Tree maintenance robot and method of operation thereof

Abstract

The application relates to the technical field of forestry maintenance automation equipment, and discloses a tree maintenance robot and a working method thereof, which comprises the following: a mobile platform, which is equipped with an encoder odometer to realize autonomous movement of the robot; a multi-sensor perception system, which is used for environment perception and self-positioning; a spraying execution mechanism, which is used for performing spraying work on trees; an automatic supply system, which comprises a charging interface and a feeding / discharging valve and is used for realizing automatic supply of energy and materials; a controller, which is used for data fusion and decision control; an environment map is constructed based on multi-sensor fusion SLAM technology, a semantic map is generated by identifying the trunk position and diameter, a full-coverage working path is planned, the spraying execution mechanism is controlled to perform adaptive spraying on target trees, and the automatic supply system is dispatched to complete autonomous recharging and feeding when resources are insufficient; and the tree maintenance robot effectively solves the problems of automation, intelligentization and continuity of tree maintenance work in a complex fruit forest environment.

Description

Technical Field

[0001] This invention relates to the field of automated agricultural and forestry maintenance equipment, and in particular to a tree maintenance robot and its operation method. Background Technology

[0002] Tree maintenance operations in orchards and forest areas (such as winter whitewashing and pest and disease control spraying) are crucial for ensuring the healthy growth of trees. Traditional methods mainly rely on manual operation or semi-mechanized equipment, with workers using hand-held sprayers to whitewash tree trunks or apply pesticides. These methods suffer from significant problems, including high labor intensity, low efficiency, and high health risks to workers due to prolonged exposure to chemicals. Furthermore, they pose considerable safety hazards in complex terrains such as steep slopes and dense forests.

[0003] To improve operational efficiency, some agricultural spraying robots have emerged in recent years. These robots mostly employ pre-programmed path planning or GPS-based navigation and positioning to travel along preset routes and complete the spraying operation. However, these spraying robots cannot autonomously perceive complex forest and fruit environments and are difficult to adapt to scenarios with uneven tree density, undulating terrain, and varied obstacles. At the same time, they lack the ability to intelligently identify and accurately locate tree trunks in three dimensions, which easily leads to problems such as spraying deviation, missed spraying, repeated spraying, and paint waste.

[0004] Therefore, there is an urgent need to develop a tree maintenance robot with the ability to autonomously perceive the environment, intelligently identify tree trunks, and accurately locate them. Summary of the Invention

[0005] This invention proposes a tree maintenance robot to address the shortcomings of the prior art. This tree maintenance robot can achieve intelligent, precise, and efficient tree maintenance operations in complex orchard settings, while reducing paint waste.

[0006] The technical solution of the present invention is: a tree maintenance robot, comprising a mobile platform for realizing robot movement, wherein the mobile platform is provided with a paint tank, and further comprising: The multi-sensor perception system includes a 3D LiDAR, a depth camera, a BeiDou RTK module, a nine-axis IMU, and ultrasonic sensors, which are used for the robot's environmental perception and self-localization. The spraying actuator includes a posture adjustment mechanism set on a mobile platform, a robotic arm connected to the posture adjustment mechanism, a pump body connected to a paint tank, and multiple nozzles distributed in a fan shape on the robotic arm. Each nozzle is connected to the liquid outlet of the pump body. The controller receives information from a 3D LiDAR, depth camera, BeiDou RTK module, nine-axis IMU, and ultrasonic sensor. Based on this information, it constructs an environmental map using SLAM technology, identifies the location and diameter of tree trunks, and plans the operation path according to the environmental map. It then controls the mobile platform to move to each tree one by one, and uses a robotic arm to drive the spray nozzle to adjust its posture and distance from the tree trunk according to the trunk diameter to perform the spraying operation.

[0007] In at least one embodiment of the present invention, the pump body is a variable frequency diaphragm pump, and the controller is further configured to obtain the bark roughness of the sprayed tree trunk based on the information collected by the depth camera, and adjust the pump body flow rate and the moving speed of the moving platform according to the trunk diameter and the bark roughness.

[0008] In at least one embodiment of the present invention, the controller includes: a multi-sensor fusion SLAM module and a tree trunk recognition and semantic modeling module. The multi-sensor fusion SLAM module is used to construct a two-dimensional grid map using Cartographer or Gmapping algorithms based on the information collected by a depth camera, a Beidou RTK module, a nine-axis IMU, and an ultrasonic sensor. The tree trunk recognition and semantic modeling module is used to extract the spatial position and diameter information of the tree trunk in the two-dimensional grid map from the point cloud data using the RANSAC cylindrical fitting algorithm based on the information collected by the three-dimensional LiDAR.

