Movement control method and system for garden robot, and computer device

Abstract

The present application relates to a movement control method and system for a garden robot, and a computer device. The movement control method comprises: during a process in which a garden robot moves to a target location according to a preset path, determining, on the basis of the states of plants on a movement path, whether there is an unworked region on the movement path; if it is determined that there is an unworked region on the movement path, acquiring the state of the garden robot and / or an attribute of the unworked region; on the basis of the state of the garden robot and / or the attribute of the unworked region, determining a working state of the garden robot when same passes through the unworked region; and on the basis of the working state, controlling the garden robot to pass through the unworked region. Thus, a garden robot can be prevented from crushing tall and lush plants on a movement path or missing working regions, thereby avoiding damage to the plants, and also improving the working efficiency of the garden robot.

Description

A mobile control method, control system and computer equipment for a garden robot Technical Field

[0001] The present application relates to the field of robotics technology, and in particular to a movement control method, control system, and computer equipment for a garden robot. Background Art

[0002] Garden robots are widely used to maintain plants in home gardens. They integrate technologies such as motion control, multi-sensor fusion, and path planning. Following instructions, they can move to a target location and then perform further operations at that location. However, current garden robots only follow a specific path and fail to adapt to the state of the plants along their path. This can lead to damage by running over tall, lush plants, or the robot may need to relocate to another area along its path to re-operate on the plants due to neglected operations, reducing its efficiency. Summary of the Invention

[0003] Based on this, it is necessary to provide a mobile control method, control system and computer equipment for a garden robot to address the above technical problems, which can control the garden robot to perform appropriate operating operations according to the status of plants on the moving path to avoid accidentally crushing plants or missing the operating area.

[0004] In a first aspect, the present application provides a movement control method for a garden robot, the movement control method comprising: in the process of the garden robot moving to a target location along a preset path, judging whether there is an unoperated area on the movement path according to the state of plants on the movement path; if it is judged that the unoperated area exists on the movement path, obtaining the state of the garden robot and / or the attributes of the unoperated area; determining the working state of the garden robot when passing through the unoperated area according to the state of the garden robot and / or the attributes of the unoperated area; and controlling the garden robot to pass through the unoperated area according to the working state.

[0005] In the second aspect, the present application also provides a mobile control system for a garden robot, and the mobile control system includes: a judgment module, which is used to judge whether there is an unoperated area on the moving path according to the status of plants on the moving path during the process of the garden robot moving to the target location along a preset path; an acquisition module, which is used to obtain the status of the garden robot and / or the attributes of the unoperated area when the judgment module judges that there is an unoperated area on the moving path; a determination module, which is used to determine the operating status of the garden robot when passing through the unoperated area according to the status of the garden robot and / or the attributes of the unoperated area; and a control module, which is used to control the garden robot to pass through the unoperated area according to the operating status.

[0006] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores computer-readable instructions, and the processor is configured to implement the steps of the method described above when executing the computer-readable instructions.

[0007] The above describes a method, control system, and computer device for controlling the movement of a garden robot. The method includes: when the garden robot moves to a target location along a preset path, determining whether there is an unoperated area on the movement path based on the status of the plants on the movement path; if it is determined that the movement path has an unoperated area, obtaining the status of the garden robot and / or the attributes of the unoperated area; determining the operating status of the garden robot when it passes through the unoperated area based on the status of the garden robot and / or the attributes of the unoperated area; and controlling the garden robot to pass through the unoperated area based on the operating status. In this way, the garden robot can be controlled to perform appropriate operating operations based on the status of the garden robot and / or the attributes of the unoperated area and the status of the plants on the movement path, thereby preventing the garden robot from crushing tall and lush plants on the movement path or missing the operating area, thereby avoiding damage to the plants and improving the operating efficiency of the garden robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] FIG1 is a schematic flow chart of a method for controlling movement of a garden robot according to an embodiment of the present application;

[0009] FIG2 is a flow chart of another method for controlling movement of a garden robot according to an embodiment of the present application;

[0010] FIG3 is a schematic structural diagram of an optical assembly of a garden robot according to an embodiment of the present application;

[0011] FIG4 is a schematic diagram showing the principle of a multispectral sensor for measuring plant chlorophyll content;

[0012] FIG5 is a schematic flow chart of another method for controlling movement of a garden robot provided in an embodiment of the present application;

[0013] FIG6 is a flow chart of another method for controlling movement of a garden robot provided in an embodiment of the present application;

[0014] FIG7 is a schematic diagram of a method for a garden robot to follow the edge;

[0015] FIG8 is a schematic diagram of a scene when there is an unmowed area in the lawn mowing robot;

[0016] FIG9 is a schematic diagram of a scenario in which the mowing robot needs to mow along the edge of an unmowed area;

[0017] FIG10 is a flow chart of another method for controlling movement of a garden robot according to an embodiment of the present application;

[0018] FIG11 is a schematic diagram of a state in which the lawn mowing robot is performing periodic operation;

[0019] FIG12 is a schematic diagram of another state of the lawn mowing robot performing periodic operation;

[0020] FIG13 is a schematic flow chart of another method for controlling movement of a garden robot according to an embodiment of the present application;

[0021] FIG14 is a schematic diagram of a scenario in which a preset path is planned based on the current position of the lawn mowing robot;

[0022] FIG15 is another schematic diagram of a scenario in which a preset path is planned based on the current position of the lawn mowing robot;

[0023] FIG16 is another schematic diagram of a scenario in which a preset path is planned based on the current position of the lawn mowing robot;

[0024] FIG17 is a flow chart of another method for controlling movement of a garden robot according to an embodiment of the present application;

[0025] FIG18 is a flow chart of another method for controlling movement of a garden robot according to an embodiment of the present application;

[0026] FIG19 is a flow chart of another method for controlling movement of a garden robot according to an embodiment of the present application;

[0027] FIG20 is a schematic structural diagram of a mobile control system of a garden robot provided in an embodiment of the present application;

[0028] FIG21 is a basic structural block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0030] A garden robot can move to a target location according to a preset moving path. For example, a lawn mowing robot can move to a charging station according to a preset recharging path in a mowing area, and a lawn mowing robot can move to a charging station according to a preset recharging path in a lawn mowing area. However, current garden robots only move according to the moving path and do not perform appropriate operating operations based on the status of the plants on the moving path. For example, a lawn mowing robot cannot identify whether the lawn on the recharging path has been cut. As a result, it may pass through an uncut area and crush the lawn when moving. The crushed lawn cannot be effectively cut, resulting in poor mowing effect. In addition, the uncut areas on the moving path are ignored, and the robot needs to travel back to an uncut area on the moving path to mow again, which reduces the mowing efficiency of the lawn mowing robot. The embodiments of the present application will introduce a method for controlling the movement of a garden robot to solve the above-mentioned technical problems.

