Light emission control method, robot and computer readable storage medium

Abstract

The invention relates to a light emitting control method, a robot and a computer readable storage medium, and relates to the field of computer vision. The method comprises the steps that an environment image corresponding to the environment where the robot is located is collected, and a target area is determined in the environment image; determining brightness information of the target area, and determining area brightness and brightness gradient of the target area according to the brightness information of the target area; determining a light-emitting brightness threshold according to the brightness gradient of the target area; if the area brightness of the target area is smaller than the light emitting brightness threshold value, the robot is controlled to execute light emitting operation. The brightness of the environment where the robot is located can be accurately recognized, so that the robot is accurately controlled to emit light, and normal work of the robot is guaranteed.

Description

Technical Field

[0001] This application relates to the field of computer vision, and more particularly to a light emission control method, a robot, and a computer-readable storage medium. Background Technology

[0002] To improve robot efficiency, robots are often used in dark environments such as nighttime and caves. To facilitate operation in low light, supplemental lighting is typically used to illuminate the work area. However, robots using this technology often require manual control to turn the supplemental lighting on and off. This can lead to issues like forgetting to turn it on causing malfunctions or wasting battery power. Alternatively, the robot may simply compare the current ambient light level to a preset brightness threshold, resulting in repeated switching on and off, indicating a low level of robot intelligence. Summary of the Invention

[0003] The main objective of this application is to provide a light emission control method, a robot, and a computer-readable storage medium that can accurately identify the brightness of the robot's environment, thereby accurately controlling the robot to emit light and ensuring the robot's normal operation.

[0004] In a first aspect, this application provides a light emission control method applied to a robot, the method comprising: Collect environmental images corresponding to the environment in which the robot is located, and determine the target area in the environmental images; Determine the brightness information of the target area, and determine the regional brightness and brightness gradient of the target area based on the brightness information of the target area; The luminance threshold is determined based on the luminance gradient of the target region; If the brightness of the target area is less than the luminous brightness threshold, then the robot is controlled to perform a luminous operation.

[0005] Secondly, this application also provides a robot, the robot comprising: ontology; A driving module is used to drive the main body to move; A cutting mechanism is disposed on the body and is used to cut the object to be cut; A light-emitting module is disposed on the body and is used to emit light; A controller, connected to the driving module, the cutting mechanism, and the light-emitting module, is used to execute the light-emitting control method as described above.

[0006] Thirdly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the light emission control method described above.

[0007] This application provides a light emission control method, a robot, and a computer-readable storage medium. The method involves acquiring an environmental image corresponding to the robot's environment and identifying a target region within that image; determining the brightness information of the target region and, based on this information, determining the region's brightness and brightness gradient; determining a light emission threshold based on the target region's brightness gradient; and controlling the robot to perform a light emission operation if the target region's brightness is less than the threshold. This allows for dynamic adjustment of the light emission threshold based on the target region's brightness gradient, and accurate control of the robot's light emission operation by comparing the target region's brightness with the adjusted threshold. This enables timely and accurate light emission based on the actual working environment, without human intervention or control, effectively improving the robot's adaptability and light emission intelligence in dynamic environments. Attached Figure Description

[0008] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 A schematic flowchart illustrating the steps of a light emission control method provided in an embodiment of this application; Figure 2 A schematic diagram of a vehicle front area, a target area, and a background area provided for an embodiment of this application; Figure 3 A flowchart illustrating a step for determining a luminance threshold based on the luminance gradient of a target region, provided for an embodiment of this application; Figure 4 A schematic flowchart illustrating another step for determining the luminance threshold based on the luminance gradient of the target region, provided for an embodiment of this application; Figure 5 A flowchart illustrating a step for determining the working environment based on the brightness gradient of the target area and the brightness information of the background area, provided for an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a robot provided in one embodiment of this application; Figure 7 This is a schematic block diagram of the structure of a robot provided in one embodiment of this application. Detailed Implementation

[0010] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0011] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0012] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0013] In related technologies, robots often require manual control to turn supplementary lighting on and off. This can easily lead to situations where the supplementary lighting is forgotten to be turned on, causing robot malfunctions, or forgotten to be turned off, resulting in wasted electricity. This indicates a low level of robot intelligence. Alternatively, the robot may decide whether to turn on the supplementary lighting based on the current time of day. However, day or night is not the sole determining factor for the brightness of the robot's working environment; there may be instances where the lighting is on when it is not needed, or vice versa.

[0014] To address the aforementioned issues, this application proposes a light emission control method, a robot, and a computer-readable storage medium, which can perform light emission operations in a timely and accurate manner according to the actual working environment without human intervention or control, effectively improving the robot's adaptability and light emission intelligence in dynamic environments.

[0015] Please refer to Figure 1 , Figure 1 This is a schematic flowchart illustrating a light emission control method provided in an embodiment of this application. This light emission control method can be applied to robots, terminals, or servers.

[0016] Among them, robots can be lawnmowers or other robots with cutting mechanisms; terminals can be smartphones, tablets, laptops, desktop computers, smart speakers, smartwatches, etc., but are not limited to these; servers can be independent servers, server clusters, or cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0017] In this application embodiment, the robot may be a robot including a light-emitting module such as a fill light, and the light-emitting control method provided in this application is used to control the opening and closing of the light-emitting module.

[0018] like Figure 1 As shown, the light emission control method includes steps S101 to S104.

[0019] S101. Collect environmental images corresponding to the robot's environment and determine the target area in the environmental images.