[0009] In at least one embodiment of the present invention, the controller uses a wavefront algorithm or a ox-plowing algorithm to plan the operation path to generate a global path passing through each tree, and uses the DWA or TEB algorithm to realize local path adjustment and real-time obstacle avoidance.

[0010] In at least one embodiment of the present invention, the posture adjustment mechanism includes a lifting member longitudinally arranged on a moving platform and a horizontal moving member arranged on the movable part of the lifting member. The robotic arm includes a first arc plate connected to the movable part of the horizontal moving member, two second arc plates slidably connected to the first arc plate, and two driving members. A plurality of nozzles are respectively arranged on the inner sides of the first arc plate and the two second arc plates. The driving members are used to drive the second arc plates to slide on the first arc plate to wrap the tree trunk between the first arc plate and the two second arc plates. The lifting member, the horizontal moving member, and the driving members are all signal connected to the controller.

[0011] In at least one embodiment of the present invention, an automatic replenishment system is further included and a replenishment base station is configured. The mobile platform is equipped with a battery. The automatic replenishment system includes: a charging interface, a feeding / discharging valve, and a resource monitoring module. The charging interface is electrically connected to the battery. The feeding / discharging valve is installed on the paint tank for automatic replenishment and replacement of paint. The resource monitoring module includes a power detection unit connected to the battery and a liquid level sensor installed in the paint tank. The power detection unit and the liquid level sensor are signal-connected to a controller. The controller is used to return to the base station based on the received power information and liquid level information, and when the power information and liquid level information are lower than a threshold.

[0012] In at least one embodiment of the present invention, the supply base station includes a power supply and a feeding / discharging mechanism. Both the power supply and the feeding / discharging mechanism are equipped with AprilTag tags. The depth camera is used to identify the AprilTag tags and send the identification information to the controller. The controller is used to control the docking and positioning of the charging interface and the feeding / discharging valve with the power supply and the feeding / discharging mechanism, respectively, according to the identification information.

[0013] This invention also proposes a method for operating a tree maintenance robot, comprising the following steps: After entering the forest area, the robot collects information using a 3D LiDAR, depth camera, BeiDou RTK module, nine-axis IMU and ultrasonic sensor, and sends the collected information to the controller. Based on the received collected information, the controller constructs an environmental map using SLAM technology, identifies the location and diameter of tree trunks, and plans the operation path according to the environmental map; Subsequently, the controller controls the mobile platform to move to each tree one by one according to the operation path. Then, the robotic arm drives the nozzle to adjust the nozzle's posture and distance from the tree trunk according to the trunk diameter. After the adjustment is completed, the pump is started to perform the spraying operation.

[0014] When the battery or paint level falls below a threshold, the robot autonomously plans a path back to the base station. It uses visual servo recognition to precisely connect the charging interface with the feeding valve, replenishes resources, and then returns to the interruption point to continue operation.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention proposes a tree maintenance robot that employs a mobile platform equipped with a paint tank, a multi-sensor perception system including a 3D LiDAR, depth camera, BeiDou RTK module, nine-axis IMU, and ultrasonic sensor, a spraying execution mechanism with posture adjustment mechanism, robotic arm, pump body, and nozzle, and a controller. During operation, it constructs an environmental map using SLAM technology, identifies the location and diameter of tree trunks, and plans the work path based on the environmental map. The mobile platform moves sequentially to each tree, and the robotic arm drives the nozzle to adjust its posture and distance from the trunk according to the trunk diameter to perform the spraying operation. Compared with existing technologies, this invention effectively solves the technical problems of existing tree maintenance equipment, such as reliance on preset paths or GPS navigation, inability to autonomously perceive complex forest environments, and lack of intelligent trunk recognition and precise positioning capabilities, leading to operational deviations, missed sprays, and paint waste. It can autonomously construct environmental maps, accurately identify the location and diameter of tree trunks, intelligently plan work paths, and adaptively adjust nozzle posture and working distance, achieving automation, intelligence, and continuity of tree maintenance operations in complex forest environments, improving operational accuracy and efficiency, and reducing paint waste. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the three-dimensional structure of the present invention. Figure 1 ; Figure 2 This is a schematic diagram of the main cross-sectional structure of the present invention; Figure 3 This is a side view of the structure of the present invention; Figure 4 This is a schematic diagram of the three-dimensional structure of the present invention. Figure 2 ; Figure 5 This is a schematic diagram of the three-dimensional structure of the present invention. Figure 3 .

