Garden robot

Abstract

This application discloses a garden robot, comprising: a mobile platform configured to drive the garden robot to move; a main body supported by the mobile platform; a power supply component disposed on the main body and configured to provide an energy source for the garden robot; multiple tool modules, each used to perform a target task; a sensor component configured to collect environmental information of the garden robot; and a control unit disposed on the main body and configured to control the tool modules to perform the target task based on the environmental information collected by the sensor component. The multiple tool modules include a mowing module, a blower module, and a pruning module that can be simultaneously installed on the main body. The garden robot integrates multiple gardening functions through the ingenious arrangement of these multiple tool modules.

Description

Technical Field

[0001] This invention relates to the field of garden robot technology, and in particular to a garden robot, garden robot system and control method that integrate multiple modules, applicable to garden maintenance, agricultural management and home gardening scenarios. Background Technology

[0002] Existing gardening tools (such as lawnmowers, blowers, and pruning machines) are typically single-purpose devices that require manual control during operation, making them unsuitable for large-scale or complex terrain operations. Furthermore, the different control methods and interfaces of various tools make it difficult to achieve automated and intelligent operation.

[0003] With the development of artificial intelligence and automatic control technology, how to integrate various gardening tools into a garden robot to achieve automatic recognition, intelligent control and efficient operation has become an urgent problem to be solved in this field. Summary of the Invention

[0004] One objective of this application is to solve or at least alleviate some or all of the aforementioned problems. To this end, one objective of this application is to provide an integrated, multifunctional garden robot system that, through modular design and an intelligent control unit, enables rapid switching and efficient operation of various gardening tools.

[0005] To achieve the above objectives, this application adopts the following technical solution: a garden robot, comprising: a mobile platform configured to drive the garden robot to move; a main body supported by the mobile platform; a power supply component disposed on the main body and configured to provide an energy source for the garden robot; multiple tool modules, each used to perform a target task; a sensor component configured to collect environmental information of the garden robot; and a control unit disposed on the main body and configured to control the tool modules to perform the target task based on the environmental information collected by the sensor component; wherein the multiple tool modules include a mowing module, a blower module, and a pruning module that can be simultaneously installed on the main body.

[0006] In some embodiments, the mobile platform includes a bionic limb structure.

[0007] In some embodiments, the bionic limb structure includes a walking wheel.

[0008] In some embodiments, the garden robot has a wheeled walking mode and a biomimetic gait mode.

[0009] In some embodiments, the mowing module is mounted to the body and surrounded by a biomimetic limb structure.

[0010] In some embodiments, the blower module is mounted to the main body via at least two mounting parts.

[0011] In some embodiments, the blowing angle of the blower module is adjustable.

[0012] In some embodiments, the pruning module is installed on one of the limbs and is disposed on both sides of the main body, respectively, along with the blower module.

[0013] In some embodiments, the garden robot can switch between quadrupedal walking mode and hindlimb walking mode.

[0014] In some embodiments, the control unit is configured to control at least two tool modules to operate simultaneously based on environmental information.

[0015] To achieve the above objectives, this application adopts the following technical solution: a garden robot, comprising: a mobile platform including a bionic limb structure configured to drive the garden robot to move; a main body supported by the mobile platform; a power supply component disposed on the main body and configured to provide an energy source for the garden robot; at least one tool module for performing a target task; a sensor component configured to collect environmental information of the garden robot; and a control unit disposed on the main body and configured to control the tool module to perform the target task based on the environmental information collected by the sensor component; wherein, at least one tool module includes a mowing module, the mowing module being installed on the main body and surrounded by the bionic limb structure.

[0016] In some embodiments, the mowing module includes a blade disc, the height of which is adjustable by the height of the main body.

[0017] In some embodiments, the height of the subject is adjusted by extending the limb structure.

[0018] In some embodiments, each leg of the bionic limb structure includes at least one joint for adjusting the posture of the bionic limb structure to change the height of the subject.

[0019] In some embodiments, the tool module further includes a blower module and a pruning module, which are respectively disposed on both sides of the main body.

[0020] The advantages of this application are: the garden robot achieves all-weather, all-scenario autonomous operation capabilities by integrating multiple modular working heads. By incorporating various tool modules such as lawn mowing, blower, and pruning modules, the purchase cost of multiple single-function devices is reduced. Attached Figure Description

[0021] Figure 1 This is a block diagram of a garden robot system according to an embodiment of this application; Figure 2 This is a schematic diagram of a garden robot according to one embodiment of this application; Figure 3 This is a schematic diagram of a garden robot according to another embodiment of this application; Figure 4 yes Figure 3 A schematic diagram showing another perspective of the garden robot; Figure 5 yes Figure 3 The diagram shows a garden robot in a crawling position. Figure 6 yes Figure 3 The diagram shown illustrates the garden robot in a standing position. Figure 7 This is a schematic diagram of the energy storage device sharing system of the garden robot of this application; Figure 8 This is an exploded view of an energy storage device according to an embodiment of this application; Figure 9 This is a schematic diagram of a workhead repository according to an embodiment of this application; Figure 10 This is a schematic diagram of a charging pile and a working head storage device according to one embodiment of this application; Figure 11 This is a schematic diagram of a charging pile and a working head storage container according to another embodiment of this application; Figure 12 This is a schematic diagram of the communication system of a garden robot system according to an embodiment of this application. Detailed Implementation

[0022] Before explaining any implementation of this application in detail, it should be understood that this application is not limited to its application to the structural details and component arrangements set forth in the following description or shown in the above drawings.

[0023] In this application, the terms "comprising," "including," "having," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0024] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this application generally indicates that the preceding and following related objects have an "and / or" relationship.

[0025] In this application, the terms "connection," "combination," "coupling," and "installation" can refer to direct connection, combination, coupling, or installation, or indirect connection, combination, coupling, or installation. For example, a direct connection refers to two parts or components being connected together without the need for an intermediary, while an indirect connection refers to two parts or components each being connected to at least one intermediary, with the connection achieved through the intermediary. Furthermore, "connection" and "coupling" are not limited to physical or mechanical connections or couplings, but can also include electrical connections or couplings.

[0026] In this application, those skilled in the art will understand that relative terms (e.g., “about,” “approximately,” “basically,” etc.) used in conjunction with quantities or conditions are to include the values ​​and have the meaning indicated by the context. For example, such relative terms include at least the degree of error associated with the measurement of a particular value, tolerances associated with the particular value due to manufacturing, assembly, use, etc. Such terms should also be considered as disclosing a range defined by the absolute values ​​of the two endpoints. Relative terms may refer to a certain percentage (e.g., 1%, 5%, 10% or more) of the indicated value. Numerical values ​​that do not use relative terms should also be disclosed as specific values ​​with tolerances. Furthermore, “basically” when expressing relative angular relationships (e.g., substantially parallel, substantially perpendicular) may refer to a certain degree (e.g., 1 degree, 5 degrees, 10 degrees or more) added to or subtracted from the indicated angle.

[0027] In this application, those skilled in the art will understand that the function performed by a component can be performed by one component, multiple components, one part, or multiple parts. Similarly, the function performed by a part can also be performed by one part, one component, or a combination of multiple parts.

[0028] In this application, the directional terms "upper," "lower," "left," "right," "front," and "rear" are used to describe the orientation and positional relationships shown in the accompanying drawings and should not be construed as limiting the embodiments of this application. Furthermore, in the context, it should be understood that when an element is mentioned as being connected "upper" or "lower" to another element, it can be directly connected to the other element "upper" or "lower," or indirectly connected through an intermediate element. It should also be understood that directional terms such as upper side, lower side, left side, right side, front side, and rear side not only represent positive orientation but can also be understood as lateral orientation. For example, "below" can include directly below, lower left, lower right, lower front, and lower rear.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the term "comprising," and any variations thereof, is intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] In this application, the terms "controller," "processor," "central processing unit," "CPU," and "MCU" are used interchangeably. When using the unit "controller," "processor," "central processing unit," "CPU," or "MCU" to perform a specific function, unless otherwise stated, these functions may be performed by a single or multiple of the aforementioned units.