[0020] Specifically, the robot can be equipped with a camera device to capture environmental images of its surroundings. The camera device is positioned at the front of the robot, allowing it to capture images of the environment in front of the robot's direction of movement. For example, if the robot is moving due north, the camera device will begin capturing images of the environment in that direction. Since this image is positioned on the robot's body, it will generally also include the front of the robot.

[0021] For example, the shooting device may include a camera, video camera, mobile phone, or other device capable of capturing environmental images.

[0022] For example, during the robot's operation or movement, a camera device can continuously capture environmental images corresponding to the direction in which the robot is moving. For instance, in the case of a lawnmower, the lawnmower can continuously capture environmental images corresponding to the direction in which it is moving while mowing the lawn.

[0023] In some embodiments, the vanishing point and vehicle end boundary in the environmental image are determined; and the target region is divided in the environmental image based on the vanishing point and vehicle end boundary.

[0024] The vanishing point is the point where the projections of parallel lines meet on the image plane. For example, two lines that are actually parallel in reality (such as railway tracks, the sides of a road, or the sides of a tall building) will no longer appear parallel in a camera photograph; instead, they will gradually intersect at the vanishing point as they extend into the distance. Since the environment image also includes the front of the vehicle, the vehicle's edge boundary is the front boundary. Figure 2 As shown, the target area is the region between the boundary line corresponding to the vanishing point and the vehicle end boundary. Since the target area is located in front of the robot's front, it can also be called the front area of ​​the vehicle.

[0025] Specifically, the intrinsic and extrinsic parameters of the imaging device can be obtained, and the vanishing point in the environmental image can be determined based on the intrinsic and extrinsic parameters of the imaging device.

[0026] For example, by using the camera's internal structural parameters (intrinsic parameters) and the camera's position and orientation parameters in the three-dimensional world (extrinsic parameters), and using coordinate system transformation formulas, the pixel coordinates of the point where "parallel lines" converge and intersect (i.e., the vanishing point) in the environmental image can be calculated.

[0027] Specifically, the robot's vehicle model can be obtained, and the vehicle's edge boundary in the environmental image can be determined based on the vehicle model; image feature extraction and analysis can also be performed on the environmental image to identify the vehicle's edge boundary in the environmental image.

[0028] For example, in the case of a lawnmower robot, since lawnmowers generally have fixed models, the vehicle end boundary in the environmental image can be quickly located by obtaining the model of the lawnmower and based on the model. The front of the lawnmower can be quickly determined in the environmental image to obtain the vehicle end boundary without the need for cumbersome image processing by the processor.

[0029] Specifically, the upper edge of the target region can be determined based on the vanishing point in the environmental image, and the lower edge of the target region can be determined based on the vehicle end boundary, thereby dividing the environmental image into a target region, a background region, and a vehicle front region. The target region is the area between the boundary line corresponding to the vanishing point and the vehicle end boundary; the background region is the area between the boundary line corresponding to the vanishing point and the upper boundary of the environmental image; and the vehicle front region is the area from the vehicle end boundary to the lower boundary of the environmental image.

[0030] S102. Determine the brightness information of the target area, and determine the regional brightness and brightness gradient of the target area based on the brightness information of the target area.

[0031] The target region can include multiple sampling points. The brightness information of the target region includes the brightness values ​​of each sampling point in the target region, and the regional brightness of the target region is the average brightness value of the target region. The brightness gradient can be used to analyze the brightness variation characteristics of the environmental image, thus reflecting the brightness changes in the environmental image.

[0032] In some embodiments, the environmental image is converted into a color space image; the brightness of the target area in the color space image is extracted to obtain the brightness information of the target area.

[0033] In this context, a color space (HSV) image refers to an image represented using the HSV color space. HSV is composed of three parameters: hue, saturation, and value, used to more intuitively describe color attributes. In this application example, using an HSV image is beneficial for acquiring brightness information of the target area.

[0034] For example, the brightness of each sampling point in the target area of ​​the color space image is extracted to obtain the brightness value of each sampling point in the target area.

[0035] In some embodiments, the average value of the brightness values ​​of each sampling point in the target area is determined, and the average value is used as the regional brightness of the target area; the gradient amplitude and gradient direction are determined based on the brightness values ​​of each sampling point in the target area, and the brightness gradient of the target area is determined based on the gradient amplitude and gradient direction. The brightness gradient can be used to characterize whether there are significant local brightness and darkness changes in the illumination within the target area.

[0036] For example, since the brightness information of the target area includes the brightness values ​​of each sampling point in the target area, the average value of the brightness values ​​of all sampling points in the target area can be calculated and used as the regional brightness of the target area.

[0037] For example, the intensity of brightness change at each sampling point is determined based on the brightness value of each sampling point in the target area, and this intensity of brightness change is used as the gradient magnitude. Alternatively, the direction of the fastest brightness change in the target area can be used as the gradient direction. Finally, the brightness gradient of the target area is determined by combining the gradient magnitude and the gradient direction.

[0038] S103. Determine the luminous intensity threshold based on the luminous gradient of the target area.

[0039] The luminance threshold is used to determine whether the robot should perform a light-emitting operation. This luminance threshold can be dynamically adjusted based on the luminance gradient of the target area. In some embodiments, if the luminance gradient of the target area is greater than a preset gradient threshold, it usually indicates that the robot is currently in a region where sunlight and local shadows meet. In such scenarios, the overall brightness is not significantly reduced, but there is a sudden darkening in a local area. To prevent the robot from mistakenly judging this local shadow as insufficient overall lighting and frequently triggering the light-emitting operation, the preset luminance threshold can be appropriately lowered to obtain the desired luminance threshold, so that the robot only triggers the light-emitting operation in darker environments.