[0031] Please refer to Figure 1, which is a flow chart of a method for controlling the movement of a garden robot provided by an embodiment of the present application. As shown in Figure 1, the method for controlling the movement of this embodiment includes the following steps:

[0032] Step S1: When the garden robot moves to a target location along a preset path, it is determined whether there is an unoperated area on the movement path according to the status of plants on the movement path.

[0033] Step S2: If it is determined that the non-operated area exists in the moving path, the state of the garden robot and / or the attributes of the non-operated area are obtained.

[0034] Step S3: determining the operating state of the gardening robot when passing through the non-operating area according to the state of the gardening robot and / or the attributes of the non-operating area.

[0035] Step S4: controlling the garden robot to pass through the non-operation area according to the operation status.

[0036] Therefore, this embodiment can identify whether there is an unoperated area on the moving path, and when an operating area is identified, control the garden robot to perform appropriate operating operations according to the state of the garden robot and / or the attributes of the unoperated area, thereby preventing the garden robot from crushing tall and lush plants on the moving path or missing the operating area, thereby avoiding damage to the plants and improving the operating efficiency of the garden robot.

[0037] The "unoperated area" includes two types of areas: first, areas that should have been operated on according to the preset operation plan but were missed for some reason; second, areas that have not yet been operated on according to the preset operation plan. For example, for a lawn mower robot, the "unoperated area" is the "uncut area" and includes the following two types of areas: first, areas that should have been cut according to the mowing plan but were missed for some reason; second, areas that have not yet been cut according to the mowing plan.

[0038] In step S1, this embodiment uses the method of determining whether there is an unused area in the movement path by judging the chlorophyll content of the plants. For details, please refer to Figure 2, which is a flow chart of another movement control method for a garden robot provided in an embodiment of the present application. As shown in Figure 2, the following steps are included:

[0039] Step S11: Acquire the chlorophyll content of the plants on the moving path.

[0040] In one embodiment, the chlorophyll content of plants can be obtained using a multispectral sensor. Specifically, the multispectral sensor is positioned obliquely downward at the front and side of the gardening robot. As the gardening robot moves, the multispectral sensor acquires multispectral information of plants at different wavelengths, and the chlorophyll content of the plants along the movement path is determined based on the multispectral information.

[0041] Please refer generally to Figure 3, which is a schematic diagram of the optical assembly of a garden robot according to an embodiment of the present application. As shown in Figure 3, the garden robot includes an optical sensing assembly 1, which is mounted to the side and front of the lawn mower robot. The optical sensing assembly 1 comprises a binocular camera 2 and a multispectral sensor 3. The binocular camera 2 includes a first camera 21 and a second camera 22. The line connecting the first camera 21 and the second camera 22 is called the baseline. The multispectral sensor 3 and the binocular camera 2 have overlapping sensing ranges. The multispectral sensor 3 can be located between the binocular cameras 2, or to the left, right, above, below, in front of, or behind the binocular camera 2. In other words, the multispectral sensor 3 can be located around the binocular camera 2. The first camera 21 and the second camera 22 can be RGB cameras and black and white cameras. The horizontal field of view of the multispectral sensor 3 is θ3, while the horizontal field of view of the binocular camera 2 is θ1 and θ2. θ3 can be equal to θ1 or θ2, or different from θ1 or θ2. Generally speaking, θ3 (20 to 70 degrees) is less than or equal to θ1 or θ2 (80 to 120 degrees). The vertical field of view angle of the multispectral sensor 3 is θ5, and the vertical field of view angle of the binocular camera 2 is θ4. Generally speaking, θ5 (70 to 100 degrees) is less than or equal to θ4 (30 to 60 degrees). The binocular camera 2 covers the robot's body at a distance of 5 to 50 cm in front of the mower robot. The multispectral sensor 3 and binocular camera 2 are both installed vertically with a downward tilt, which facilitates the acquisition of environmental information from the front and below.

[0042] Please also refer to Figure 4, which illustrates the principle behind a multispectral sensor measuring plant chlorophyll content. This principle is based on the absorption spectrum of chlorophyll. When a plant is healthy, it absorbs significant amounts of red and blue light and reflects significant amounts of infrared light. When a plant is subhealthy, it absorbs significant amounts of red and blue light and reflects minimal infrared light. When a plant is dying, it absorbs minimal amounts of red and blue light and reflects minimal infrared light. This characteristic of chlorophyll directly correlates a plant's infrared reflection with its chlorophyll content. Therefore, by analyzing a plant's multispectral data at different wavelengths using a spectral sensor, the plant's chlorophyll content can be accurately determined.

[0043] When a multispectral sensor detects the chlorophyll content of a plant, it usually detects the reflected energy of the blue, green, red and infrared wavelength bands.

[0044] Green corresponds to reflected energy in the 500-600nm spectral band and has maximum reflectivity in this band, with a peak at around 550nm. This spectral band is closely related to the amount of chlorophyll contained in plants. In this visible part of the plant spectrum, the reflectance curve of healthy plants has a maximum reflectivity in the green band (within the 550nm range).