[0017] Explanation of reference numerals in the attached figures: 1. Mobile platform; 11. Paint tank; 111. Liquid level sensor; 12. Battery; 2. Multi-sensor sensing system; 21. 3D LiDAR; 22. Depth camera; 23. Ultrasonic sensor; 3. Spraying actuator; 31. Posture adjustment mechanism; 311. Lifting component; 312. Horizontal moving component; 32. Robotic arm; 321. First arc plate; 322. Second arc plate; 33. Pump body; 34. Spray nozzle. Detailed Implementation

[0018] The accompanying drawings in this invention are not strictly drawn to scale, and the specific dimensions and quantity of each structure can be determined according to actual needs. The drawings described in this invention are merely structural schematic diagrams.

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "inner," "outer," "upper," "lower," "far," "near," "front," and "rear" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Existing tree maintenance robots have the following technical shortcomings in practical applications: 1. Insufficient environmental adaptability: Relying on preset paths or manual markers, they cannot autonomously perceive and map unfamiliar work areas in real time. They are ill-suited to dynamic orchard environments with uneven tree planting density, varied inter-row obstacles, and complex terrain, often resulting in incomplete coverage due to path deviations. 2. Low target recognition accuracy: Lacking intelligent recognition and positioning capabilities for tree trunks, they cannot obtain real-time information on the three-dimensional spatial position, diameter, and posture of the trunks. Positional shifts are prone to occur during spraying, leading to missed spraying, repeated spraying, or uneven paint coverage, affecting both maintenance effectiveness and material waste. 3. Low functional integration: Their operation modes are limited; the equipment typically only supports whitewashing or pesticide spraying, and cannot automatically switch spraying materials and process parameters according to maintenance needs. Users need to purchase multiple dedicated devices, increasing equipment investment costs and maintenance difficulty. 4. Lack of endurance and replenishment capabilities: It lacks self-charging and automatic feeding functions. When the power or materials are exhausted, manual intervention is required for replenishment. It cannot achieve continuous unattended operation around the clock, which limits the practicality and economy of the equipment in large-scale operation scenarios.

[0022] In view of this, the tree maintenance robot proposed in this invention has autonomous navigation, intelligent recognition, multi-functional integration and automatic replenishment capabilities.

[0023] Combination Figures 1 to 5As shown, a tree maintenance robot includes a mobile platform 1 for robot movement, a paint tank 11 mounted on the mobile platform 1, and specifically, an encoder odometer mounted on the mobile platform 1. The mobile platform 1 is a tracked platform with strong mobility. The tree maintenance robot also includes: The multi-sensor perception system 2 includes a 3D LiDAR 21, a depth camera 22, a BeiDou RTK module, a nine-axis IMU, and an ultrasonic sensor 23, which are used for the robot's environmental perception and self-localization; specifically, the depth camera 22 is an RGB-D depth camera. The spraying actuator 3 includes a position adjustment mechanism 31 mounted on the mobile platform 1, a robotic arm 32 connected to the position adjustment mechanism 31, a pump body 33 connected to the paint tank 11, and multiple nozzles 34 arranged in a fan shape on the robotic arm 32. Each nozzle 34 is connected to the outlet of the pump body 33, and a solenoid valve is provided on the connecting pipe between the nozzle 34 and the pump body 33. The controller receives information from a 3D LiDAR 21, a depth camera 22, a BeiDou RTK module, a nine-axis IMU, and an ultrasonic sensor 23. Based on the collected information, it constructs an environmental map using SLAM (Simultaneous Localization and Mapping) technology, identifies the location and diameter of tree trunks, and plans the operation path according to the environmental map. It controls the mobile platform 1 to move to each tree one by one, and the robotic arm 32 drives the spray nozzle 34 to adjust the posture of the spray nozzle 34 and the distance from the tree trunk according to the trunk diameter to perform the spraying operation. The specific controller includes a main control computer equipped with ROS and an embedded controller for data fusion and decision control. This invention effectively solves the problems of existing equipment relying on preset paths and insufficient environmental adaptability. It can autonomously build maps, locate and navigate in complex forest and fruit environments, accurately identify the location and diameter of tree trunks, realize fully autonomous intelligent operation, improve the accuracy and efficiency of operation, and reduce paint waste.

