photovoltaic panel 402 is charged. When there is sufficient sunlight, the support device 401 is controlled to increase the light-receiving angle of the photovoltaic panel 402 to enhance the charging power. When there is insufficient sunlight, priority is given to ensuring the operating power of the robotic arm 302 and the drive motor 3041, depending on the light intensity. Dynamic allocation of computing resources: When there is sufficient light, ≥50000 lux, increasing the proportion of charging power; when light is insufficient, <50,000 lux, prioritize ensuring operating power to guarantee that the quality of work is not affected; When the battery level is less than 30%, the mowing unit 3 stops operating, the sun's position is located by the light sensor, the mowing task is paused, and the light-seeking charging mode is started. The solar panel 402 is adjusted to the optimal light-receiving angle by the light sensor, and the support foot 101 is controlled to move the mobile carrier 1 to an unobstructed area. At the same time, the support device 401 is controlled to adjust the solar panel 402 to the optimal light-receiving angle and start the light-seeking charging mode. After the battery level is restored to 50%, the operation will automatically restart, forming a closed loop of operation and charging.

[0030] It also includes an execution layer module, which converts the instructions generated by the decision layer module into control signals that the device can execute, enabling coordinated action of various components; The execution layer module includes: The motion control unit receives gait adjustment coefficients. and path The commands drive the rotation of the 101 multi-degree-of-freedom joints of the supporting foot, controlling stride length, stride frequency and body center of gravity to achieve stable movement in complex terrain. According to the instructions of the mowing control strategy unit, the operation control unit controls the lifting and lowering of the electric push rod 301, the extension and retraction of the robotic arm 302 and the joint rotation, and adjusts the output power of the drive motor 3041 to achieve the speed control of the cutting blade 3042 and accurately execute the mowing operation. The energy control unit receives instructions from the energy dispatching unit and controls the angle adjustment mechanism of the support device 401 to adjust the attitude of the photovoltaic panel 402. At the same time, it manages the charging and discharging process of the battery to ensure efficient energy utilization and storage.

[0031] This embodiment also includes a fault self-correction module; the fault self-correction module includes a status monitoring unit, a fault classification unit, and a response control unit; The status monitoring unit works in conjunction with the perception layer module to collect data such as the load of the mowing unit, the operating status of the robotic arm 302, and battery operating parameters in real time, and accurately identify equipment abnormalities, such as the cutting blade 3042 jamming, the robotic arm 302 sticking, and abnormal battery charging and discharging. The fault classification unit is used to distinguish fault levels, analyze detected abnormal states, and differentiate between minor and major faults. The response control unit is used to perform adaptive adjustment or safety protection operations, and performs corresponding processing operations according to the fault level.

[0032] Specifically, the operating status of the mechanical structure is monitored by sensors, and fault response commands are generated using a fault level adaptive response algorithm. ; in, For fault response strategies; This represents the fault level value. This is the fault threshold; The power reduction ratio; For alarm commands, For safe movement instructions. Specific controls: In cases of minor malfunctions, such as excessive load on the 3042 cutting tool, : Control drive motor 3041 press Reduce output power and simultaneously control the joint motor 3021 of the robotic arm 302 to adjust the working angle to avoid tool jamming; In case of severe malfunctions, such as jamming of robotic arm 302 or abnormality of support foot joint 101, The system controls the mowing unit 3 and the mobile carrier 1 to stop moving, sends an alarm message to the terminal, and simultaneously controls the support leg 101 to move the mobile carrier 1 to a preset safe area to prevent the fault from escalating.

[0033] This embodiment also includes a deep connection between the energy management module and the perception layer module, decision layer module, and execution layer module, and deep linkage with each module and the structure such as energy unit 4, lawn mowing unit 3, and mobile carrier 1. It monitors the energy consumption status of components such as robotic arm 302, drive motor 3041, and support foot 101 joints in real time, dynamically allocates energy according to the instructions of the decision layer module, prioritizes the energy supply of the core working structure, and maximizes the charging efficiency of photovoltaic panel 402 to extend the equipment's battery life.

[0034] The embodiments disclosed in this invention are preferred embodiments, but are not limited thereto. Those skilled in the art can easily understand the spirit of this invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of this invention, they are all within the protection scope of this invention.

Claims

1. A lawnmower robot, comprising a mobile carrier (1) and a mounting plate (102) fixedly mounted on the top of the mobile carrier (1), characterized in that, The mobile carrier (1) is provided with a support foot (101) at the bottom, and a grass-cutting unit (3) and an energy unit (4) are provided at the top of the support foot (101). The mobile carrier (1) and the supporting foot (101) constitute a quadrupedal mechanical dog. The supporting foot (101) is equipped with multi-degree-of-freedom joints to achieve terrain-adaptive gait control. The mowing unit (3) is located on both sides of the body of the mobile carrier (1), including a radially extendable robotic arm (302) and a mowing assembly (304) located at the end of the robotic arm (302). The robotic arm (302) has at least three sets of joints, and a joint motor (3021) for driving the joint rotation is provided at each joint position. The energy unit (4) includes a support device (401), on the top of which is a photovoltaic panel (402). The support device (401) has a built-in angle adjustment mechanism that can drive the photovoltaic panel (402) to rotate around the support point, thereby achieving adaptive adjustment of the illumination angle.