[0045] Red corresponds to the reflected energy in the 600-700nm spectral band, which is largely absorbed by chlorophyll in this band, resulting in low reflectivity. Therefore, healthy leaves have a low red reflectivity.

[0046] Infrared, corresponding to wavelengths between 700 nm and 1.3 μm, has the highest reflectance of the studied wavelengths. This reflectance is strongly correlated with plant chlorophyll content. When plants are stressed and experiencing sub-health, significant changes in reflectance in this spectral band occur.

[0047] In practical applications, the Normalized Difference Red Edge Index (NDRE) can be used to analyze plant health in images obtained from multispectral sensors. Similar to the Normalized Difference Vegetation Index (NDVI), NDRE primarily uses the ratio of infrared to red light. NDRE uses a red edge filter to analyze plant reflectance. The red edge is a region in the transition band from red to near-infrared (NIR) in the plant reflectance spectrum, marking the boundary between chlorophyll absorption in the visible red region and scattering from internal leaf structures in the NIR region.

[0048] Step S12: determining whether there is an unoperated area on the moving path according to the chlorophyll content.

[0049] As shown above, the chlorophyll content can be determined by detecting the reflected energy of the blue, green, red and infrared wavelength bands, especially the ratio of infrared to red.

[0050] When plants are cut or sprayed with pesticides, their chlorophyll content changes. For example, when plants are cut, the cutter inevitably cuts the epidermis of the grass leaves, causing damage to the tissue. The exposed cells lose water and pigment, resulting in a decrease in the plant's chlorophyll content. On the other hand, the damage caused by cutting the plant leads to insufficient nutrition, which can lead to a decrease in chlorophyll content. Similarly, when plants are sprayed with herbicides, the herbicides damage the chlorophyll and the enzymes that produce it, causing damage to the plant. On the one hand, the damaged chlorophyll loses its original color, causing the leaves to turn yellow or white. On the other hand, the damage to the chlorophyll reduces the plant's photosynthesis, which can also affect the chlorophyll content.

[0051] In this step, if the chlorophyll content is less than a preset chlorophyll content threshold, it indicates that the plants on the moving path have low chlorophyll content. In this case, it can be determined that the plants on the moving path have been subjected to corresponding operations, such as cutting or spraying herbicides, and it is determined that there is no unoperated area on the moving path. Conversely, if the detected chlorophyll content is greater than or equal to the preset chlorophyll content threshold, it is determined that there is an unoperated area on the path.

[0052] Since garden robots perform operations on plants, such as cutting lawns or spraying herbicides, the chlorophyll content of plants is greatly affected. Therefore, the embodiment of the present application determines whether there are unoperated areas by detecting changes in the chlorophyll content of plants. There is no need to create other detection conditions for the plants. The solution is convenient, simple and effective.

[0053] After determining the status of the working area on the movement path, step S3 is executed: the working state of the garden robot when passing through the non-working area is determined based on the state of the garden robot and / or the attributes of the non-working area. For details, please refer to Figure 5, which is a flow chart of another method for controlling the movement of a garden robot provided in an embodiment of the present application. As shown in Figure 5, the control method includes the following steps:

[0054] Step S31: If the state of the garden robot is an operation failure state, the power is lower than a preset power threshold, or the attribute of the non-operated area exceeds a preset threshold, it is determined that the garden robot needs to move along the edge of the non-operated area to bypass the non-operated area.

[0055] The garden robot's "non-operational" fault state means the garden robot is unable to complete its corresponding operation. For example, a lawn mower robot's blades may be damaged or the driver that drives the blades may have burned out, making it unable to mow. Another example is a weeding robot's nozzle may be clogged or insufficient, making it unable to spray herbicides.

[0056] There are two ways to determine whether the battery level is lower than the preset threshold:

[0057] First, when the desired movement path is obtained, it can be determined whether the current power level of the garden robot is less than a preset power threshold, that is, the current power level of the garden robot is compared with the preset power threshold.

[0058] Second, the robot compares the remaining power after completing the desired movement path with a preset power threshold. Specifically, a relationship between movement path and power consumption can be preset, and a power threshold can be further preset. When the desired movement path is obtained, the corresponding power consumption is obtained based on the movement path. The actual remaining power after completing the movement path is then calculated based on the current remaining power and power consumption. The relationship between the actual remaining power and the preset power threshold is then used to determine whether the power level is below the preset power threshold.

[0059] It is understandable that the power threshold in the first judgment scheme and the power threshold in the second scheme may be different. For example, the power threshold in the first scheme may be 20%, 30%, etc. of the total power, and the power threshold in the second scheme may be 5%, 10%, etc.

[0060] The attributes of the unoperated area include the area, size, and perimeter of the unoperated area. The attributes of the unoperated area exceeding the preset threshold may include the following situations:

[0061] First, the area of ​​the unoperated region is larger than a preset area threshold, for example, the area of ​​the unmowed region is larger than a preset area threshold.

[0062] Second, the size of the unoperated area is greater than a preset size threshold, for example, the length of one side of the unmowed area is greater than a preset length threshold;

[0063] Third, the perimeter of the unoperated area is greater than a preset perimeter threshold, for example, the perimeter of the unmowed area is greater than the preset perimeter threshold.

[0064] In addition, the attributes of the unoperated area may also include information such as the length of plants in the area, the distribution of plants in the area, the health of plants in the area, and the location of the area. When the attribute information is the length of plants in the unoperated area, if the length of the plants is less than a preset length threshold; when the attribute information is the distribution of plants in the unoperated area, if the distribution of plants is uneven; or when the attribute information is the location of the unoperated area, if the distance between the location of the unoperated area and the target location is greater than a preset distance threshold, the above relationships can determine that the attribute of the unoperated area exceeds the preset threshold.