[0040] If the brightness gradient of the target area is not greater than the preset gradient threshold, it indicates that there is no obvious local shadow in the current environment, and the overall brightness change can represent the actual lighting conditions. In order to enable the robot to respond to the overall lighting and reduce environmental changes in a timely manner, the preset luminous brightness threshold is increased to obtain the luminous brightness threshold, so that the robot can more easily trigger luminous emission when the brightness decreases.

[0041] The preset gradient threshold can be any gradient threshold, which can be set according to actual conditions and is not specifically limited here. The preset luminance threshold can be any luminance value, generally representing a luminance threshold suitable for daily conditions, which can be set according to actual conditions and is not specifically limited here.

[0042] like Figure 3 As shown, for example, step S103 may include steps S1031 to S1033.

[0043] S1031. Determine whether the brightness gradient of the target area is greater than the preset gradient threshold.

[0044] S1032. If the brightness gradient of the target area is greater than the preset gradient threshold, then reduce the preset luminous brightness threshold to obtain the luminous brightness threshold.

[0045] S1033. If the brightness gradient of the target area is not greater than the preset gradient threshold, then increase the preset luminous brightness threshold to obtain the luminous brightness threshold.

[0046] If a robot is in a partially dark environment, its image typically exhibits significant brightness variations due to the presence of both bright and dark areas. Therefore, the brightness gradient is often large, although the overall ambient brightness does not decrease significantly. However, localized areas may experience a sudden decrease in brightness due to occlusion or shadows. Maintaining the original luminous brightness threshold would lead to repeated brightness fluctuations in the target area, causing it to alternate between high and low brightness values. This would result in the robot repeatedly performing light-up and light-down operations, affecting the operation and lifespan of the luminous module. To avoid this situation, this application can preliminarily determine the robot's working environment based on the brightness gradient of the target area, thereby dynamically adjusting the preset luminous brightness threshold to obtain an accurate luminous brightness threshold.

[0047] For example, if the brightness gradient of the target area is greater than the preset gradient threshold, it indicates that the brightness change intensity of the target area is large, which means that the robot's working environment is likely to be a locally dark environment. Therefore, the preset luminous brightness threshold can be reduced to obtain the luminous brightness threshold, making it more difficult for the robot to trigger the luminous operation. That is, the brightness of the target area needs to be smaller in order to trigger the luminous operation.

[0048] For example, taking a lawnmower as an example, if the lawnmower moves to the shade of a tree, since the shaded environment is a locally dark environment, the brightness gradient of the target area corresponding to the environmental image collected by the lawnmower is generally large. Therefore, the preset luminous brightness threshold can be reduced to obtain the luminous brightness threshold, making it more difficult for the lawnmower to trigger the luminous operation, thus avoiding the lawnmower from repeatedly performing the luminous operation and the light-off operation when it moves to different shades of trees.

[0049] For example, if the brightness gradient of the target area is not greater than the preset gradient threshold, it indicates that the brightness change intensity of the target area is small, that is, some areas of the target area are brighter and some areas are darker. At this time, the robot's working environment is less likely to be a locally dark environment. It is generally a completely dark environment or a completely bright environment. Therefore, the preset luminous brightness threshold can be increased to obtain the luminous brightness threshold, so that the robot can more easily trigger the luminous operation, and the robot can turn on the light and perform the corresponding work faster.

[0050] For example, taking a lawnmower as an example, if the lawnmower is working in a nighttime environment, since the nighttime environment is completely dark, the brightness gradient of the target area corresponding to the environmental image collected by the lawnmower is generally small. Therefore, the preset luminous brightness threshold can be increased to obtain the luminous brightness threshold, which makes it easier for the lawnmower to trigger the luminous operation, so that the lawnmower can more quickly identify the nighttime environment to respond to the light turning on, and thus carry out the corresponding lawnmowing operation.

[0051] In some embodiments, brightness information of the background area is acquired, and the working environment of the robot is determined based on the brightness gradient of the target area and the brightness information of the background area; the preset luminous brightness threshold is adjusted according to the working environment of the robot to obtain the luminous brightness threshold.

[0052] The brightness information of the background area can include the regional brightness of the background area. The robot's working environment can include partially dark environments, completely dark environments, etc.

[0053] like Figure 4 As shown, exemplarily, step S103 may also include steps S1034 to S1035.

[0054] S1034. Obtain the brightness information of the background area, and determine the working environment of the robot based on the brightness gradient of the target area and the brightness information of the background area.

[0055] S1035. Adjust the preset luminous brightness threshold according to the robot's working environment to obtain the luminous brightness threshold.

[0056] For example, the brightness of each sampling point in the background region of the color space image can be extracted to obtain the brightness value of each sampling point in the background region. Then, the average value of the brightness values ​​of all sampling points in the background region can be calculated, and this average value can be used as the regional brightness of the background region.

[0057] In this embodiment, by combining the brightness information of the background area and the brightness gradient of the target area, the working environment of the robot can be identified more accurately, thereby enabling more precise adjustment of the preset luminous brightness threshold to obtain the luminous brightness threshold.