[0031] In this application, the terms "device," "module," or "unit" are used to describe devices that can be implemented in hardware or software to perform a specific function.

[0032] In this application, the terms “calculation,” “judgment,” “control,” “determine,” “identify,” etc., refer to the operation and process of a computer system or similar electronic computing device (e.g., controller, processor, etc.).

[0033] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0034] like Figures 1 to 4 As shown, this application provides a garden robot system 10, wherein the garden robot 100 includes a main body 110, a mobile platform 120, a power supply assembly 130, a tool module 150, a sensor assembly 160, a control unit 170, and a communication module 180. Optionally, the garden robot system 10 also includes a charging pile 200, a modular interface 140, and a work head storage container 300.

[0035] The robot in this application is not limited to a humanoid body 110. It can be in a form similar to a human, with the lower limbs on the ground and the upper limbs working; or in a form similar to a dog, with all four limbs on the ground; or it can switch between the two. Whether it is a dog-shaped robot, a humanoid robot, or a robot of other forms, it is collectively referred to as a robot in this application, and this application does not limit the specific form of the robot. The robot's body 110 carries the core components of the entire system, responsible for providing power, executing control, enabling multi-module collaborative work, and ensuring the stability and adaptability of the system. The body 110 can be understood as a body part similar to a human or dog's body. The mobile platform 120, used to enable the robot's autonomous movement, is installed on the body 110 and supports the body 110.

[0036] The mobile platform 120 offers various structural options, including tracked, wheeled, and bionic legged designs. Users can select the appropriate configuration based on their target working conditions to adapt to different terrains and application scenarios. The tracked structure is made of high-strength composite materials, offering excellent wear resistance and impact resistance. Its large contact area and distributed pressure design enable it to demonstrate strong obstacle-crossing ability and stability in complex terrains such as mud, gravel, or rugged surfaces. Furthermore, the tracked structure is equipped with an adaptive suspension system that automatically adjusts its posture according to ground undulations, ensuring smooth operation of the robot on uneven terrain. In one embodiment, the tracked structure can be used for a humanoid robot with its lower limbs on the ground. The wheeled structure uses lightweight alloy wheels and highly elastic tires, enabling high-speed and efficient movement on both flat and hard surfaces. Its drive motor uses brushless DC technology, featuring high torque output and low energy consumption, making it suitable for cleaning and maintenance tasks in urban parks, squares, and other similar locations. The wheeled structure is also equipped with an electronic differential system for flexible steering and precise positioning. The biomimetic limb structure 121 mimics the movement mechanism of biological legs, employing a multi-joint design. Each joint is driven by a high-precision servo motor, enabling stable walking on irregular or steep terrain. Each leg is equipped with a force sensor and an inertial measurement unit (IMU) to monitor ground reaction forces and robot posture in real time, ensuring balance and flexibility in complex terrain. In one embodiment, this application provides a wheeled biomimetic limb structure 121 that combines wheel-like and biomimetic limb structures. It can freely switch between wheeled walking mode and biomimetic gait mode. In wheeled mode, its limbs are used as wheels for high-speed movement, driven by built-in motors for rapid movement. In biomimetic gait mode, its limbs transform into support and balance devices, achieving stable walking on complex terrain through multi-joint coordinated movement. The mode switching is automatically completed by the control unit 170, with a switching time of less than 2 seconds, ensuring the robot's efficient adaptation in different scenarios. In one embodiment, the robot includes walking wheels 1214 disposed on the claws of its limbs. These walking wheels 1214 can be driven by hub motors and can include two modes: rotation and locking. In rotation mode, the walking wheels rotate to drive the robot to walk in a wheeled mode. In locking mode, the walking wheels 1214 do not rotate, and the robot walks in a bionic gait mode. Each bionic leg 1211 includes at least one joint 1212 for adjusting the limb posture to change the height of the main body 110. In another embodiment, the walking wheels are disposed at the knee joints of the limbs. In wheeled mode, the lower legs are raised, allowing the walking wheels 1214 to rotate on the ground. In bionic gait mode, the lower legs are lowered, walking in a bionic gait to prevent slipping on complex terrain such as stairs. In one embodiment, such as Figure 5As shown, the robot has a cutting blade on its abdomen. By adjusting the posture of its limbs to make its abdomen lie flat on the ground, the height of the cutting blade can be adjusted to meet the need for the cutting blade to cut grass close to the ground. At the same time, it adopts a wheeled movement mode to meet the need for stable movement.

[0037] The power supply assembly 130 and control unit 170 are crucial for the efficient operation of the garden robot 100, configured to provide a continuous and stable energy supply and precise behavioral control. In some embodiments, both the power supply assembly and control unit 170 are located on the robot body 110. In one embodiment, a high-efficiency lithium-ion battery pack provides a long-term energy supply. The battery pack adopts a modular design, supports hot-swappable replacement, and ensures the robot's endurance during long-term tasks, making it suitable for extended outdoor operations.

[0038] The power supply assembly 130 includes an energy storage device to provide a power source for the various components of the garden robot 100. In one embodiment, the power supply assembly 130 consists of a removable battery pack; in another embodiment, the power supply assembly 130 consists of a non-removable built-in battery cell module. In one embodiment, the power supply assembly 130 is composed of both a removable battery pack and a non-removable built-in battery cell module. In one embodiment, the power supply assembly 130 consists of a removable first battery pack 131 and a removable second battery pack 132, wherein at least one operating parameter of the first battery pack 131 is different from that of the second battery pack 132. Note that "non-removable" in this application means that the user cannot remove it from the installed state without tools, not that maintenance personnel cannot remove the built-in battery cell module from the installed state even with the aid of professional tools; otherwise, it would be detrimental to the maintenance and upkeep of the garden robot 100. In contrast, the removability of this application means that the user can remove the battery pack from its installed state without the aid of tools. In this way, the user can easily remove the battery pack for charging, or replace the low-charge battery pack with another high-charge battery pack, or replace the defective battery pack with another good-condition battery pack.

[0039] Furthermore, when the battery pack is matched with the power tool 20, the battery pack on the garden robot 100 can be removed to power the power tool 20; or the battery pack on the power tool can be removed to power the garden robot 100. For example... Figure 7As shown, the power tool 20 can be a garden tool such as a lawnmower, lawn trimmer, pruning machine, hair dryer, chainsaw, snowplow, etc.; a torque output tool such as an electric drill or hammer drill; a sawing tool such as a circular saw, jigsaw, or reciprocating saw; or a grinding tool such as an angle grinder or sander. Alternatively, when the battery pack is matched with the power station, the battery pack on the garden robot 100 can be removed to power the power station; or the battery pack on the power station can be removed to power the garden robot 100. Thus, a single battery pack can be shared by the power tool, the power station, and the garden robot 100, improving battery pack utilization, reducing operating costs, and increasing convenience.

[0040] like Figure 8 As shown, the first battery pack 131 includes multiple battery cell units 1311 connected in series, parallel, or a combination of series and parallel connections. These multiple battery cell units 1311 are integrated within a battery casing 1312, forming a single unit. Specifically, each battery cell unit 1311 can be a lithium-ion battery cell. In one embodiment, the battery cell unit 1311 is a lithium iron phosphate battery. In another embodiment, the battery cell unit 1311 is a ternary lithium-ion battery. It is understood that the battery cell unit 1311 is not necessarily cylindrical; it can also be rectangular, blade-shaped, pouch-shaped, or other shapes. In one embodiment, the multiple battery cell units 1311 can include two or more different types of cells, such as 18650 and 21710 cells, lithium iron phosphate cells and ternary lithium-ion cells, liquid cells and solid / semi-solid cells. In one embodiment, the battery cell unit is a multi-tab cell.

[0041] In one embodiment, the power supply assembly includes multiple energy storage devices. These energy storage devices can discharge in parallel, in series, or in a series-parallel combination. In one embodiment, two first battery packs 131 with a rated voltage of 55V are connected in parallel, allowing them to discharge at their rated voltage of 55V. In another embodiment, two first battery packs 131 with a rated voltage of 55V are connected in series, allowing them to discharge at their rated voltage of 110V. The rated voltage of the first battery pack is 55V in the above example; in other embodiments, the rated voltage of the first battery pack 131 can also be 24V, 48V, 72V, etc.