[0065] That is, if the garden robot detects an unused area, it can be controlled to move along the boundary of the unused area for a circle to obtain the attributes of the unused area. Specifically, please refer to Figures 6 and 7. Figure 6 is a flow chart of another method for controlling the movement of a garden robot provided in an embodiment of the present application, and Figure 7 is a schematic diagram of the method for controlling the movement of the garden robot along the edge. As shown in Figure 6, the control method includes the following steps:

[0066] Step S311: During the process of following the edge, an image representing the state of plants in the forward direction of the garden robot is obtained.

[0067] Specifically, the garden robot is controlled to edge an unused area in a clockwise or counterclockwise direction, for example, an uncut area of ​​a lawn mower robot. During the edge-edge-edge process, image information from the multispectral sensor is acquired in real time. As previously described, a multispectral sensor can be used to detect the chlorophyll content of plants to determine whether they are in an unused area. The image information in this step represents the status of the plant as either worked or unworked, as measured by its chlorophyll content. For example, in a lawn mower robot application, the image information represents information about mowed and unmowed areas. Specifically, areas in the image with a chlorophyll content below a preset chlorophyll threshold are identified as unworked areas, while areas with a chlorophyll threshold greater than or equal to the preset chlorophyll threshold are identified as worked areas.

[0068] Step S312: Determine the boundary between the operated area and the unoperated area based on the image of the plant status.

[0069] The dividing line is used to distinguish between worked and unworked areas. One side of the dividing line represents the worked area, while the other side represents the unworked area. In images representing plant status, worked and unworked areas can be determined based on plant status, such as chlorophyll content. The boundary between the worked and unworked areas serves as the dividing line.

[0070] Step S313: Determine whether the dividing line is at a preset position.

[0071] In this step, whether the dividing line is at the preset position can be determined by determining whether the ratio of the unoperated area to the operated area is equal to 1:1.

[0072] If the result of the judgment is no, jump to step S314; if the result of the judgment is yes, jump to step S315.

[0073] Step S314: controlling the garden robot to adjust its posture so that the dividing line is at a preset position.

[0074] In this step, when the ratio of the unoperated area to the operated area determined in the multispectral image information is less than 1:1, the garden robot is controlled to rotate toward the unoperated area; when the ratio of the unoperated area to the operated area determined in the multispectral image information is greater than 1:1, the garden robot is controlled to rotate toward the operated area. Therefore, during the entire edging process, the garden robot will continuously "shake its head".

[0075] By continuously controlling the "head swing" of the garden robot, the ratio of the unoperated area and the operated area determined in the multispectral image information is always adjusted to 1:1, that is, the garden robot moves along the boundary line between the operated area and the unoperated area, so that the properties of the unoperated area, such as the side length and area size of the unoperated area, can be detected more accurately.

[0076] Step S315: If the dividing line is at the preset position, control the garden robot to continue moving in the current posture.

[0077] In addition, during the process of edge tracking in the unoperated area, it can be further determined whether the length of the edge tracking path exceeds a preset value. If the length of the edge tracking path exceeds the preset value, the garden robot is controlled to edge track the unoperated area in the reverse direction. This prevents the garden robot from running out of power, etc.

[0078] The preset value can be determined based on the current power consumption of the garden robot. For example, if the current power consumption of the garden robot is Q1, and the power required to move from the current position to the target location is Q2, then the power consumption (Q2-Q1) corresponds to the power consumption along the forward and reverse directions. Therefore, the preset value of the garden robot's path length corresponds to the distance traveled by the garden robot using the power consumption (Q2-Q1) / 2. It is understood that the preset value can also be a fixed value, such as 2m, 3m, etc.

[0079] In summary, in step S31, if the state of the garden robot satisfies one of the following: operation failure state, power level is lower than the preset power threshold, or the attribute of the non-operating area exceeds the preset threshold, it indicates that the garden robot is not suitable for operating in the non-operating area, for example, a lawn mower is not suitable for mowing the unmowed area, and thus the garden robot is controlled to move along the edge of the non-operating area to bypass the non-operating area.

[0080] Furthermore, unused areas can be marked in the application software to facilitate subsequent return to work. Users can also edit unused areas based on actual circumstances. For example, they can directly define the circumscribed circle or rectangle of an unused area as a new unused area, ensuring consistent operation path rules. As shown in Figure 8, in a lawn mower robot application, the unused area (i.e., the circumscribed circle of the uncut area) is defined as the new uncut area.

[0081] After completing the corresponding operation at the target location, for example, if the target location is a charging station, a movement path can be planned after charging is completed, passing through the aforementioned unoperated area. When returning to the unoperated area, the unoperated area can be operated in a spiral path. The direction of the spiral path is consistent with the boundary line of the unoperated area.

[0082] Therefore, this application takes into account whether the state of the garden robot is suitable for operating in the non-operated area. When the state of the garden robot is not suitable for operating in the non-operated area, the garden robot is controlled to move along the edge of the non-operated area to bypass the non-operated area, so as to avoid the garden robot directly crushing the plants in the non-operated area and causing damage to the plants.

[0083] Step S32: If the state of the garden robot is normal working state, the power level is greater than the threshold power level and at least one of the following conditions is met: the attribute of the non-working area meets the preset threshold and the non-working area is within the preset range of the target location, then it is determined that the garden robot needs to perform working operations on the plants in the non-working area.

[0084] The fact that the unoperated area is within the preset range of the target location indicates that the unoperated area is relatively close to the target location. For example, if the target location is a charging station, and the unoperated area is located near the charging station, then the plants in the unoperated area need to be operated, and the garden robot needs to be controlled to operate around the charging station to operate in the unoperated area. For example, in the application of a lawn mower robot, if the unmowed area is the edge of the charging station, the lawn mower robot needs to be controlled to mow around the charging station to make up for the unmowed area.

[0085] If the state of the garden robot and the attributes of the non-operated area meet the corresponding conditions, the garden robot will be controlled to operate on the plants in the non-operated area while moving to the target location, eliminating the need for the garden robot to plan an additional operation path before operating, thereby improving the operation efficiency of the garden robot.