[0058] For example, the robot's working environment can be determined based on the brightness gradient of the target area and the brightness information of the background area. If the robot's working environment is determined to be a partially dark environment, the preset luminous brightness threshold can be lowered to obtain the luminous brightness threshold, making it more difficult for the robot to trigger the luminous operation. That is, the brightness of the target area needs to be lower in order to trigger the luminous operation. If the robot's working environment is determined to be a completely dark environment or a completely bright environment, the preset luminous brightness threshold can be increased to obtain the luminous brightness threshold, making it easier for the robot to trigger the luminous operation, so that the robot can turn on the light and perform the corresponding work more quickly.

[0059] In some embodiments, if the brightness gradient of the target area is greater than a preset gradient threshold and the brightness information of the background area is greater than a preset brightness threshold, then the robot's working environment is determined to be a partially dark environment; if the brightness gradient of the target area is not greater than a preset gradient threshold and the brightness information of the background area is not greater than a preset brightness threshold, then the robot's working environment is determined to be a completely dark environment.

[0060] like Figure 5 As shown, by way of example, step S1034 may also include steps S10341 to S10344.

[0061] S10341. Determine whether the brightness gradient of the target area is greater than the preset gradient threshold.

[0062] S10342. Determine whether the brightness information of the background area is greater than the preset brightness threshold.

[0063] S10343. If the brightness gradient of the target area is greater than the preset gradient threshold, and the brightness information of the background area is greater than the preset brightness threshold, then the working environment of the robot is determined to be a locally dark environment.

[0064] S10344 If the brightness gradient of the target area is not greater than the preset gradient threshold, and the brightness information of the background area is not greater than the preset brightness threshold, then the working environment of the robot is determined to be a completely dark environment.

[0065] Since the brightness gradient of the target area is greater than the preset gradient threshold, it indicates that the brightness change intensity of the target area is relatively large, that is, some areas of the target area are brighter and some areas are darker. At the same time, the brightness information of the background area is greater than the preset brightness threshold, indicating that the brightness of the background area is high. Therefore, it can be determined that the working environment of the robot is a locally dark environment.

[0066] Since the brightness gradient of the target area is not greater than the preset gradient threshold, it indicates that the brightness change intensity of the target area is small, that is, the entire target area is bright or the entire target area is dark. At the same time, the brightness information of the background area is not greater than the preset brightness threshold, which indicates that the brightness of the background area is low. Therefore, it can be determined that the working environment of the robot is a completely dark environment.

[0067] If the brightness gradient of the target area is not greater than the preset gradient threshold, and the brightness information of the background area is greater than the preset brightness threshold, it indicates that the brightness of the background area is high and the brightness change intensity of the target area is small. Therefore, it can be determined that the working environment of the robot is a completely bright environment.

[0068] It should be noted that when the brightness gradient of the target area is greater than the preset gradient threshold, and the brightness information of the background area is not greater than the preset brightness threshold, since it is generally difficult to determine whether the robot is in a partially dark environment, a completely dark environment, or a completely bright environment, the luminous brightness threshold can be adjusted only by the brightness gradient of the target area.

[0069] In some embodiments, the image acquisition time of the environmental image is obtained, and the preset luminous brightness threshold is adjusted according to the image acquisition time and the working environment to obtain the luminous brightness threshold.

[0070] For example, the image acquisition time of the environmental image is obtained, and the corresponding time period is determined according to the image acquisition time. The preset luminous brightness threshold is adjusted according to the time period and the working environment to obtain the luminous brightness threshold.

[0071] In this embodiment of the application, the working environment can be more accurately identified as a partially dark environment by combining the image acquisition time. For example, if the image acquisition time is during the daytime period, the working environment should be a completely bright environment. However, if the working environment is identified as a partially dark environment, the preset luminous brightness threshold needs to be reduced to obtain the luminous brightness threshold. As another example, if the image acquisition time is during the daytime period, the working environment should be a completely bright environment. However, if the working environment is identified as a completely dark environment, the preset luminous brightness threshold needs to be increased to obtain the luminous brightness threshold.

[0072] Specifically, the image acquisition time of the environmental image can also be obtained, and the preset luminance threshold can be directly adjusted according to the image acquisition time to obtain the luminance threshold.

[0073] For example, if the image acquisition time is determined to be a first time period (daytime period), the preset luminous brightness threshold can be lowered to obtain the luminous brightness threshold, making the conditions for triggering the robot to perform the luminous operation more stringent. If the image acquisition time is determined to be a second time period (nighttime period), the preset luminous brightness threshold can be increased to obtain the luminous brightness threshold, making the conditions for triggering the robot to perform the luminous operation easier.

[0074] In some embodiments, if the image acquisition time is a first time period and the working environment is a partially dark environment, the preset luminous brightness threshold is reduced to obtain the luminous brightness threshold; if the image acquisition time is a first time period and the working environment is a completely dark environment, the preset luminous brightness threshold is increased to obtain the luminous brightness threshold.

[0075] The first time period can be the daytime period, which can be from 6:00 to 18:00, and the specific time can be determined according to the actual situation.

[0076] For example, if the image acquisition time is the first time period, which is a daytime period, the working environment should be a completely bright environment. However, if the working environment is identified as a partially dark environment, such as a shady area in a grassy area, the brightness of the target area in the partially dark environment will inevitably decrease. This may cause the robot to make a misjudgment and repeatedly perform the light-up and light-down operations. Therefore, it is necessary to reduce the preset light-up brightness threshold to obtain the light-up brightness threshold, so that the robot's judgment of performing the light-up operation is more rigorous and accurate, avoiding the situation where the robot repeatedly turns the lights on and off when passing through the shady area, thereby affecting the operation and service life of the light-up module.