[0042] The power supply assembly 130 also includes a battery management system (BMS). The BMS is mainly used to manage the charging and discharging of the aforementioned energy storage device and has functions such as overvoltage protection, undervoltage protection, overcurrent protection, temperature protection, and cell balancing. In one embodiment, the BMS includes a power monitoring module for real-time monitoring of the energy status and dynamic adjustment of the power distribution of the garden robot 100 through an energy consumption optimization algorithm to extend its battery life. When the garden robot 100 has low battery power, it notifies the control unit 170 so that the control unit 170 can control the garden robot 100 to return to the charging station 200 for charging.

[0043] The garden robot system 10 supports the integration and automated control of multiple tool modules 150, including a mowing module 151, a blower module 152, and a pruning module 153.

[0044] The mowing module 151 can be mounted on the abdomen of a dog-like robot, surrounded by the bionic limb structure 121, or it can be mounted on the chassis of a humanoid robot. The mowing module 151 includes a motor and a mowing blade driven by the motor. In one embodiment, the mowing module 151 adopts an integrated blade design, integrating the mowing blade and a height adjustment device. The blade is connected to the robot's chassis via a mechanism such as a four-bar linkage or a hydraulic / pneumatic adjustment mechanism, and supports vertical stroke adjustment of 20-100mm. The height adjustment device incorporates a high-precision encoder, which, combined with a vision sensor, collects real-time data on lawn height and density, and spatially matches this data with coordinate information fed back from a position sensor to dynamically adjust the blade's height above the ground (up to millimeter-level accuracy) and blade speed (e.g., adjustable from 2000-4000 rpm). In another embodiment, the mowing module 151 is fixedly mounted to the robot's main body 110, and the height of the main body 110 is adjusted through other structures of the robot itself, such as the bionic limb structure 121, thereby changing the height of the blade. See also... Figure 5The robot's mowing module 151 is surrounded by bionic limb structures 121. Each limb of the bionic limb structure 121 is equipped with three active degrees of freedom joints (hip, knee, and ankle joints). Through sensor arrays installed on the abdomen or head, the control unit 170 can perceive the suspension state of the blade head relative to the ground in real time. When terrain undulations are detected by sensors such as stereo vision and radar, the control unit 170 automatically calculates the optimal joint angle combination based on inverse kinematics algorithms, allowing the robot to lie stably in a bionic posture, ensuring that the blade head is always suspended at a constant height above the ground. When working on slopes or uneven terrain, the control unit 170 dynamically adjusts the force distribution of the limbs to achieve precise control of the cutting height. This innovative bionic adjustment method not only significantly improves the mowing coverage in complex terrain but also simplifies the system design by reusing the robot's original motion mechanism, achieving energy savings of more than 15% compared to traditional lifting chassis solutions. In addition, when encountering obstacles, the control unit 170 can quickly perform an abdomen-lifting action to protect the blade head and automatically return to the ground-hugging state after the obstacle is cleared. The entire process requires no manual intervention, fully demonstrating the design concept of intelligence and adaptability. See Figure 6 According to safety regulations, the mowing module 151 also includes a protective cover 1511 to prevent stones and other debris from splashing out when the blade 1512 is mowing.

[0045] In terms of control, the control unit 170 uses a deep learning algorithm built on ResNet-18 or other models to automatically divide the work area by analyzing the texture features of the lawn, generating zigzag or spiral mowing paths, and triggering a pressure-boosting cutting mode for high-density areas (>80% coverage), increasing the blade speed to 4500 rpm. The adaptive control system uses pre-stored templates of common grass species parameters, automatically optimizing cutting parameters after matching the templates based on visual features. For example, when the cutting height for warm-season grass species is set to 40mm, the system adjusts the blade angle to 5° to reduce grass tearing. During operation, the module and the main control system share workload, energy consumption, and path coverage data in real time, generating multi-dimensional operation logs for reinforcement learning model training, improving path planning efficiency after several iterations.

[0046] The hair dryer module 152 can be mounted on the side of the robot, held in the hand of the humanoid robot, or installed via the modular interface 140. Notably, the humanoid robot's bionic hand can hold various power tools, such as hair dryers and pruning machines, in a human-like manner, using readily available commercial tools without requiring modification. In one embodiment, such as... Figure 3As shown, the blower module 152 is generally cylindrical and is mounted to the robot body 110 via at least two mounting portions at the front and rear. The rear end of the blower module 152 includes an air inlet, a brushless motor, and a duct, all three disposed on or within the cylindrical housing and axially distributed from rear to front. In one embodiment, the motor has a rated power of 800W. In one embodiment, the rear mounting portion is rotatably mounted to the robot body 110 via a pivoting mechanism, and the rear mounting portion is disposed on or formed in the housing of the blower module 152. In one embodiment, the blower module 152 is electrically connected to and powered by a power supply assembly 130 disposed on the body 110, wherein the wires can pass through the pivot shaft of the pivoting mechanism. The front end of the blower module 152 includes an air outlet and a front mounting portion, wherein the front mounting portion is slidably mounted on the robot's forelimb via a slide rail mechanism, thereby changing the blowing angle of the air outlet. Specifically, the front mounting part can be a collar, and the outside of the air outlet pipe is wrapped and fixed by the collar. The collar is coupled with the sliding part of the slide rail mechanism. The slide rail is set on the outside of the robot's forelimb in a roughly vertical direction. The sliding of the front end, together with the pivoting of the rear end, achieves the adjustment of the air outlet angle.

[0047] In terms of control, the intelligent control system housing identifies the distribution density of scattered debris using millimeter-wave radar, and detects the ground material using a pressure sensor or visual sensor, dynamically adjusting the motor speed and the angle of the air outlet. In some embodiments, the blower has different speed settings corresponding to different motor speeds, including a Boost mode. In some embodiments, the blower module 152 has different cleaning modes. For example, in spot cleaning mode, the system identifies areas where debris accumulates using a convolutional neural network and controls the air outlet to focus on powerful cleaning within a small area. In area cleaning mode, a coverage path is generated based on a deep learning algorithm, and cleaning is advanced in a serpentine trajectory. In particular, when a damp surface is detected (humidity greater than or equal to a certain threshold), it automatically switches to an intermittent pulse mode (e.g., 0.5Hz frequency fluctuation) to improve the removal efficiency of fallen leaves and grass clippings.

[0048] Similar to the blower module 152, the pruning module 153 can be directly mounted on the robot's limbs, held in the hand of a humanoid robot, or installed via the modular interface 140. The pruning module 153 includes a motor, a transmission mechanism, and blades. The motor converts electrical energy into mechanical rotational motion, which is transmitted to the blades via a gear reduction mechanism and an eccentric transmission structure to complete the cutting. The eccentric block converts the motor's rotational motion into the reciprocating motion of the blades, thereby achieving the reciprocating cutting of branches and the purpose of pruning. Taking a robot as an example, the pruning module 153 is integrated into or mounted on the side of the robot's limbs. In one embodiment, the blower module 152 and the pruning module 153 can be respectively located on both sides of the robot's main body 110. In one embodiment, the pruning shears are mounted at the knee joint of the robot's forelimbs. The robot's limbs can rotate freely and remain stable in their respective positions, ensuring the flatness of the cut surface and avoiding oblique cuts or burrs. Figure 6 As shown, the robot can raise its forelimbs using motors mounted on its hip joints, thereby raising the pruning shears; alternatively, the robot can raise its forelimbs and main body 110 as a whole to mimic a human standing posture, further raising the pruning shears to meet different pruning height requirements. Preferably, in this case, the two hind limbs can mimic human walking in a biomimetic gait mode. That is, the robot's biomimetic gait mode can be further subdivided into a quadrupedal walking mode and a hind limb walking mode, and can switch between these two modes. In one embodiment, using motors mounted on the knee joints and feedback data from posture sensors or vision sensors, the control unit 170 can maintain a cutting plane levelness error of <1° under ±15° tilt conditions, thereby meeting the requirements for cut flatness. Specifically, a servo motor or stepper motor can be used for driving, and a harmonic reducer or gearbox can be used to increase torque output, ensuring precise rotation (e.g., within a ±180° range) and angle locking of the pruning module 153. In one embodiment, the blower module 152 needs to be removed before the garden robot 100 switches to the hind limb walking mode.