[0086] The above describes how a garden robot determines whether there are unused areas along a preset path to a target location, and describes the specific operating states of the garden robot when such areas exist. Before controlling the garden robot to move along a preset path to a target location, it is necessary to plan that path. The following describes how the garden robot plans this path.

[0087] Please refer to FIG10 , which is a flow chart of another method for controlling movement of a garden robot according to an embodiment of the present application. As shown in FIG10 , before the garden robot moves to a target location along a preset path, the method further includes the following steps:

[0088] Step S61: Acquire a first position of a target location and a current second position of the garden robot.

[0089] The target location can be the location indicated by the garden robot after receiving a user command or based on its current status. For example, if a lawnmower robot is currently low on battery and determines that it needs to be recharged, the target location is the charging station, and the lawnmower robot will automatically return to the charging station for recharging. Alternatively, if the lawnmower robot detects damage to a mowing component, such as a blade, it can send a signal to the user, who can instruct the robot to return to the charging station or a repair location. The charging station or repair location is the target location. Alternatively, if a user issues a mowing command to the lawnmower robot based on their needs, instructing the robot to move to a specific mowing area, the mowing area is the target location.

[0090] Step S62: determining whether the garden robot has completed periodic operation based on the second position.

[0091] Garden robots typically perform their operations in a cyclical pattern. For example, a lawnmower robot can mow in a bow-shaped pattern or a U-shaped pattern. Similarly, a weeding robot can spray herbicides in a bow-shaped pattern or a U-shaped pattern.

[0092] In this step, it is determined whether the garden robot has completed the current cycle of operation. For example, the lawn mower determines whether it has completed the current bow-shaped operation. More specifically, it can be determined whether the lawn mower robot is at the end or beginning of the bow-shaped operation path.

[0093] Step S63: If it is determined that the garden robot has completed the periodic operation, a preset path is planned to move from the second position to the first position.

[0094] If the garden robot is currently at the starting point or end point of a periodic operation path, a preset path is planned to move from the current position to the first position.

[0095] As an application scenario, please refer to Figure 11, which is a schematic diagram of a state of a lawn mowing robot performing periodic operations. As shown in Figure 11, the lawn is divided into multiple mowing areas, and a mowing path is preset in each mowing area. The mowing path is a bow-shaped mowing path. When the lawn mowing robot is mowing, it determines that the current power is insufficient and needs to return to the charging station for charging. At this time, the location of the charging station is the first position. If the current position of the lawn mowing robot is the end position of the bow-shaped operation path, it is determined that the lawn mowing robot has completed the mowing operation of the current bow-shaped cycle, and the end position of the row is the second position. A preset path is planned from the end position of the row to the charging station. Similarly, if the current position of the lawn mowing robot is the beginning position of the bow-shaped operation path, it is also determined that the lawn mowing robot has completed the mowing operation of the current bow-shaped cycle, and the beginning position of the row is the second position, and a preset path is planned from the beginning position of the row to the charging station.

[0096] That is to say, if the garden robot has completed the operation of the current cycle and is at the starting point or end point of the operation path, it can directly drive from the current position to the target position, forming the shortest moving path between the two points, and there is no need to move to other positions in the middle. On the one hand, it shortens the moving distance of the garden robot, and on the other hand, it avoids the garden robot from trampling and damaging plants in too many areas when moving.

[0097] Step S64: If it is determined that the garden robot has not completed the periodic operation, the initial position and the end position in the operation path of the garden robot in the current cycle are determined based on the second position, and a preset path is planned based on the first position, the second position, the initial position or the end position.

[0098] If the garden robot is not at the starting point or end point of a periodic operation path, it first determines the initial position and end position of the current operation path, and then plans a preset path based on the obtained positions.

[0099] As an application scenario, please refer to Figure 12, which illustrates another state of a robotic lawnmower during periodic operation. As shown in Figure 12, during a mowing operation, the robotic lawnmower determines that its battery is low and needs to return to a charging station for recharging. The charging station is located at the first position. The robotic lawnmower is currently in the middle of a row of a bow-shaped path. The robot first determines the end and beginning of the row based on its current middle position. It then plans a predefined path based on the location of the charging station, its current middle position, and either the end or beginning of the row.

[0100] That is, if the garden robot has not completed the current cycle of operation and is located in the middle position between the starting point and end point of the current cycle of operation path, it is necessary to preset a shorter movement path based on the current middle position, the starting position of the current cycle of operation, the end position, and the first position. Because the first position, the starting position, and the end position of each cycle of operation are pre-set, when the garden robot is in the middle position between the starting point and end point of the current cycle of operation path, by pre-setting the movement path with reference to the starting position, end position, and the first position of the current cycle of operation, the garden robot can pass through the determined starting position or end point when moving along the movement path, thereby facilitating the positioning of the garden robot.

[0101] Presetting a shorter moving path based on the current intermediate position, the starting position, the end position, and the first position of the current cycle operation may include the following solutions:

[0102] The first solution is shown in FIG13 , which is a flow chart of another method for controlling the movement of a garden robot provided by an embodiment of the present application. As shown in FIG13 , the method further includes the following steps:

[0103] Step S71: determining a first distance from the second position to the end position, and determining a second distance from the second position to the initial position, and comparing the first distance and the second distance.

[0104] Step S72: If the first distance is smaller than the second distance, the planned moving path is: starting from the second position, passing through the end position, and ending at the first position.

[0105] If the first distance is smaller than the second distance, it indicates that the distance from the garden robot to the end position is shorter. Based on the shortest path principle, a preset path from the current position, through the end position, and then to the first position can be planned.

[0106] As an application scenario, refer to Figure 14. The current position of the mowing robot is between the beginning and end of the current row of the bow-shaped operation path. The beginning of the row is the initial position, and the end of the row is the final position. The distance from the current position of the mowing robot to the end of the row is determined to be L1, and the distance from the current position of the mowing robot to the beginning of the row is determined to be L2. If L1 is less than L2, a preset path is planned from the current position, through the end of the row, and then to the charging station. This ensures that the mowing robot returns to the charging station from the end of the row, thereby reducing the planned preset path from passing through the uncut portion of the current mowing area, reducing trampling on the uncut portion of the current mowing area, and improving recharging efficiency.