[0077] Taking a lawnmower as an example, if the lawnmower is working in the shaded area of ​​the grass, since the shaded area is a discontinuous dark area, the lawnmower can identify the working environment as a locally dark environment by collecting environmental images. In this case, it can lower the preset light brightness threshold to obtain the light brightness threshold, so that the lawnmower's judgment on performing the light operation is more rigorous and accurate. This avoids the situation where the lawnmower repeatedly turns the lights on and off when passing through the shaded area, which would affect the operation and service life of the light-emitting module.

[0078] For example, if the image acquisition time is the first time period, since the first time period is the daytime period, the working environment should be a completely bright environment. However, if the working environment is identified as a completely dark environment, such as a large area of ​​grass under continuous shade, the brightness of the target area in a completely dark environment will inevitably be very low. Therefore, it is necessary to increase the preset luminous brightness threshold to obtain the luminous brightness threshold, so that the robot can more easily trigger the luminous operation, and the robot can turn on the light and perform the corresponding work more quickly.

[0079] Taking a lawnmower as an example, if the lawnmower is working under a large area of ​​continuous shade, the lawnmower can identify that the working environment is completely dark by collecting environmental images. In this case, it can increase the preset luminous brightness threshold to obtain the luminous brightness threshold, which makes it easier for the robot to trigger the luminous operation, so that the robot can turn on the light and perform the corresponding work faster.

[0080] It should be noted that if the image acquisition time is the second time period, which is generally the nighttime period, the nighttime period can be 18:00-6:00. If the image acquisition time is determined to be the second time period, since the robot generally needs to quickly identify the nighttime environment and perform the light emission operation during the nighttime period, the preset light emission brightness threshold can be left unchanged, or the preset light emission brightness threshold can be increased to obtain the light emission brightness threshold. No specific limitation is made here.

[0081] S104. If the brightness of the target area is less than the luminous brightness threshold, control the robot to perform a luminous operation.

[0082] Among them, the luminance threshold is the luminance threshold adjusted by the luminance gradient of the target area, which means that the adjusted luminance threshold is in line with the working environment of the robot.

[0083] For example, if the brightness of the target area is less than the luminous brightness threshold, it means that the brightness of the target area is low, which means that the robot is working in a dark environment. At this time, the robot can be controlled to turn on the supplementary light to illuminate the working environment, which is beneficial for the robot to work in a dark environment.

[0084] In some embodiments, after determining the luminance threshold based on the luminance gradient of the target area, the method further includes: acquiring the robot's moving speed and / or pitch angle; adjusting the luminance threshold based on the robot's moving speed and / or pitch angle to obtain a target luminance threshold; and controlling the robot to emit light if the luminance of the target area is less than the target luminance threshold.

[0085] The target luminance threshold is a luminance threshold that is dynamically adjusted based on the robot's moving speed and / or pitch angle. The target luminance threshold not only conforms to the robot's working environment but also to the robot's motion state.

[0086] When the robot is moving at high speeds or with large pitch angles, the environmental images it captures fluctuate significantly. This leads to large fluctuations in the brightness threshold adjusted based on these images, potentially causing frequent changes in the brightness of the target area and triggering frequent light-up and light-down actions. Conversely, when the robot is moving at low speeds or with small pitch angles, the environmental images it captures fluctuate less, resulting in smaller fluctuations in the brightness threshold adjusted based on these images. Consequently, the brightness of the target area remains relatively stable, and the triggering of light-up and light-down actions is more accurate.

[0087] In this embodiment, the luminance threshold is further adjusted by the robot's moving speed and / or pitch angle to obtain the target luminance threshold. If the brightness of the target area is less than the target luminance threshold, the robot is controlled to emit light. Therefore, the robot's luminance control also takes into account the robot's actual motion state, enabling the robot to perform luminance operation in a timely and accurate manner according to the actual working environment and actual motion state, without human intervention and control, effectively improving the robot's adaptability and luminance intelligence in dynamic environments.

[0088] In some embodiments, the environmental image also includes multiple adjacent frame images. If the robot's moving speed exceeds a preset speed threshold or the pitch angle is greater than a preset angle threshold, the regional brightness of the target area corresponding to the multiple adjacent frame images is obtained. If the regional brightness of the target area corresponding to the multiple environmental images is less than the luminous brightness threshold, the robot is controlled to perform a luminous operation.

[0089] Among them, environmental images also include multiple adjacent frame images. For example, a robot will usually continuously collect multiple environmental images during the movement or work process. At this time, the multiple environmental images are multiple adjacent frame images.

[0090] For example, if the robot's moving speed exceeds a preset speed threshold and / or the pitch angle is greater than a preset angle threshold, the regional brightness of the target area corresponding to multiple adjacent frames of images is obtained. That is, for each frame of image, the regional brightness of the target area corresponding to each frame of image is identified in the manner described in the above embodiment. If the regional brightness of the target area corresponding to multiple frames of environmental images is detected to be less than the luminous brightness threshold, it indicates that the robot is continuously in a dark environment. At this time, the robot can be controlled to perform a luminous operation. In this way, the adverse effects caused by the brightness detection fluctuations due to robot movement vibration and slope changes can be effectively solved.