[0024] As an alternative embodiment, the pump body 33 is a variable frequency diaphragm pump, specifically; the pump body 33 is a PWM controlled diaphragm pump; the controller is also used to obtain the bark roughness of the tree trunk to be sprayed based on the information collected by the depth camera 22, and adjust the flow rate of the pump body 33 and the moving speed of the moving platform 1 according to the trunk diameter and bark roughness, and use a PID algorithm closed-loop control to control the spray uniformity. Specifically, the control principle of the flow rate of the pump body 33 and the moving speed of the moving platform 1 is: when the trunk diameter is relatively large and relatively rough, the pump body 33 is controlled to output spray at a large flow rate, and the moving platform 1 moves slowly; when the trunk diameter is relatively small and the trunk surface is relatively smooth, the pump body 33 is controlled to output spray at a small flow rate, and the moving platform 1 moves quickly, so as to ensure uniform spray coverage and no waste. Furthermore, the specific spray flow rate is determined according to the type and viscosity of the paint. This tree maintenance robot adjusts the flow rate of the pump body 33 and the speed of the moving platform 1 in real time according to the trunk diameter and bark roughness, solving the problems of low spraying accuracy, uneven coverage, and paint waste, effectively improving spraying quality and efficiency, and further saving paint.

[0025] As an alternative embodiment, the controller includes: a multi-sensor fusion SLAM module and a tree trunk recognition and semantic modeling module. The multi-sensor fusion SLAM module is used to construct a two-dimensional grid map using Cartographer or Gmapping algorithms based on the information collected by the depth camera 22, the Beidou RTK module, the nine-axis IMU, and the ultrasonic sensor 23. The tree trunk recognition and semantic modeling module is used to extract the spatial position and diameter information of the tree trunk in the two-dimensional grid map from the point cloud data using the RANSAC cylindrical fitting algorithm based on the information collected by the three-dimensional lidar 21.

[0026] As an alternative implementation, the controller uses wavefront algorithm or ox-plowing algorithm to plan the operation path to generate a global path passing through each tree, and uses DWA or TEB algorithm to realize local path adjustment and real-time obstacle avoidance. The implementation of the above planning and algorithm enables the robot to cope with dynamic environments with uneven fruit tree density and complex terrain, solves the problems of operation path deviation and weak obstacle avoidance ability, and improves the stability of operation in complex scenarios.

[0027] As an alternative embodiment, the posture adjustment mechanism 31 includes a lifting member 311 longitudinally arranged on the moving platform 1 and a horizontal moving member 312 arranged on the movable part of the lifting member 311. The robotic arm 32 includes a first arc plate 321 connected to the movable part of the horizontal moving member 312, two second arc plates 322 slidably connected to the first arc plate 321, and two driving members. Multiple nozzles 34 are respectively arranged on the inner side of the first arc plate 321 and the two second arc plates 322. The driving members are used to drive the second arc plates 322 to slide on the first arc plate 321 to wrap the tree trunk between the first arc plate 321 and the two second arc plates 322. The lifting member 311, the horizontal moving member 312, and the driving members are all connected to the controller signal. Specifically, the lifting member 311 and the horizontal moving member 312 are H-shaped as a whole, and each component of the robotic arm 32 is made by 3D printing and is lightweight.

[0028] As an alternative embodiment, an automatic replenishment system with a replenishment base station is also included. The mobile platform 1 is equipped with a battery 12. The automatic replenishment system includes a charging interface, a feeding / discharging valve, and a resource monitoring module. The charging interface is electrically connected to the battery 12. The feeding / discharging valve is installed on the paint tank 11 for automatic replenishment and replacement of paint. The resource monitoring module includes a power detection unit connected to the battery 12 and a liquid level sensor 111 installed in the paint tank 11. The power detection unit and the liquid level sensor 111 are connected to the controller. The controller is used to return to the base station based on the received power and liquid level information. When the power and liquid level information are lower than the threshold, the controller returns to the base station. The above configuration solves the problem of reliance on manual operation for endurance and material replenishment, which prevents continuous operation. It can autonomously recharge, add materials, and replace materials. After replenishment, it returns to the interruption point to continue operation, realizing continuous unattended operation around the clock.