[0107] Step S73: If the first distance is greater than the second distance, the planned moving path is: starting from the second position, passing through the initial position, and ending at the first position.

[0108] If the first distance is greater than the second distance, it means that the distance from the garden robot to the initial position is shorter. Based on the shortest path principle, a preset path can be planned from the current position, through the initial position, and then to the first position.

[0109] As an application scenario, refer to Figure 15. The current position of the mowing robot is between the beginning and end of the current row of a bow-shaped operation path. The beginning of the row is the initial position, and the end of the row is the final position. The distance from the current position of the mowing robot to the end of the row is determined to be L3, and the distance from the current position of the mowing robot to the beginning of the row is L4. If L3 is greater than L4, a preset path is planned from the current position, through the beginning of the row, and then to the charging station. This ensures that the mowing robot returns to the charging station from the beginning of the row, thereby reducing the planned preset path from passing through the uncut portion of the current mowing area, reducing trampling on the uncut portion of the current mowing area, and improving recharging efficiency.

[0110] Step S74: If the first distance is equal to the second distance, the planned moving path is: starting from the second position, passing through the initial position or the end position, and ending at the first position.

[0111] If the first distance is equal to the second distance, it indicates that the distance from the garden robot to the initial position and the distance to the final position are equal. A preset path can be planned from the current position, through the initial position or the final position, and then to the first position. For example, in Figure 16, the current position of the lawn mower robot is between the beginning and end positions of the current row of the bow-shaped operation path, with the beginning of the row being the initial position and the end of the row being the final position. Therefore, a preset path 1 can be planned from the current position to the beginning of the row and then to the charging station. Alternatively, the lawn mower robot can plan a preset path 2 from the current position to the end of the row and then to the charging station.

[0112] It should be understood that the above steps S72 to S74 are optional steps. In practical applications, there is no restriction on the order in which these steps are executed.

[0113] The second solution is shown in FIG17 , which is a flow chart of another method for controlling the movement of a garden robot provided by an embodiment of the present application. As shown in FIG17 , the method further includes the following steps:

[0114] Step S81: Determine a third distance between the second position and the end position, and compare the third distance with a first distance threshold.

[0115] That is, the distance between the current position and the end position is determined. For example, the mowing robot determines a third distance between the current position and the end position of the row, and then compares the third distance with the first distance threshold.

[0116] Step S82: If the third distance is greater than the first distance threshold, the planned moving path is: starting from the second position, passing through the initial position, and ending at the first position.

[0117] That is, when the distance from the current position to the end position is far, the planned preset path does not pass through the end position. For example, the lawn mowing robot plans a preset path from the current position to the starting position and then to the charging station.

[0118] Step S83: If the third distance is less than the first distance threshold, the planned moving path is: starting from the second position, passing through the end position, and ending at the first position.

[0119] That is, when the distance from the current position to the end position is short, the planned preset path passes through the end position. For example, the mowing robot plans a preset path from the current position to the end position of the row and then to the charging station.

[0120] Step S84: If the third distance is equal to the first distance threshold, the planned moving path is: starting from the second position, passing through the initial position or the end position, and ending at the first position.

[0121] That is, the distance from the current position to the end position is appropriate. For example, if the current position is halfway between the end position and the initial position, the planned preset path can pass through the end position or the initial position. For example, the lawn mowing robot plans a preset path from the current position to the end position or the beginning position of the row and then to the charging station.

[0122] It should be understood that the above steps S82 to S84 are optional steps. In practical applications, there is no restriction on the order in which these steps are executed.

[0123] In the second scheme, the moving path is planned by using the third distance between the second position and the end position and comparing the third distance with the first distance threshold. The moving path can pass through the pre-set positions of the initial position or the end position, helping the garden robot to achieve accurate positioning, and reducing the planned preset path passing through the uncut part of the current mowing robot, reducing the trampling on the uncut part of the current mowing area, and improving the movement efficiency of the garden robot.

[0124] The third solution is shown in FIG18 , which is a flow chart of another method for controlling the movement of a garden robot provided by an embodiment of the present application. As shown in FIG18 , the method further includes the following steps:

[0125] Step S91: Determine a fourth distance between the second position and the initial position, and compare the fourth distance with a second distance threshold. Specifically, the distance between the current position and the initial position is determined. For example, a lawn mower robot determines a fourth distance between the current position and the initial position, and then compares the fourth distance with the second distance threshold.

[0126] Step S92: If the fourth distance is greater than the second distance threshold, the planned moving path is: starting from the second position, passing through the end position, and ending at the first position.

[0127] That is, when the distance from the current position to the initial position is far, the planned preset path does not pass through the initial position. For example, the lawn mowing robot plans a preset path from the current position to the end of the row and then to the charging station.

[0128] Step S93: If the fourth distance is less than the second distance threshold, the planned moving path is: starting from the second position, passing through the initial position, and ending at the first position.

[0129] That is, when the distance from the current position to the initial position is short, the planned preset path passes through the initial position. For example, the mowing robot plans a preset path from the current position to the initial position and then to the charging station.

[0130] Step S94: If the fourth distance is equal to the second distance threshold, the planned movement path is: starting from the second position, passing through the initial position or the end position, and ending at the first position. That is, if the distance between the current position and the end position is appropriate, for example, the current position is halfway between the end position and the initial position, then the planned preset path may pass through the end position or the initial position. For example, the lawn mower robot may plan a preset path from the current position to the end position or the beginning position of a row, and then to the charging station.

[0131] In the third scheme, the moving path is planned by using the fourth distance between the second position and the initial position and comparing the fourth distance with the second distance threshold. The moving path can pass through the pre-set positions of the initial position or the end position, helping the garden robot to achieve accurate positioning, and reducing the planned preset path passing through the uncut part of the current mowing robot, reducing the trampling on the uncut part of the current mowing area, and improving the movement efficiency of the garden robot.