[0091] For example, if the robot's moving speed does not exceed a preset speed threshold or the pitch angle is not greater than a preset angle threshold, the regional brightness of the target area corresponding to any adjacent frame image can be obtained. If the regional brightness of the target area corresponding to the environmental image of that frame is less than the luminous brightness threshold, it can be quickly identified that the robot is in a dark environment, and then the robot can be quickly controlled to perform the corresponding luminous operation. In this way, the response speed of the robot to perform luminous operation can be effectively improved.

[0092] In some embodiments, the method further includes: if the robot is in a light-emitting state, acquiring the regional brightness of the target area and the background area; if the regional brightness of the target area and the regional brightness of the background area are both greater than the light-off brightness threshold, controlling the robot to stop emitting light.

[0093] The brightness threshold for turning off the lights can be any brightness value, which can be determined according to the actual situation, and no specific limit is made here.

[0094] For example, if the robot is in a light-emitting state, it means that the robot is performing a light-emitting operation. The brightness of the target area and the background area is obtained. If the brightness of both the target area and the background area is detected to be greater than the brightness threshold for turning off the lights, it means that the brightness of the target area is relatively large, which means that the robot is working in a bright environment. At this time, the robot can be controlled to turn off the supplementary light to save power and avoid the robot wasting power.

[0095] In some embodiments, the method further includes: determining the regional brightness and standard deviation of the target area; determining a reflectance brightness threshold based on the regional brightness and standard deviation of the target area; and after controlling the robot to emit light, further including: re-determining the brightness information of the target area, the brightness information including the brightness value of each sampling point in the target area; and if the brightness value of the sampling point is greater than the reflectance brightness threshold, controlling the robot to adjust the emitting power and / or emitting angle.

[0096] For example, the regional brightness and standard deviation of the target area can be determined based on the brightness values ​​of each sampling point in the target area, and a dynamic contrast coefficient can be constructed based on the standard deviation, thereby determining the reflectance brightness threshold based on the regional brightness and dynamic contrast coefficient of the target area.

[0097] The reflectance threshold A can be calculated using the following formula: A = H * K.

[0098] Where A is the reflectance threshold, H is the regional brightness of the target area, and K is the dynamic contrast coefficient. The coefficient K is an empirical coefficient or adjustment factor used to determine whether a locally bright area belongs to a strongly reflective scene; the value of K is generally between 1.2 and 1.8.

[0099] For example, after controlling the robot to emit light, the environmental image is reacquired and the brightness information of the target area is determined. The brightness information includes the brightness value of each sampling point in the target area. If the brightness value of any sampling point is greater than the pre-determined reflection brightness threshold, the robot is determined to be in a strong reflection scene, and the robot is controlled to adjust the light emission power and / or light emission angle accordingly.

[0100] The embodiments of this application can dynamically adjust the luminance threshold by the brightness gradient of the target area, and accurately control whether the robot performs luminance operation by comparing the regional brightness of the target area with the adjusted luminance threshold. This enables the robot to perform luminance operation in a timely and accurate manner according to the actual working environment without human intervention or control, effectively improving the robot's adaptability and luminance intelligence in dynamic environments.

[0101] like Figure 6 As shown in the figure, this application embodiment also provides a robot 100, which includes a body 10, a driving module 20, a cutting mechanism 30, a light-emitting module 40, and a controller (not shown). The driving module 20 is used to drive the body 10; the cutting mechanism 30 is disposed on the body 10 and is used to cut the object to be cut; the light-emitting module 40 is disposed on the body 10 and is used to emit light; the controller is connected to the driving module 20, the cutting mechanism 30, and the light-emitting module 40.

[0102] For example, the robot 100 provided in this application embodiment can be used to perform lawn mowing operations while moving. Of course, it is not limited to this. The robot 100 provided in this application embodiment can also perform cleaning, snow sweeping, leaf blowing and other operations, which are not limited here.

[0103] Taking robot 100 as a lawnmower as an example, the cutting mechanism 30 is located at the bottom of the main body and is used to cut the grass to be cut. The grass to be cut includes, but is not limited to, grass on lawns, gardens and paths. In other words, the lawnmower can cut the grass on the lawn to ensure the aesthetics of the lawn. The driving module 20 is located on the main body 10 and is used to drive the main body 10 to move, so that the main body 10 can drive the cutting mechanism 30 to cut the grass on the lawn along a preset trajectory, thereby greatly reducing manual operation, saving time and effort, and truly freeing people from the labor of lawn maintenance.

[0104] Please see Figure 7 , Figure 7 This is a schematic block diagram of the structure of a robot 100 provided in an embodiment of this application. Figure 7In the robot 100, there are a processor 200 and a memory 300. The processor 200 and the memory 300 are connected by a bus, which can be any applicable bus such as an I2C (Inter-integrated Circuit) bus.

[0105] The memory 300 may include a storage medium and internal memory. The storage medium may store an operating system and a computer program. The computer program includes program instructions that, when executed, cause the processor to perform the light emission control method described in any embodiment.

[0106] The processor 200 provides computing and control capabilities to support the operation of the entire robot 100.

[0107] The processor 200 can be a Central Processing Unit (CPU), but it can also be a general-purpose processor, a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or it can be any conventional processor.

[0108] The processor 200 is used to run a computer program stored in the memory 300, and performs the following steps when executing the computer program: The system acquires an environmental image corresponding to the robot's environment and identifies a target region within the image. It then determines the brightness information of the target region and, based on this information, determines the region's brightness and brightness gradient. Finally, it determines a luminous intensity threshold based on the target region's brightness gradient. If the region's brightness is less than the luminous intensity threshold, the system controls the robot to perform a light-emitting operation.