[0049] In terms of control, leveraging advanced visual recognition technology and motion planning algorithms, the robot can accurately locate the cutting point of branches, supporting multi-angle (e.g., horizontal, vertical, inclined) and differentiated length (e.g., thinning, shortening) pruning needs, thus improving the adaptability of gardening operations. The system can also preset different pruning speeds and trimming modes, for example, automatically activating an oscillating sawing mode (e.g., frequency 50Hz, amplitude 2mm) for branches with larger diameters. During task execution, the system continuously records pruning parameters (e.g., cutting force, frequency, branch diameter, etc.) and analyzes the data through machine learning algorithms to continuously optimize the motion trajectory and force control strategy. This feedback mechanism not only improves the completion quality of a single task but also provides data support for long-term performance upgrades, ultimately achieving a pruning effect that becomes increasingly intelligent with use. During pruning, the motion planning algorithm can generate the optimal cutting path based on RRT* (Rapid Exploration Random Tree) and record cut roughness, cutting time, and energy consumption data. A parameter correlation model is established through a Long Short-Term Memory (LSTM) network, improving pruning efficiency and reducing blade wear after multiple operation cycles.

[0050] In addition to the aforementioned tool modules 150 for mowing, blowering, and pruning, in some embodiments, the garden robot system 10 may also have more optional tool modules 150, such as chainsaw modules, pole saw modules, grass trimming modules, and brush cutter modules. The chainsaw module is equipped with a drive motor that provides the torque required for high-speed chain operation. A chain guide plate provides precise guidance, enabling continuous cutting. An automatic lubrication device supplies oil to the chain through a specific oil circuit to reduce friction and wear. A safety guard blocks flying debris. Jamming and overheating sensors trigger alarms or stop the equipment in case of abnormalities. Its modular interface 140 can be connected to the robot's limbs. Built-in posture sensors communicate with the control unit 170, supporting automatic posture adjustment and enabling multi-angle cutting. This allows it to efficiently cut thick tree trunks and branches with its high-speed chain and optimized torque output. Automatic lubrication extends equipment life, safety protection ensures personnel safety, and flexible adaptation to complex environments allows for seamless integration with the robot platform. The lever saw module employs a retractable operating lever that can be extended to a high position via an electric or pneumatic telescopic mechanism. It features a miniature chainsaw cutting head with lightweight cutting capabilities for small-diameter branches, an adjustable-angle saw head connector that allows the operating head to pitch and rotate within a certain range, a stabilization sensing system that monitors the operating lever's attitude in real time and automatically adjusts the robot platform's stability, and a robot vision recognition system that works in conjunction with the system. After the robot locates the target branch, it automatically extends its arm to perform the operation, facilitating high-altitude work, achieving precise cutting, ensuring operational safety, and reducing manual labor intensity. The mowing module uses a high-speed rotating thread head made of safe and flexible nylon rope or polymer thread. In some embodiments, it may also selectively include an angle adjustment structure that can finely adjust the mowing angle according to the terrain, an anti-entanglement structure to prevent grass clippings and debris from tangling around the main shaft, and a remaining thread sensor that indicates replacement or automatically supplies thread. It is suitable for installation on a robot's lightweight actuator arm or rotatable interface and has flexible turning capabilities, thereby enabling precise mowing, trimming, and other operations, facilitating use, and enhancing adaptability to complex environments. The brush cutter module uses multi-tooth metal blades or serrated disc blades with strong cutting capabilities, a high-power direct-drive motor that can increase rotation speed and maintain stable output, a multi-segment protective cover to block splashes and a shock-absorbing handle structure to reduce vibration transmission, and a load monitoring module that monitors cutting resistance in real time and intelligently adjusts output power to prevent motor burnout. This enables efficient brush cutting, ensures safe and comfortable operation, and intelligently protects the motor to reduce maintenance costs. It is especially suitable for initial clearing operations in undeveloped areas or large green spaces.

[0051] One way to utilize the different tool modules 150 is for the aforementioned humanoid robot's bionic hand to hold various power tools 20 in a human-like manner, using readily available power tools in a human-like way, which will not be elaborated here. Another way to utilize them is to use a specific modular interface 140 to match various tool modules 150. Bionic hands have many joints and are relatively expensive; moreover, the compatibility of readily available power tools with the garden robot 100 may not be ideal. For example, when the garden robot 100 encounters a power tool it has never used before, it may need some learning and practice. Compared to the former method, using the modular interface 140 with a work head (also referred to as tool module 150 in this application) to perform the target work can achieve more stable installation of the tool module 150 and more precise and flexible control of the tool module 150 at a lower cost. Different tool modules 150 can be replaced autonomously by the robot or under the user's operation. In one embodiment, such as Figure 2 As shown, one of the robot's hands is a simulated robotic arm 1213, and the other hand is a modular interface 140. The robot uses its multi-degree-of-freedom simulated robotic arm 1213 to grasp the target tool module 150. Combining visual guidance (such as RGB-D camera positioning) and force feedback control (such as a 6-axis torque sensor), the robot can install or remove the tool module 150 from the modular interface 140, achieving sub-millimeter precision insertion and removal operations. The modular interface 140 is a key component enabling rapid replacement and automatic identification of different tool modules 150. Its standardized design ensures compatibility, reliability, and scalability. The system consists of three main parts: a physical connection interface, an automatic docking mechanism, and an automatic identification mechanism. It supports hot-swapping operations and plug-and-play functionality, significantly improving the robot's function switching efficiency and task adaptability.

[0052] The physical connection interface is used to couple the interfaces on the robot body with different tool modules 150. In some embodiments, the interfaces on the robot body can be located on the limbs, such as the elbow joint. The physical connection interface includes electrical connection interfaces and mechanical connection interfaces. The electrical connection interface can use multi-pin gold-plated contacts or wireless inductive power supply technology to provide stable power transmission and high-speed bidirectional data communication, supporting voltage / current adaptive adjustment to ensure safe operation of tool modules 150 with different power requirements; the data channel uses a differential signal transmission protocol to enhance anti-interference capabilities. The mechanical connection interface can be a snap-fit ​​interface, a slide rail interface, or a magnetic interface. In one embodiment, the mechanical connection interface uses a spring locking device with a guide groove to achieve precise positioning and rigid fixation of the module; in another embodiment, the mechanical connection interface can use an electromagnetic adsorption mechanism, using controllable magnetic force for quick assembly and disassembly, suitable for lightweight, high-frequency replacement scenarios. Both designs can integrate a foolproof structure to prevent damage to the interface due to misoperation. The mechanical connection design of the modular interface 140 is specifically designed for durability in outdoor environments. For example, the electrical connection interface uses a spring-loaded pin structure with an IP67 waterproof rating to prevent water seepage and short circuits during rainy weather operations; while the mechanical connection interface (such as a rotating buckle with a self-cleaning function) can effectively resist the intrusion of grass clippings and soil. When it is necessary to change tool module 150 (for example, switching from the grass trimming module to the brush cutter module), the robot can locate the target module in the storage compartment through the onboard vision system (such as a wide-angle camera mounted under the chassis) and use a force feedback manipulator (such as a three-finger gripper equipped with strain gauge sensors) to complete the grasping.

[0053] In one embodiment, the robot is equipped with an automatic docking mechanism for physical connection interfaces. For example, it is equipped with an infrared / ultrasonic proximity sensor and a servo drive mechanism. When the tool module 150 enters the docking range (e.g., ≤10cm), the system automatically activates the guidance program, completes the docking with millimeter-level precision through visual assistance or mechanical self-calibration, and provides real-time feedback on the connection status to the main control system through pressure sensors and circuit continuity detection.