[0132] The fourth solution, please refer to FIG19, which is a flow chart of another method for controlling the movement of a garden robot provided by an embodiment of the present application. As shown in FIG10, the method further includes the following steps:

[0133] Step S110: Determine a fifth distance of a path that sequentially passes through the second position, the end position, and the first position. Specifically, the fifth distance of a path that passes through the current position, the end position, and the target location of the garden robot is determined. For example, the fifth distance of a path passing through the current position of the lawn mower robot, the end position of a row, and the charging station is determined.

[0134] Step S111: Determine the sixth distance of the path that passes through the second position, the initial position, and the first position in sequence. That is, the sixth distance of the path that passes through the current position, the initial position, and the target location of the garden robot is determined. For example, the sixth distance of the path of the current position, the initial position, and the charging station of the lawn mower robot is

[0135] Step S112: Compare the fifth distance and the sixth distance.

[0136] Step S113: If the fifth distance is less than the sixth distance, the planned moving path is: starting from the second position, passing through the end position, and ending at the first position.

[0137] Step S114: If the fifth distance is greater than the sixth distance, the planned moving path is: starting from the second position, passing through the initial position, and ending at the first position.

[0138] Step S115: If the fifth distance is equal to the sixth distance, the planned moving path is: starting from the second position, passing through the initial position or the end position, and ending at the first position.

[0139] In the fourth solution, a preset path with the shortest path is planned based on the first position, the current position, the initial position or the end position to improve the movement efficiency of the garden robot.

[0140] The above describes a method for controlling the movement of a garden robot. This application also provides a mobile control system for a garden robot, which is applicable to the mobile control method described above. Please refer to Figure 20, which is a schematic diagram of the structure of a mobile control system for a garden robot provided in an embodiment of this application. As shown in Figure 20, the mobile control system 200 includes:

[0141] The determination module 201 is configured to determine whether there is an unused area along the path based on the status of plants along the path as the gardening robot moves along the preset path to the target location. Prior to controlling the gardening robot to move along the preset path to the target location, the preset path must be planned. The specific planning scheme is as described above and will not be further elaborated here.

[0142] Furthermore, the specific solution for determining whether there is an unoperated area on the moving path according to the status of the plants on the moving path is as described above and will not be repeated here.

[0143] The acquisition module 202 is configured to acquire the state of the garden robot and / or the attributes of the non-operated area when the determination module determines that the non-operated area exists in the movement path. The method for acquiring the state of the garden robot and / or the attributes of the non-operated area is as described above and will not be repeated here.

[0144] The determination module 203 is used to determine the operating state of the garden robot when it passes through the non-operating area according to the state of the garden robot and / or the attributes of the non-operating area. The specific solution is as described above and will not be repeated here.

[0145] The control module 204 is used to control the garden robot to pass through the non-operation area according to the operation status. The specific solution is as described above and will not be repeated here.

[0146] To solve the above technical problems, the present application also provides a computer device. Specifically, please refer to FIG21 , which is a basic structural block diagram of the computer device of this embodiment.

[0147] The computer device 6 includes a memory 61, a processor 62, and a network interface 63 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 6 with components 61-63, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0148] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0149] The memory 61 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 61 can be an internal storage unit of the computer device 6, such as the hard disk or memory of the computer device 6. In other embodiments, the memory 61 can also be an external storage device of the computer device 6, such as a plug-in hard disk equipped on the computer device 6, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 61 can also include both the internal storage unit of the computer device 6 and its external storage device. In this embodiment, the memory 61 is generally used to store the operating system installed on the computer device 6 and various information management operating systems, such as computer-readable instructions for the movement control method of the garden robot. In addition, the memory 61 can also be used to temporarily store various types of data that have been output or are to be output.

[0150] In some embodiments, the processor 62 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 62 is generally used to control the overall operation of the computer device 6. In this embodiment, the processor 62 is used to execute computer-readable instructions stored in the memory 61 or process data, such as computer-readable instructions for executing the HUD image calibration method.

[0151] The network interface 63 may include a wireless network interface or a wired network interface. The network interface 63 is generally used to establish a communication connection between the computer device 6 and other electronic devices.

[0152] The present application also provides another embodiment, namely, providing a computer program product, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the above-mentioned garden robot movement control method.

[0153] The present application provides a movement control method, control system, and computer device for a garden robot. The movement control method includes: when the garden robot moves to a target location along a preset path, judging whether there is an unoperated area on the movement path based on the status of the plants on the movement path; if it is judged that the movement path has the unoperated area, obtaining the status of the garden robot and / or the attributes of the unoperated area; determining the operation status of the garden robot when passing through the unoperated area based on the status of the garden robot and / or the attributes of the unoperated area; and controlling the garden robot to pass through the unoperated area based on the operation status. In this way, the garden robot can be controlled to perform appropriate operation operations based on the status of the garden robot and / or the attributes of the unoperated area and the status of the plants on the movement path, thereby preventing the garden robot from crushing tall and lush plants on the movement path or missing the operation area, thereby avoiding damage to the plants and improving the operation efficiency of the garden robot.

[0154] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0155] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0156] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for controlling the movement of a garden robot, wherein, The described mobile control method includes: During the process of the gardening robot moving to a target location according to a preset path, judging whether there is an unoperated area on the moving path according to the state of the plants on the moving path; If it is judged that there is the unoperated area on the moving path, obtaining the state of the gardening robot and / or the attributes of the unoperated area; Determining the operation state of the gardening robot when passing through the unoperated area according to the state of the gardening robot and / or the attributes of the unoperated area; Controlling the gardening robot to pass through the unoperated area according to the operation state.

2. The mobile control method according to claim 1, wherein, The step of judging whether there is an unoperated area on the moving path according to the state of the plants on the moving path further includes: Obtaining the chlorophyll content of the plants on the moving path; Judging whether there is an unoperated area on the moving path according to the chlorophyll content.