[0029] As an alternative embodiment, the supply base station includes a power supply and a feeding / discharging mechanism. Both the power supply and the feeding / discharging mechanism are equipped with AprilTag tags. The depth camera 22 is used to identify the AprilTag tags and send the identification information to the controller. The controller is used to control the docking and positioning of the charging interface and the feeding / discharging valve with the power supply and the feeding / discharging mechanism, respectively, according to the identification information.

[0030] This invention also proposes a method for operating a tree maintenance robot, comprising the following steps: After entering the forest area, the robot collects information using a 3D LiDAR 21, a depth camera 22, a BeiDou RTK module, a nine-axis IMU, and an ultrasonic sensor 23, and sends the collected information to the controller. Based on the received data, the controller constructs an environmental map using SLAM technology, identifies the location and diameter of tree trunks, and plans the operation path according to the environmental map. Subsequently, the controller controls the mobile platform 1 to move to each tree one by one according to the work path. Then, the robotic arm 32 drives the nozzle 34 to adjust the posture of the nozzle 34 and the distance from the tree trunk according to the diameter of the tree trunk. After the adjustment is completed, the pump body 33 is started to perform the spraying operation. When the battery or paint level falls below a threshold, the robot autonomously plans a path back to the base station. It uses visual servo recognition to precisely connect the charging interface with the feeding valve, replenishes resources, and then returns to the interruption point to continue operation.

[0031] As an alternative embodiment, during the automatic replenishment phase, based on the real-time monitoring data of the power and liquid level sensors 111, the return-to-base command is triggered in advance through the resource prediction model, and the interruption coordinates are automatically recorded before returning to the base. The robot identifies the base station AprilTag mark and uses visual servo control to dock and position the charging interface and the paint tank 11 feeding port with the power supply and feeding mechanism, respectively. After replenishment is completed, the optimal path is planned according to the interruption coordinates to return and continue the operation.

[0032] As an alternative embodiment, the tree maintenance robot performs the following steps for automatically changing the sprayed material: the maintenance robot returns to the base station, opens the discharge port, discharges the remaining paint to the base station for recycling, then fills the entire paint tank 11 with water to clean it through the base station, then discharges the cleaning water through the discharge port, and then replaces the paint with new paint.

[0033] This invention proposes a tree maintenance robot with the following advantages: 1. It achieves fully autonomous and intelligent operation, autonomously completing mapping, positioning, and navigation in unfamiliar orchards and forest environments. It accurately identifies tree trunks and constructs semantic maps, enabling adaptive spraying of trees without human intervention, significantly reducing labor costs. 2. It improves the quality and efficiency of spraying operations. Through PID algorithm closed-loop control, it adjusts the pump flow and moving platform speed in real time based on the trunk diameter and bark roughness, ensuring uniform coating thickness, increasing spray coverage, effectively saving coating, and reducing material waste. 3. It achieves multi-functional integrated operation, supporting automatic switching between whitewashing and pesticide spraying modes. It can automatically change spraying materials and adjust process parameters as needed, improving equipment utilization and reducing equipment investment and maintenance costs. 4. It has all-weather continuous operation capability. Equipped with an automatic replenishment system, it can actively trigger a return-to-base station command based on real-time monitoring data of power and liquid level. Through visual servoing, it achieves precise docking for charging, adding / changing materials. After replenishment, it automatically returns to the interrupted point to continue working without manual intervention. 5. Possesses strong environmental adaptability. Relying on a multi-sensor fusion perception system and DWA / TEB dynamic obstacle avoidance algorithm, it can cope with complex and dynamic orchard environments with uneven tree density, changing obstacles, and undulating terrain, achieving stable operation. 6. Adopts a modular and scalable design. Based on a ROS-based distributed software architecture and modular hardware, it supports rapid algorithm iteration and online upgrades. Simultaneously, it enables multi-machine collaborative operation, and the system has continuous evolution capabilities, comprehensively promoting the automation and intelligent upgrading of orchard maintenance.

[0034] The above embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit them. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions implemented in the present invention, and should all be covered within the protection scope of the present invention.