[0109] In some embodiments, the processor 200 determines a target region in the environmental image to: Determine the vanishing point and vehicle end boundary in the environmental image; based on the vanishing point and vehicle end boundary in the environmental image, divide the target region in the environmental image.

[0110] In some embodiments, the processor 200, in determining the brightness information of the target region, is used to: The environmental image is converted into a color space image; the brightness of the target area in the color space image is extracted to obtain the brightness information of the target area.

[0111] In some embodiments, the brightness information of the target region includes the brightness values ​​of each sampling point in the target region. The processor 200, in implementing the determination of the regional brightness and brightness gradient of the target region based on the brightness information of the target region, is used to: The average value of the brightness values ​​of each sampling point in the target area is determined, and the average value is used as the regional brightness of the target area; the gradient amplitude and gradient direction are determined based on the brightness values ​​of each sampling point in the target area, and the brightness gradient of the target area is determined based on the gradient amplitude and the gradient direction.

[0112] In some embodiments, the processor 200, in implementing the determination of a light emission threshold based on the brightness gradient of the target region, is used to: If the brightness gradient of the target area is greater than a preset gradient threshold, the preset luminous brightness threshold is reduced to obtain the luminous brightness threshold; if the brightness gradient of the target area is not greater than the preset gradient threshold, the preset luminous brightness threshold is increased to obtain the luminous brightness threshold.

[0113] In some embodiments, the processor 200, in implementing the determination of a light emission threshold based on the brightness gradient of the target region, is used to: The brightness information of the background area is obtained, and the working environment of the robot is determined based on the brightness gradient of the target area and the brightness information of the background area; the preset luminous brightness threshold is adjusted according to the working environment of the robot to obtain the luminous brightness threshold.

[0114] In some embodiments, the processor 200 determines the robot's working environment based on the brightness gradient of the target area and the brightness information of the background area, for the following purposes: If the brightness gradient of the target area is greater than a preset gradient threshold, and the brightness information of the background area is greater than a preset brightness threshold, then the working environment of the robot is determined to be a partially dark environment; if the brightness gradient of the target area is not greater than a preset gradient threshold, and the brightness information of the background area is not greater than a preset brightness threshold, then the working environment of the robot is determined to be a completely dark environment.

[0115] In some embodiments, the processor 200 adjusts a preset luminance threshold according to the robot's working environment to obtain the luminance threshold, thereby achieving: The image acquisition time of the environmental image is obtained, and the preset luminous brightness threshold is adjusted according to the image acquisition time and the working environment to obtain the luminous brightness threshold.

[0116] In some embodiments, the processor 200 adjusts a preset luminance threshold based on the image acquisition time and the working environment to obtain the luminance threshold, thereby achieving: If the image acquisition time is a first time period and the working environment is a partially dark environment, then the preset luminous brightness threshold is reduced to obtain the luminous brightness threshold; if the image acquisition time is a first time period and the working environment is a completely dark environment, then the preset luminous brightness threshold is increased to obtain the luminous brightness threshold.

[0117] In some embodiments, after determining the luminance threshold based on the luminance gradient of the target region, the processor 200 is configured to: The robot's moving speed and / or pitch angle are obtained; the luminance threshold is adjusted according to the robot's moving speed and / or pitch angle to obtain a target luminance threshold; if the brightness of the target area is less than the target luminance threshold, the robot is controlled to emit light.

[0118] In some embodiments, the environmental image further includes multiple adjacent frame images, and the processor 200 adjusts the luminance threshold according to the robot's movement speed and / or pitch angle to obtain a target luminance threshold, for the purpose of: If the robot's moving speed exceeds a preset speed threshold and / or the pitch angle is greater than a preset angle threshold, then the regional brightness of the target area corresponding to multiple adjacent frame images is obtained; if the regional brightness of the target area corresponding to multiple environmental images is less than the luminous brightness threshold, then the robot is controlled to perform a luminous operation.

[0119] In some embodiments, the processor 200 is further configured to implement: If the robot is in a light-emitting state, the brightness of the target area and the background area is obtained; if the brightness of both the target area and the background area is greater than the light-off brightness threshold, the robot is controlled to stop emitting light.

[0120] In some embodiments, the processor 200 is further configured to implement: Determine the regional brightness and standard deviation of the target area; determine the reflectance threshold based on the regional brightness and standard deviation of the target area; After controlling the robot to emit light, the processor 200 is also used to: The brightness information of the target area is redefined, including the brightness value of each sampling point in the target area; if the brightness value of the sampling point is greater than the reflection brightness threshold, the robot is controlled to adjust the luminous power and / or luminous angle.

[0121] This application also provides a computer-readable storage medium storing a computer program, which includes program instructions. A processor executes these program instructions to implement any of the light-emitting control methods provided in this application's embodiments. For example, when the computer program is loaded by a processor, it can perform the following steps: Collect environmental images corresponding to the environment in which the robot is located, and determine the target area in the environmental images; Determine the brightness information of the target area, and determine the regional brightness and brightness gradient of the target area based on the brightness information of the target area; The luminance threshold is determined based on the luminance gradient of the target region; If the brightness of the target area is less than the luminous brightness threshold, then the robot is controlled to perform a luminous operation.

[0122] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0123] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0124] It should also be understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, herein, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system 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 system. 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 system that includes that element.