[0054] An automatic identification mechanism is used to identify information about the tool module 150 connected to the robot's interface before or after the physical connection interface is connected. This information is at least used to identify the type of the connected tool module 150. In one embodiment, each tool module 150 embeds a uniquely identified RFID tag and / or integrates a readable and writable smart chip (such as an EEPROM with an I²C interface) to store metadata such as module model, firmware version, and calibration parameters. In one embodiment, the identification method may also be to scan a QR code / barcode on the module housing using a laser. That is, the control unit 170 includes an RFID tag, a smart chip, or a QR code recognition module. In one embodiment, multiple identification methods can coexist and mutually verify each other or serve as redundant backups.

[0055] In one embodiment, after detecting a physical connection, the control unit 170 immediately initiates an identification process: first, it reads the RFID to obtain basic information, then accesses the detailed configuration in the smart chip via the data bus, and finally completes drive matching within ≤200ms. Furthermore, the control unit 170 maintains a dynamically loaded algorithm library and supports OTA updates of control strategies and parameter presets for newly added modules.

[0056] In some embodiments, multiple tool modules 150 can be controlled collaboratively. Collaborative working modes include: (1) Parallel mode—multiple tool modules 150 work simultaneously, for example, the mowing module 151 and the blower module 152 operate synchronously to blow away the cut grass clippings; (2) Sequential mode—tool modules 150 are activated sequentially according to the process, for example, the mowing module 151 and the trimming module first perform large-area cutting of the lawn, and then use more refined trimming operations to make the lawn more beautiful; (3) Fault-tolerant mode—when a module fails, a backup module is automatically called or the workflow is adjusted, for example, the mowing module 151 and the trimming module, when the mowing blade fails, the trimming module can also be used to cut the lawn. The resource allocation module of the control unit 170 dynamically monitors the energy consumption and bandwidth utilization of each interface, and optimizes the task allocation strategy through a genetic algorithm.

[0057] Optionally, the garden robot system 10 has a work head storage container 300, such as Figure 9 As shown, the tool head storage unit 300 has a accommodating section for storing and managing the optional tool modules 150. The accommodating section can be semi-open, such as a cavity with an opening or a basically exposed mounting base. The tool head storage unit 300 supports two deployment schemes to adapt to different application scenarios: one is a built-in storage unit installed inside the robot body 110 (e.g., drawer structure, flip-top structure) or externally mounted (e.g., rear modular slot / card slot). Preferably, it adopts a lightweight alloy frame and shock-absorbing design to ensure the stability of the tool modules 150 during movement, suitable for applications requiring frequent changes in working environment, such as field inspections; the other is a fixed storage unit, set in a dedicated tool rack or intelligent storage cabinet within the work area, supporting high-density storage (e.g., matrix-style arrangement of compartments). Preferably, it is equipped with temperature and humidity control and a dustproof sealing design to ensure that the tool modules 150 are not easily aged or damaged during long-term storage, suitable for relatively fixed working environments, such as gardening. The tool head storage unit 300 is specifically designed for the characteristics of garden tools. For example, the built-in storage compartment uses an open mesh structure (such as a 304 stainless steel woven mesh bag) to ensure that the tools are ventilated and protected from rust, while also allowing for the quick removal of grass clippings and debris.

[0058] In one embodiment, the workhead storage container 300, fixed in a specific area, can be shared by multiple robots. The tool modules 150 within the workhead storage container 300 can also be redundant. For example, in a commercial scenario, multiple robots work collaboratively, autonomously returning to the shared workhead storage container 300 to replace or call upon suitable tool modules 150. In some embodiments, the workhead storage container 300 and the control unit 170 can communicate to exchange data, achieving optimal configuration and control of the tool modules 150. For example, the workhead storage container 300 has a built-in IoT communication module that collects parameters such as the inventory quantity of tool modules 150, their lifespan (e.g., usage hours), health status, and calibration offset, and uploads them to a cloud server / database 400. The workhead storage container 300 supports wireless communication, including Wi-Fi, Bluetooth, or cellular data, and can interact with the control unit 170 through point-to-point or cloud sharing. The storage compartment has a built-in RFID reader (e.g., a UHF band anti-metal interference model) that can automatically record the usage time of each module and generate maintenance reminders (e.g., prompting for gearbox lubrication after a certain number of accumulated working hours).

[0059] The control unit 170 can generate an optimal tool configuration scheme based on task instructions (such as process documents or real-time sensor data), and dynamically select the tool module 150 by combining module performance parameters (such as accuracy and power consumption) and the current inventory status of the working head storage 300. In one embodiment, when the garden robot 100 performs an autumn leaf clearing task, it will prioritize calling the blower module 152 and plan the optimal working path based on the tree distribution data recorded by GPS. In another embodiment, when the garden robot 100 detects that the tool wear exceeds the standard (e.g., through current analysis) and the working head storage 300 has the same tool in stock, it automatically triggers a replacement process.

[0060] Furthermore, the workhead storage unit 300 can automatically generate tool usage logs and maintenance reports to optimize future task execution strategies and tool configurations. For example, it can train predictive maintenance models (such as LSTM neural networks) based on historical data to trigger module maintenance or replacement requests in advance. In one embodiment, tool usage logs can be linked to task work orders to optimize module allocation strategies (e.g., frequently used tools are prioritized for placement in easily accessible locations). The above-mentioned setup of the workhead storage unit 300 improves the operational efficiency and flexibility of the garden robot 100 in different task scenarios, and enhances the efficient scheduling and intelligent management capabilities of multi-module tasks.

[0061] Sensor component 160 provides comprehensive data support for environmental perception, tool recognition, and task feedback, providing various operational data for the garden robot 100. The garden robot 100 is equipped with a multimodal sensor array, achieving dual protection for environmental perception and operational safety. Sensors can be installed on various parts of the robot, such as its head, body, and robotic arm. The vision sensor, as the core perception unit, acquires visual data about the garden robot 100's surroundings. For example, using a wide-angle camera in conjunction with deep learning algorithms, it can complete lawn boundary modeling, obstacle recognition, vegetation type recognition, and dynamic path planning. In one embodiment, when the system detects a sudden animal intrusion into the lawn (such as recognizing a rabbit's outline), the vision module will trigger the path planning system to generate an emergency avoidance trajectory. LiDAR sensors provide centimeter-level accuracy in environmental mapping; for example, by constructing a 3D point cloud map of the garden using 16-line radar scanning, it can accurately identify the spatial location of complex obstacles such as landscape stones and sculptures. In some operational scenarios, control unit 170 can automatically mark protected components to ensure a safe distance of more than 20cm during robotic arm operation. In some embodiments, to cope with special working conditions, the garden robot 100 integrates a multi-band infrared sensor. For example, in dawn or foggy weather, the 850nm infrared array can penetrate low-visibility environments to detect pebbles hidden in grass or the edges of drainage ditches. In nighttime operation mode, the sensor, in conjunction with supplemental lighting (e.g., using invisible light wavelengths), can maintain 80% detection accuracy in complete darkness. In some embodiments, the garden robot 100 is equipped with a temperature sensor for thermal management of the tool module 150. For example, during continuous pruning operations, the temperature sensor collects gearbox temperature data in real time; when an abnormal temperature rise is detected, the system automatically reduces the motor speed and triggers an alarm. For high-risk scenarios (e.g., cutting dry, dead branches), the control unit 170 limits the tool's continuous operating time to a predetermined time, such as 15 minutes, to prevent friction-induced fires. Furthermore, the power supply components of the garden robot 100 are typically equipped with temperature sensors for battery thermal management. In some embodiments, the garden robot 100 is equipped with a force feedback system to ensure the safety of delicate operations. A six-dimensional force sensor is embedded in the end effector of the robotic arm, for example, to monitor blade resistance in real time when pruning shrub balls; when an abnormal load is detected (e.g., the branch diameter exceeds a preset threshold), the system immediately stops cutting and switches to manual review mode. During blower operations, force sensor data can be used to dynamically adjust the blower tilt angle. For example, based on changes in reaction force, it can automatically maintain the optimal distance between the blower head and the ground, such as 8-12cm, ensuring both operational efficiency and preventing excessive dust generation. The positioning sensors of the Garden Robot 100 can employ a combination of GNSS or RTK sensors and IMU sensors to balance accuracy in outdoor operations with robustness in complex terrain.GNSS provides global positioning (meter-level accuracy) via satellite signals, suitable for path planning in open lawns, but is susceptible to obstruction by trees and buildings. RTK uses ground or virtual base stations to correct signals, improving positioning accuracy to centimeter-level, ensuring precise obstacle avoidance or operation along set boundaries (such as flower beds or lawn edges), but it relies on base station coverage and is costly. IMU uses inertial measurement to sense the robot's acceleration and turning angular velocity in real time, maintaining pose estimation even during brief GNSS signal interruptions (such as passing through tree shade or arches), but its errors accumulate over time. In practical systems, all three are usually used in combination: RTK provides high-precision absolute positioning in open areas, IMU compensates for motion details and handles short-term obstruction, and GNSS serves as a global position reference to calibrate IMU drift. This combination ensures that the garden robot 100 can stably perform tasks such as pruning and sowing in complex terrain, while reducing the risk of loss of control in positioning blind spots. Furthermore, SLAM, laser, and radar positioning methods can be integrated to obtain more accurate and robust positioning methods, which will not be elaborated here.