Claims

1. A tree maintenance robot, comprising a mobile platform for enabling robot movement, wherein the mobile platform is equipped with a paint tank, characterized in that, Also includes: The multi-sensor perception system includes a 3D LiDAR, a depth camera, a BeiDou RTK module, a nine-axis IMU, and an ultrasonic sensor, all mounted on a mobile platform. The spraying actuator includes a posture adjustment mechanism set on a mobile platform, a robotic arm connected to the posture adjustment mechanism, a pump body connected to a paint tank, and multiple nozzles distributed in a fan shape on the robotic arm, each of which is connected to the liquid outlet of the pump body. The controller receives information from a 3D LiDAR, depth camera, BeiDou RTK module, nine-axis IMU, and ultrasonic sensor. Based on this information, it constructs an environmental map using SLAM technology, identifies the location and diameter of tree trunks, and plans the work path according to the environmental map. It then controls the mobile platform to move to each tree one by one, and uses a robotic arm to drive the spray nozzle to adjust its posture and distance from the tree trunk according to the trunk diameter to perform the spraying operation.

2. The tree maintenance robot according to claim 1, characterized in that, The controller includes: The multi-sensor fusion SLAM module is used to construct a two-dimensional grid map based on the information collected by the depth camera, Beidou RTK module, nine-axis IMU and ultrasonic sensor, using the Cartographer or Gmapping algorithm. The tree trunk recognition and semantic modeling module is used to extract the spatial position and diameter information of the tree trunk in the two-dimensional grid map from the point cloud data using the RANSAC cylindrical fitting algorithm based on the information collected by the three-dimensional lidar.

3. The tree maintenance robot according to claim 1, characterized in that, The pump body is a variable frequency diaphragm pump, and the controller is also used to obtain the bark roughness of the tree trunk to be sprayed based on the information collected by the depth camera, and to adjust the pump flow rate and the moving platform speed according to the trunk diameter and bark roughness.

4. The tree maintenance robot according to claim 1, characterized in that, The controller uses wavefront algorithm or ox-plowing algorithm to plan the operation path to generate a global path through each tree, and uses DWA or TEB algorithm to realize local path adjustment and real-time obstacle avoidance.

5. A tree maintenance robot according to claim 1, characterized in that, The posture adjustment mechanism includes a lifting component longitudinally arranged on the moving platform and a horizontal moving component arranged on the movable part of the lifting component. The robotic arm includes a first arc plate connected to the movable part of the horizontal moving component, two second arc plates slidably connected to the first arc plate, and two driving components. Multiple nozzles are respectively arranged on the inner sides of the first arc plate and the two second arc plates. The driving components are used to drive the second arc plates to slide on the first arc plate to wrap the tree trunk between the first arc plate and the two second arc plates. The lifting component, the horizontal moving component, and the driving components are all signal connected to the controller.

6. A tree maintenance robot according to claim 1, characterized in that, It also includes an automatic resupply system and is equipped with a resupply base station. The mobile platform is equipped with a battery. The automatic resupply system includes: The charging port is electrically connected to the battery. The feeding / discharging valve is installed on the paint tank for automatic paint replenishment and replacement; The resource monitoring module includes a power detection unit connected to the battery and a liquid level sensor installed inside the paint tank; the power detection unit and the liquid level sensor are signal-connected to the controller, which is used to return information to the base station based on the received power and liquid level information, and when the power and liquid level information are below a threshold.

7. A tree maintenance robot according to claim 6, characterized in that, The supply base station includes a power supply and a feeding / discharging mechanism. Both the power supply and the feeding / discharging mechanism are equipped with AprilTag tags. The depth camera is used to identify the AprilTag tags and send the identification information to the controller. The controller is used to control the charging interface and the feeding / discharging valve to dock with the power supply and the feeding / discharging mechanism respectively according to the identification information.

8. A tree maintenance robot operation method, based on the tree maintenance robot according to claim 1, characterized in that, Includes the following steps: After entering the forest area, the robot collects information using a 3D LiDAR, depth camera, BeiDou RTK module, nine-axis IMU and ultrasonic sensor, and sends the collected information to the controller. Based on the received collected information, the controller constructs an environmental map using SLAM technology, identifies the location and diameter of tree trunks, and plans the operation path according to the environmental map; Subsequently, the controller controls the mobile platform to move to each tree one by one according to the operation path. Then, the robotic arm drives the nozzle to adjust the nozzle's posture and distance from the tree trunk according to the trunk diameter. After the adjustment is completed, the pump is started to perform the spraying operation.

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