3. The mobile control method according to claim 2, wherein, The method for obtaining the chlorophyll content of the plants on the moving path includes: During the movement of the gardening robot, obtaining the multispectral information of the plants at different wavelengths through a multispectral sensor, and determining the chlorophyll content of the plants on the moving path according to the multispectral information.

4. The mobile control method according to claim 3, wherein, The multispectral sensor is inclined downward and arranged in front of the side of the gardening robot.

5. The mobile control method according to claim 1, wherein, Before the gardening robot moves to the target location according to the preset path, the method includes: Obtaining the first position of the target location and the current second position of the gardening robot; Judging whether the gardening robot has completed a periodic operation based on the second position; If it is judged that the gardening robot has completed the periodic operation, planning a preset path from the second position to the first position; If it is judged that the gardening robot has not completed the periodic operation, determining the initial position and the end position in the operation path of the current cycle of the gardening robot based on the second position, and planning a preset path based on the first position, the second position, the initial position or the end position.

6. The mobile control method according to claim 5, wherein, The step of planning the preset path based on the first position, the second position, the initial position or the end position further includes: Determining the first distance from the second position to the end position, and determining the second distance from the second position to the initial position, and comparing the magnitudes of the first distance and the second distance; If the first distance is less than the second distance, the planned moving path is: starting from the second position, passing through the end position, and ending at the first position; If the first distance is greater than the second distance, the planned moving path is: starting from the second position, passing through the initial position, and ending at the first position; If the first distance is equal to the second distance, the planned moving path is: starting from the second position, passing through the initial position or the end position, and ending at the first position.

7. The mobile control method according to claim 5, wherein, The step of planning the preset path based on the first position, the second position, the initial position or the end position further includes: Determine a third distance between the second position and the end position, and compare the third distance with a first distance threshold; If the third distance is greater than the first distance threshold, the planned movement path is: starting from the second position, passing through the initial position, and ending at the first position; If the third distance is less than the first distance threshold, the planned movement path is: starting from the second position, passing through the end position, and ending at the first position; If the third distance is equal to the first distance threshold, the planned movement path is: starting from the second position, passing through the initial position or the end position, and ending at the first position.

8. The mobile control method according to claim 5, wherein, The step of planning the preset path based on the first position, the second position, the initial position or the end position further includes: Determine a fourth distance between the second position and the initial position, and compare the fourth distance with a second distance threshold; If the fourth distance is greater than the second distance threshold, the planned movement path is: starting from the second position, passing through the end position, and ending at the first position; If the fourth distance is less than the second distance threshold, the planned movement path is: starting from the second position, passing through the initial position, and ending at the first position; If the fourth distance is equal to the second distance threshold, the planned movement path is: starting from the second position, passing through the initial position or the end position, and ending at the first position.

9. The mobile control method according to claim 5, wherein, The step of planning the preset path based on the first position, the second position, the initial position or the end position further includes: Determine a fifth distance of the path that sequentially passes through the second position, the end position and the first position; Determine a sixth distance of the path that sequentially passes through the second position, the initial position and the first position; And compare the magnitudes of the fifth distance and the sixth distance; If the fifth distance is less than the sixth distance, the planned movement path is: starting from the second position, passing through the end position, and ending at the first position; If the fifth distance is greater than the sixth distance, the planned movement path is: starting from the second position, passing through the initial position, and ending at the first position; If the fifth distance is equal to the sixth distance, the planned movement path is: starting from the second position, passing through the initial position or the end position, and ending at the first position.

10. The mobile control method according to claim 1, wherein, The step of determining the operation state of the gardening robot when passing through the unoperated area according to the state of the gardening robot and / or the attribute of the unoperated area further includes: If the state of the gardening robot is an operation failure state, the battery power is lower than a preset battery power threshold, or the attribute of the unoperated area exceeds a preset threshold, determine that the gardening robot needs to perform an edge following on the unoperated area to bypass the unoperated area; If the state of the garden robot is the normal operation state, the battery power is greater than the threshold battery power threshold, and at least one of the following conditions is met: the attribute of the unoperated area conforms to the preset threshold and the garden robot is within the preset range of the target location, then it is determined that the garden robot needs to perform an operation on the plants in the unoperated area; Wherein, the attribute includes the area, size and perimeter of the unoperated area.

11. The mobile control method according to claim 10, wherein, Before the step of determining the operation state of the garden robot when passing through the unoperated area, it also includes: Performing an edge following on the unoperated area to obtain the attribute of the unoperated area, where: During the edge following process, obtaining an image representing the state of the plants in the forward direction of the garden robot; Determining the boundary line between the operated area and the unoperated area according to the image of the plant state; Judging whether the boundary line is at a preset position; If the boundary line is not at the preset position, controlling the garden robot to adjust its pose so that the boundary line is at the preset position.

12. The mobile control method according to claim 10, wherein, The step of performing an edge following on the unoperated area also includes: During the process of performing an edge following on the unoperated area, judging whether the length of the edge following path exceeds a preset value; If the length of the edge following path exceeds the preset value, controlling the garden robot to perform a reverse edge following on the unoperated area.

13. A mobile control system for a garden robot, wherein, The mobile control system includes: A judgment module, configured to judge whether there is an unoperated area on the movement path according to the state of the plants on the movement path during the process of the garden robot moving to the target location according to the preset path; An acquisition module, configured to acquire the state of the garden robot and / or the attribute of the unoperated area when the judgment module judges that there is an unoperated area on the movement path; A determination module, configured to determine the operation state of the garden robot when passing through the unoperated area according to the state of the garden robot and / or the attribute of the unoperated area; A control module, configured to control the garden robot to pass through the unoperated area according to the operation state.

14. A computer device, wherein, The computer device includes a memory and a processor. The memory stores computer-readable instructions, and the processor is configured to implement the steps of the method as claimed in claim 1 when executing the computer-readable instructions.

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