[0062] As the core decision-making hub of the garden robot 100, the control unit 170 undertakes the core functions of data processing, algorithm execution, and task scheduling. The control unit 170 processes multi-source sensor data in real time through a heterogeneous computing architecture (e.g., an integrated low-power ARM processor). At the data processing and optimization level, it achieves centimeter-level accuracy autonomous navigation and intelligent obstacle avoidance through multi-sensor fusion technology, such as using a binocular vision camera to identify lawn boundaries, a six-axis IMU to detect terrain slope, a position sensor to obtain precise coordinates, and a near-infrared sensor to distinguish vegetation types. For example, in a lawn mowing task, when the vision system detects an obstacle, the control unit 170 integrates attitude sensor data with historical work paths to replan the detour trajectory and raise the cutter head height to avoid collisions.

[0063] With the intelligent support of deep learning and reinforcement learning algorithms, the control unit 170 exhibits significant advantages in path planning and tool optimization. In a typical embodiment, the control unit 170 uses a convolutional neural network (CNN) to analyze the vegetation density distribution map collected by the infrared sensor, automatically generating pruning paths and increasing the coverage rate to over 98%. Simultaneously, it continuously optimizes the optimal cutting height for different grass species through a Q-learning algorithm, reducing the pruning evenness error to the millimeter level after multiple task iterations. Multi-source data fusion technology (such as feature-level fusion of LiDAR point clouds and RGB images) endows the robot with precise environmental perception capabilities. For example, in pruning operations, the control unit 170 can analyze the branch diameter through visual information and automatically match an appropriate motor speed, improving pruning efficiency.

[0064] The control unit 170 also possesses a self-learning function, continuously improving its operational strategies through a feedback mechanism. During task execution, the control unit 170 records over 20 operating parameters (such as motor current fluctuations and tool vibration spectra) to establish a device health assessment model. For example, after the pruning module 153 has accumulated a certain number of hours of operation, the system predicts component wear trends by analyzing gearbox noise characteristics (FFT spectrum comparison) and triggers maintenance reminders in advance. This self-optimization capability has shown significant results after multiple task iterations: for standardized lawn areas, after the robot's operational path has been optimized through learning, task time has been reduced by more than 20%, and battery life has been extended by 18% to 20%. In addition, the control unit 170 can also maintain synchronization with a cloud-based horticultural database via a communication unit, for example, by periodically downloading pruning specifications for new ornamental plants to ensure that operational parameters comply with the latest horticultural standards.

[0065] In terms of mode management and task planning, the system supports intelligent switching and coordination of multiple modes such as mowing, blowing, and pruning. In one embodiment, when the system detects shrubs (e.g., through HSV color space analysis and point cloud density recognition), it automatically switches to pruning mode and calls the pre-stored plant database to adjust the tool's actions. When the image segmentation algorithm calculates that the leaf cover exceeds a certain threshold, the control unit 170 automatically activates the blowing mode and dynamically adjusts the collection path based on meteorological data (such as wind speed sensor readings)—for example, using a spiral progressive trajectory under crosswind conditions to ensure a leaf capture rate of over 95%. The task priority management system handles complex decisions through operations research models. In one embodiment, when both excessive lawn height and a rainstorm warning signal are detected simultaneously, the control unit 170 will instruct the robot to perform the mowing task in ultra-fast mode.

[0066] The control unit 170 also provides dual-mode operation, offering both remote control and autonomous operation to adapt to diverse scenario needs. In autonomous mode (e.g., nighttime maintenance of municipal parks), the robot automatically generates task sequences based on a preset horticultural calendar (including plant growth cycles and peak periods for pests and diseases). In remote control mode (e.g., pruning of villa courtyards), users can define customized work areas (e.g., circular flower bed patterns) through AR and other human-computer interaction interfaces. When the task is converted into the robotic arm's motion trajectory, the cutting depth is corrected in real time using force feedback. This intelligent mode management system allows a single device to replace the repetitive work of traditional landscaping teams, while simultaneously raising the precision of complex styling operations to the level of professional horticulturists.

[0067] The communication module 180, serving as the core channel for the garden robot 100 to interact with the outside world, employs a multi-mode collaborative design to ensure reliable connectivity in complex environments. Regarding communication methods, the system supports one or more wireless communication methods such as Wi-Fi, Bluetooth, and cellular networks. For example, 5G is prioritized for high-definition video transmission in open lawn areas, while switching to Bluetooth / Wi-Fi when entering pergola areas with severe signal obstruction. Of course, for special operating scenarios, such as ancient tree protection areas where electromagnetic interference needs to be avoided, the system provides a wired communication backup solution, enabling offline export of gardening logs via a waterproof USB interface, or firmware security upgrades using an industrial-grade Ethernet port. In some embodiments, the robot includes an RTK mobile station for positioning calibration, requiring communication with the RTK base station via radio waves; in other embodiments, the robot uses network RTK data for positioning calibration, which can be achieved through the aforementioned wireless communication methods. In some embodiments, data sharing between more devices can also be achieved through communication between the robot and the battery pack's data terminals. Figure 12 As shown, in order to improve work efficiency and effectively share information, the garden robot 100 can communicate not only with the cloud server / database 400, but also with the work head storage unit 300 and the charging pile 200.

[0068] The data interaction system is deeply integrated into the gardening operation process, enabling information management throughout the entire lifecycle. The data exchanged in real time between the system and the control platform not only includes standard status parameters such as cutter head speed and battery temperature, but also integrates specialized horticultural data streams. In a typical application scenario, the robot uses multispectral imaging technology to acquire vegetation health indices, and combines this with soil conductivity sensor data to automatically generate a visualized maintenance report for gardeners' reference. Remote control functionality enables precise operation through customized software. For example, in pruning ancient trees in historical gardens, experts can set cutting angle protection parameters via a PC interface. When the system translates these professional requirements into machine instructions, it simultaneously considers environmental variables such as real-time wind speed to ensure operational safety. The mobile application provides a convenient electronic fence setting function. For instance, after a user delineates a protected area for valuable flowers on a map, the robot's operating path will automatically maintain a safe distance of at least 50cm.

[0069] In terms of security, the communication module 180 constructs a multi-layered protection system. Data transmission employs a dynamic encryption strategy; for example, it automatically uses national cryptographic algorithms to protect operational data in public green space scenarios, while switching to a stronger hybrid encryption scheme when an enterprise intranet environment is detected. The physical layer protection design fully considers the characteristics of outdoor operations; for example, key communication interfaces adopt a military-grade dustproof and waterproof structure to ensure basic connectivity is maintained even in heavy rain. The communication module 180 is equipped with an intelligent self-healing mechanism. In one embodiment, when the wireless signal is interrupted due to lightning interference, the control unit 170 immediately activates a local caching mode, continuously recording operational data and automatically resuming transmission after the signal is restored. Simultaneously, it uses topology analysis to locate the breakpoint, providing a reference for subsequent communication optimization. These designs enable the communication module 180 to maintain transmission stability in diverse scenarios such as municipal parks and private gardens, providing reliable protection for intelligent horticulture operations.