2. The lawnmower robot according to claim 1, characterized in that, An electric push rod (301) is fixedly installed on the top of the mounting plate (102). The top of the electric push rod (301) is connected to the robotic arm (302). A mounting bracket (303) is fixedly installed at the end of the robotic arm (302). The electric push rod (301) can drive the robotic arm (302) to achieve vertical adjustment.

3. A lawnmower robot according to claim 2, characterized in that, The mowing assembly (304) is located inside the mounting bracket (303). The mowing assembly (304) includes a cutting blade (3042) and a drive motor (3041) for driving the cutting blade (3042). The drive motor (3041) can dynamically adjust its output power according to control commands.

4. A lawnmower robot according to claim 1, characterized in that, Force control sensors are installed on the support foot (101) to collect force data when the support foot (101) contacts the ground, providing a basis for terrain-adaptive gait control.

5. A lawnmower robot control system, applicable to the lawnmower robot according to any one of claims 1-4, characterized in that, It includes a perception layer module, a decision-making layer module, an execution layer module, a fault self-correction module, and an energy management module; The perception layer module is used to collect environmental data and equipment status data through multi-source sensors, including an environmental perception unit and a status monitoring unit; The environmental perception unit is equipped with a lidar and a vision camera, and the status monitoring unit is equipped with a force control sensor, a light sensor and a power sensor. The decision-making layer module is used to generate operation instructions and energy scheduling strategies, including a dynamic task planning unit, a lawn mowing control strategy unit, and an energy scheduling unit. The dynamic task planning unit is used to generate the optimal mowing path and adaptive gait control commands through a path-terrain co-optimization algorithm. The mowing control strategy unit is used to adjust the parameters of the robotic arm (302) and the cutting power according to the weed density and height through a weed parameter adaptive adjustment algorithm; The energy scheduling unit is used to execute a priority scheduling strategy based on the battery power range using a power-light intensity linkage priority scheduling algorithm. The execution layer module is used to convert the instructions of the decision layer module into equipment control signals, including a motion control unit, a work control unit, and an energy control unit; The motion control unit is used to control the movement and gait adjustment of the quadrupedal mechanical dog, and the operation control unit is used to control the extension, angle adjustment and cutting operation of the robotic arm (302); The energy control unit is used to adjust the angle of the photovoltaic panel (402) and manage battery charging and discharging; The fault self-correction module is used to detect abnormal equipment status and perform adaptive adjustment or safety protection operations through a fault level adaptive response algorithm. The energy management module is connected to the perception layer module, decision layer module, and execution layer module to realize dynamic energy allocation and optimization.

6. A lawnmower robot control system according to claim 5, characterized in that, The priority scheduling strategy of the energy scheduling unit is configured as follows: When the battery charge is ≥80%, the grass mowing task is performed first, and the angle adjustment mechanism of the support device (401) is controlled to make the photovoltaic panel (402) at the maximum light-receiving angle to maximize the solar charging efficiency. When the battery charge is between 30% and 80%, the lawn mowing operation and solar charging are carried out in parallel, and energy resources are dynamically allocated according to the light intensity. When the battery power is less than 30%, the mowing operation is suspended, the light-seeking charging mode is started, the mobile carrier (1) is controlled to move to an area with unobstructed light, and the photovoltaic panel (402) is adjusted to the optimal light-receiving angle. The operation is restarted after the battery power is restored to 50%.

7. A lawnmower robot control system according to claim 5, characterized in that, The dynamic task planning unit generates the optimal mowing path and gait control instructions through a path-terrain co-optimization algorithm. The formula for the path-terrain co-optimization algorithm is as follows: ； ； in, The optimal mowing path; The set of candidate paths; The length of the candidate path; For terrain cost weights; This represents the number of sub-regions. For the first The complexity of the terrain in each sub-region; This is the gait adjustment factor; This is the force calibration coefficient; This is the slope calibration factor. Weed density; The height of the weeds.

8. A lawnmower robot control system according to claim 5, characterized in that, The mowing control strategy unit generates extension length commands for the robotic arm (302) and output power commands for the drive motor (3041) through a weed parameter adaptive adjustment algorithm. This algorithm is calculated based on weed density and height parameters collected by the visual camera. The formula for the weed parameter adaptive adjustment algorithm is as follows: ； ； in, The extension length of the robotic arm (302); Base length; This is the length adjustment factor; This is the output power of the drive motor (3041); Base power; This is the power adjustment coefficient; Weed density; The height of the weeds.

9. A lawnmower robot control system according to claim 5, characterized in that, The fault self-correction module includes a status monitoring unit, a fault classification unit, and a response control unit. The fault classification unit is used to distinguish between minor faults and major faults. The response control unit performs adaptive adjustment operations for minor faults and performs safety protection operations and sends alarm information for major faults.

10. A lawnmower robot control system according to claim 5, characterized in that, The energy management module monitors the energy consumption status of the robotic arm (302), drive motor (3041), and support foot (101) joint components in real time, and prioritizes the energy supply of the core operating components according to the instructions of the decision layer module, while maximizing the charging efficiency of the photovoltaic panel (402).

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