[0070] The charging station 200 provides continuous energy for the garden robot 100, ensuring that it can replenish its energy in a timely manner and maintain an efficient working state during long-term task execution. For example... Figure 10 As shown, the charging station 200 can be deployed at a specific location within the work area via fixed installation or a portable design. The automatic recharging module of the control unit 170 allows the garden robot 100 to automatically navigate to the charging station 200 for charging when its battery is low or after completing its task, thereby enabling long-term independent operation and efficient work. In one embodiment, such as... Figure 11 As shown, the charging pile 200 and the workhead storage container 300 can be integrated, allowing them to share hardware such as power supply, communication chip, controller, and guidance markers, thus reducing production costs. In one embodiment, the charging pile 200 and the workhead storage container 300 can be housed in a single enclosure. The workhead storage container 300 can have accommodating sections of varying depths to accommodate tools of different sizes, thus making efficient use of the space saved by the shallower accommodating sections for charging interfaces. When the robot visits the workhead storage container 300 to change the tool module 150, it can charge its device simultaneously. The charging pile 200 supports high-power fast charging, such as 2C, 4C, and 8C fast charging, ensuring the robot can effectively replenish its energy when returning to the pile to change the tool module 150. For the robot, there is no need to separately locate the charging pile 200 and the workhead storage container 300, reducing communication requirements; for commercial users, there is no need to deploy the charging pile 200 and the workhead storage container 300 separately when entering a work environment, improving work efficiency.

[0071] Specifically, the charging station 200 includes a charging interface 210, a guidance label module 220, and a communication module 280. The charging interface 210 can charge the garden robot 100 using either wireless or wired charging. Wireless charging achieves energy transfer through electromagnetic induction or magnetic resonance, while wired charging achieves power transfer through an automatic docking device. The guidance label module 220 may include visual labels, infrared labels, or RFID tags for guiding the robot to precise docking. The communication module 280 of the charging station 200 and the robot's communication module 180 together support real-time data exchange between the charging station 200 and the garden robot 100, providing monitoring of charging status, equipment malfunctions, and power information.

[0072] The control unit 170 of the garden robot 100 integrates a power monitoring and path planning module. When the power level falls below a preset threshold or the task is completed, it automatically initiates a recharging mode. In recharging mode, the control unit 170 uses data from vision sensors, LiDAR, and infrared sensors to precisely locate and navigate the charging station 200. When the garden robot 100 approaches the charging station 200, it authenticates its identity and confirms its status through visual recognition or communication interaction. The garden robot 100 precisely docks with the charging station 200 using an automatic docking device (such as a robotic arm or adaptive docking interface) to ensure the stability and safety of charging. During charging, the control unit 170 continuously monitors the power level and charging progress, and automatically disconnects upon completion, re-entering standby or operating mode.

[0073] The garden robot system 10 supports self-learning and intelligent scheduling functions. By analyzing the energy consumption and charging efficiency of each task, it continuously optimizes charging timing and path planning. During long-duration tasks, the robot can automatically determine whether it needs to be charged midway and optimize the charging route, thereby reducing unnecessary travel distances and waiting time. When multiple garden robots 100 work simultaneously, the charging station 200 can intelligently schedule the charging order and priority of different robots, avoiding conflicts and waste of charging resources.

[0074] In one embodiment, the charging pile 200 and the control unit 170 maintain real-time data transmission via wireless communication (such as Wi-Fi, 5G, etc.). The remote control platform can monitor and manage the charging status of the charging pile 200 and the garden robot 100, providing power reports and fault diagnosis functions. The system supports remote wake-up and automatic recovery functions, and can automatically trigger an emergency recharging procedure when insufficient power or an abnormal state is detected. By introducing an automatic recharging mechanism and the charging pile 200, the garden robot system 10 of this application achieves more complete energy management and adaptive operation capabilities, providing strong support for intelligent operation during long-term continuous work.

[0075] The following describes, in conjunction with the aforementioned components, the process by which the garden robot 100 autonomously completes lawn mowing and sweeping tasks. After the garden robot 100 is started, the control unit 170 first automatically detects the installed tool module 150 through the modular interface 140. When the mowing module 151 is connected to the robot body 110, the system confirms that the current tool is the mowing module 151 through the aforementioned automatic identification mechanism and automatically loads the corresponding control algorithm and parameter configuration.

[0076] As the robot moves through the lawn area, visual sensors and LiDAR scan the lawn in real time, collecting data on its height, density, and distribution. The visual sensors capture images of the lawn and use image processing algorithms to identify the height and density of the grass blades; the LiDAR precisely measures the height of the grass clumps, constructing a three-dimensional contour model of the lawn. The control unit 170 uses data fusion technology to integrate the data from the visual sensors and LiDAR, generating a real-time status map reflecting the overall condition of the lawn.

[0077] Based on the lawn condition diagram and task requirements, the control unit 170 optimizes the mowing strategy. When the lawn is detected to be tall and dense, the blade height automatically increases to reduce resistance, while the blade speed decreases to prevent motor overload. When the lawn is short or sparse, the blade height decreases and the speed increases, thereby improving mowing efficiency and accuracy. Simultaneously, the path planning algorithm calculates the optimal path based on the lawn's density and shape, avoiding repetitive work and missed areas, and dynamically adjusts the path curvature and coverage during operation to ensure efficient operation.

[0078] During actual operation, the height adjustment device in the mowing module 151 receives instructions from the control unit 170 and drives the blades up and down via a motor-driven screw structure, achieving millimeter-level precision adjustment. The blade motor's speed is controlled by a PWM signal and adjusted via a frequency converter driver. Simultaneously, a force sensor monitors the force changes on the blades during the cutting process in real time and feeds the data back to the control unit 170. When the blades encounter resistance or excessive load, the system automatically reduces the speed and increases the height to avoid jamming or equipment damage.

[0079] In one embodiment, while mowing, the turbine fan of the blower module 152 is started, the system automatically adjusts the nozzle angle and wind speed, and uses visual recognition technology to accurately locate residual grass clippings and debris, blowing the grass clippings and debris to the predetermined position.

[0080] After the mowing operation is completed, the control unit 170 generates a task report containing multiple dimensions, including the mowing area, time taken, blade height and speed adjustment records, mowing effect and grass clipping residue rate, as well as detailed information such as energy consumption and efficiency analysis. Finally, this report is uploaded to the remote control platform via the communication module 180 for operators to view and analyze. The entire process achieves fully automated, high-precision, and high-efficiency operation of lawn mowing and sweeping tasks.

[0081] The following describes, in conjunction with the aforementioned components, the process by which the garden robot 100 autonomously completes the tree branch pruning and cleaning tasks. In the tree branch pruning and cleaning task, the garden robot 100 first identifies the installed tool module 150. Through the modular interface 140, the control unit 170 reads the RFID tag or smart chip information on the pruning module 153 and loads the corresponding control algorithm and parameter configuration. The robot can change different working heads according to the working conditions, such as electric shears, reciprocating blades, and a saw, to adapt to the pruning needs of branches of different thicknesses and heights.

[0082] After the task begins, the garden robot 100 scans the target area using visual sensors and LiDAR, and constructs a 3D model of the tree branches. The visual sensors identify the shape, position, and growth angle of the branches, while the LiDAR provides precise distance information and thickness measurements. After multi-source data fusion processing, the data from both sources forms a digital scene map containing the structure, position, and features of the tree branches.

[0083] Based on the scene diagram and task requirements, the control unit 170 performs optimized calculations for the pruning strategy. For thicker branches, the system selects to use a cutting saw blade, while adjusting the extension length and cutting angle of the robotic arm to ensure a smooth cut without excessive damage. For thinner or softer branches, the system prioritizes using electric shears for pruning, automatically adjusting the opening and closing angle and pressure of the shears to avoid damage or breakage during the cutting process.

[0084] The actions of the pruning module 153 are optimized and adjusted in real time by the control unit 170. The system employs an adaptive control algorithm to precisely locate the working area of ​​the pruning tool based on the thickness and position of the target branch. The movement speed of the shears and saw blades is regulated by a PWM control signal, and the force situation during the cutting process is monitored by a built-in force sensor. When excessive resistance or unsatisfactory cutting results are detected, the system automatically optimizes the cutting parameters, such as reducing the speed, increasing the cutting force, or changing the cutting angle, to ensure the quality and efficiency of pruning.

[0085] When the currently installed working head cannot meet the intended requirements, such as when the target branch to be cut is too high or too thick, the garden robot 100 will return to the working head storage 300 to replace the working head, for example, by replacing it with a chainsaw, pole saw, or long-pole pruning machine. After the pruning task is completed, the garden robot 100 will perform a cleaning task. Through the automatic changing device in the working head storage 300, the pruning module 153 is safely returned to the designated position, and then the blower module 152 is installed. After the turbine fan is started, the control unit 170 adjusts the nozzle angle and wind speed, and uses a vision sensor to identify debris and leaves generated during the pruning process. During the cleaning process, the system dynamically adjusts the wind speed and direction to ensure that debris is collected in the predetermined collection area or garbage bag.

[0086] After the cleaning operation is completed, the control unit 170 generates a task report, which includes information such as the number and type of branches pruned, the frequency and efficiency of pruning shears and saw blades, the cleaning effect and residue rate, and energy consumption and efficiency analysis. The task report is uploaded to the remote control platform via the communication module 180 for operators to record and analyze. Simultaneously, the system continuously optimizes the pruning and cleaning algorithms based on feedback data during the operation to improve the efficiency and accuracy of future tasks. The entire process achieves fully automated operation from branch pruning to cleaning, and improves the accuracy and adaptability of the operation through intelligent control and self-learning capabilities.

[0087] The following description, using the aforementioned components as an example, illustrates the process by which the garden robot 100 autonomously schedules and uses multi-functional tools according to the target task. Through the integrated workhead storage 300 and control unit 170, the garden robot 100 can automatically select, configure, and schedule different tool modules 150 according to the needs of the current task. The entire process includes the storage management of tool modules 150, automatic identification and replacement, task planning and execution, and optimized control of multi-tool collaborative work.

[0088] The garden robot 100 is equipped with a tool head storage container 300, which can be configured inside or outside the robot body 110, such as being installed on a garden cart, tool rack, or fixed operating platform. The storage container includes multiple storage units for tool modules 150, each equipped with an automatic locking device and a power interface to ensure stable placement and power supply of the tool modules 150. When the robot enters the storage container area or near the tool rack, the system automatically detects the currently available tool modules 150 and updates the tool list and status information.

[0089] The task execution process begins with the control unit 170 identifying and analyzing the task type. The system determines the current work requirements, such as mowing, pruning, or sweeping, through a remote control platform or a local task list. Based on the task type and environmental perception data of the target area (including scene maps collected by visual sensors and LiDAR), the control unit 170 determines the type of tool module 150 required and the optimal configuration. In some embodiments, during the robot's patrol, the control unit 170, in conjunction with data input from the sensor components 160, automatically determines the type of task to be performed and installs and controls the appropriate tool module 150 to execute the corresponding task through the modular interface 140.

[0090] Once the required tool module 150 is identified, the robot automatically retrieves the corresponding tool module 150 from the repository via a robotic arm or module interface device. During the retrieval process, the system verifies the type and status of the tool module 150 through an automatic identification mechanism and executes a self-test procedure to ensure the integrity of the module's functionality. The installation of the tool module 150 adopts an integrated mechanical and electrical connection design, with an automatic locking device and a docking power interface working together to ensure the stability and safety of the module installation.

[0091] After the tool module 150 is installed, the control unit 170 automatically loads the corresponding control algorithm and adjusts the working parameters according to the task requirements. For example, in a lawn mowing task, the control unit 170 sets the blade speed and height according to the height and density of the lawn; in a pruning task, the control unit 170 adjusts the opening angle and / or cutting speed of the electric shears and / or saw blades; and in a sweeping task, the control unit 170 adjusts the wind speed of the turbine fan and the angle of the nozzle.

[0092] To enable multi-tool collaborative operation, the control unit 170 incorporates a multi-module management algorithm. This algorithm supports parallel operation of tool modules 150 and dynamic adjustment of task priorities. For example, when performing large-area lawn mowing, the mowing module 151 and the blower module 152 can work collaboratively. The mowing module 151 is responsible for the front-end cutting work, while the blower module 152 cleans up residual grass clippings and debris in real time. Through the collaborative scheduling algorithm, the system can dynamically allocate the workload of different modules according to the progress and effect of the current operation, thereby improving the overall efficiency and accuracy of the task.

[0093] Furthermore, the control unit 170 possesses self-learning capabilities, enabling it to analyze and optimize process data after each task. Through deep learning and reinforcement learning algorithms, the system can identify the optimal operating parameters and configuration strategies for the tool module 150. For example, after multiple lawn mowing tasks, the system automatically optimizes the mowing path and adjusts the blade height and speed control strategies to address differences in lawn density in different areas; in tree trimming tasks, the system continuously improves the way the shears and saw blades are used, thereby reducing energy consumption and wear.

[0094] Upon completion of the task, the system automatically generates a task report, including: usage of tool module 150, task execution time, records of tool parameter and configuration adjustments, analysis of the effectiveness of multi-tool collaborative work, and energy consumption and efficiency comparisons. These reports are automatically uploaded to the remote control platform, providing operators with detailed feedback and optimization suggestions. In this way, the garden robot 100 can seamlessly switch between different tasks and automatically select the most suitable tool module 150 for operation. The intelligent and modular design of the entire system significantly improves operational efficiency, accuracy, and adaptability, providing a more comprehensive technical solution for outdoor maintenance and cleaning.

[0095] The foregoing has shown and described the basic principles, main features, and advantages of this application. Those skilled in the art should understand that the above embodiments do not limit this application in any way, and all technical solutions obtained by equivalent substitution or equivalent transformation fall within the protection scope of this application.

Claims

1. A garden robot, comprising: A mobile platform configured to drive the garden robot to move; The main body is supported by the mobile platform; A power supply component, disposed on the main body, is configured to provide an energy source for the garden robot; Multiple tool modules, each used to execute the target task; Sensor components are configured to collect environmental information about the location of the garden robot; and A control unit, located in the main body, is configured to control the plurality of tool modules to perform their respective target tasks based on the environmental information collected by the sensor components. The feature is that the plurality of tool modules include a mowing module, a blower module, and a pruning module that can be simultaneously installed on the main body.

2. The garden robot according to claim 1, characterized in that, The mobile platform includes a bionic limb structure, and the lawn mowing module is surrounded by the bionic limb structure.

3. The garden robot according to claim 2, characterized in that, The bionic limb structure includes walking wheels, and the garden robot has a wheeled walking mode and a bionic gait mode.

4. The garden robot according to claim 2, characterized in that, The blower module is rotatably mounted to the main body via at least two mounting parts, so that the blowing angle of the blower module is adjustable.

5. The garden robot according to claim 2, characterized in that, The pruning module is installed on one of the four limbs, and is respectively located on the left and right sides of the main body along with the blower module.

6. The garden robot according to claim 2, characterized in that, The garden robot can switch between quadrupedal walking mode and lower limb walking mode.

7. The garden robot according to claim 1, characterized in that, The control unit is further configured to control at least two of the tool modules to work collaboratively based on the environmental information.

8. A garden robot, comprising: A mobile platform, including a bionic limb structure, is configured to drive the garden robot to move; The main body is supported by the mobile platform; A power supply component, disposed on the main body, is configured to provide an energy source for the garden robot; At least one tool module for performing the target task; Sensor components are configured to collect environmental information about the location of the garden robot; and A control unit, disposed in the main body, is configured to control at least one tool module to perform the target task based on the environmental information collected by the sensor components; The feature is that the at least one tool module includes a mowing module, which is installed on the main body and surrounded by the bionic limb structure.

9. The garden robot according to claim 8, characterized in that, The mowing module includes a blade disc, the height of which is adjusted by the height of the main body.

10. The garden robot according to claim 9, characterized in that, The height of the main body is adjusted by the bionic limb structure, each leg of the bionic limb structure including at least one joint, the joint being configured to adjust the posture of the bionic limb structure to change the height of the main body.

11. The garden robot according to claim 8, characterized in that, The at least one tool module further includes a blower module and a pruning module, respectively disposed on both sides of the main body.

Images