[0125] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. The above descriptions are merely specific implementations of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A light emission control method characterized by, The method is applied to a robot, and the method comprises the following steps: An environment image corresponding to an environment where the robot is located is collected, and a target region is determined in the environment image; Brightness information of the target region is determined, and region brightness and a brightness gradient of the target region are determined according to the brightness information of the target region; A light-emitting brightness threshold is determined according to the brightness gradient of the target region; If the region brightness of the target region is less than the light-emitting brightness threshold, the robot is controlled to perform a light-emitting operation.

2. The method of claim 1, wherein, The target region is determined in the environment image, which comprises the following steps: Vanishing points and vehicle end boundaries in the environment image are determined; The target region is divided in the environment image according to the vanishing points and the vehicle end boundaries in the environment image.

3. The method of claim 1, wherein, The brightness information of the target region is determined, which comprises the following steps: The environment image is converted into a color space image; Brightness extraction is performed on the target region of the color space image to obtain the brightness information of the target region.

4. The method of claim 1, wherein, The brightness information of the target region comprises brightness values of each sampling point in the target region, and the region brightness and the brightness gradient of the target region are determined according to the brightness information of the target region, which comprises the following steps: An average value of the brightness values of each sampling point in the target region is determined, and the average value is taken as the region brightness of the target region; Gradient amplitudes and gradient directions are determined according to the brightness values of each sampling point in the target region, and the brightness gradient of the target region is determined according to the gradient amplitudes and the gradient directions.

5. The method of claim 1, wherein, The light-emitting brightness threshold is determined according to the brightness gradient of the target region, which comprises the following steps: If the brightness gradient of the target region is greater than a preset gradient threshold, the preset light-emitting brightness threshold is reduced to obtain the light-emitting brightness threshold; If the brightness gradient of the target region is not greater than the preset gradient threshold, the preset light-emitting brightness threshold is increased to obtain the light-emitting brightness threshold.

6. The method of claim 1, wherein, The light-emitting brightness threshold is determined according to the brightness gradient of the target region, which comprises the following steps: Brightness information of a background region is obtained, the background region being a region between a boundary corresponding to a vanishing point and an edge on the environment image; A working environment of the robot is determined according to the brightness gradient of the target region and the brightness information of the background region; The preset light-emitting brightness threshold is adjusted according to the working environment of the robot to obtain the light-emitting brightness threshold.

7. The method of claim 6, wherein, The working environment of the robot is determined according to the brightness gradient of the target region and the brightness information of the background region, which comprises the following steps: If the brightness gradient of the target region is greater than a preset gradient threshold, and the brightness information of the background region is greater than a preset brightness threshold, it is determined that the working environment of the robot is a local dark environment; If the brightness gradient of the target region is not greater than the preset gradient threshold, and the brightness information of the background region is not greater than the preset brightness threshold, it is determined that the working environment of the robot is a complete dark environment.

8. The method of claim 6, wherein, The preset light-emitting brightness threshold is adjusted according to the working environment of the robot to obtain the light-emitting brightness threshold, which comprises the following steps: acquire an image acquisition time of the environment image, and adjust a preset light-emitting brightness threshold according to the image acquisition time and the working environment to obtain the light-emitting brightness threshold.

9. The method of claim 8, wherein, The adjusting the preset light-emitting brightness threshold according to the image acquisition time and the working environment to obtain the light-emitting brightness threshold comprises: if the image acquisition time is a first time period and the working environment is a local dark environment, the preset light-emitting brightness threshold is reduced to obtain the light-emitting brightness threshold; if the image acquisition time is the first time period and the working environment is a completely dark environment, the preset light-emitting brightness threshold is increased to obtain the light-emitting brightness threshold.

10. The method of claim 1, wherein, The method further comprises: acquiring a moving speed and / or a pitch angle of the robot; adjusting the light-emitting brightness threshold according to the moving speed and / or the pitch angle of the robot to obtain a target light-emitting brightness threshold; if the area brightness of the target region is less than the target light-emitting brightness threshold, controlling the robot to emit light.

11. The method of claim 10, wherein, The environment image further comprises a plurality of adjacent frame images, and the adjusting the light-emitting brightness threshold according to the moving speed and / or the pitch angle of the robot to obtain a target light-emitting brightness threshold comprises: if the moving speed of the robot exceeds a preset speed threshold and / or the pitch angle is greater than a preset angle threshold, acquiring the area brightness of the target region corresponding to a plurality of adjacent frame images; if the area brightness of the target region corresponding to a plurality of environment images is less than the light-emitting brightness threshold, controlling the robot to perform a light-emitting operation.

12. The method of claim 1, wherein, The method further comprises: if the robot is in a light-emitting state, acquiring the area brightness of the target region and a background region; if the area brightness of the target region and the area brightness of the background region are both greater than a light-off brightness threshold, controlling the robot to stop emitting light.

13. The method of claim 1, wherein, The method further comprises: determining the area brightness and the standard deviation of the target region; determining a reflection brightness threshold according to the area brightness and the standard deviation of the target region; The method further comprises: redetermining the brightness information of the target region, the brightness information comprising the brightness value of each sampling point in the target region; if the brightness value of the sampling point is greater than the reflection brightness threshold, controlling the robot to adjust the light-emitting power and / or the light-emitting angle.

14. A robot, characterized in that The robot comprises: a body; a driving module for driving the body to move; a cutting mechanism arranged on the body and used for cutting a to-be-cut object; a light-emitting module arranged on the body and used for emitting light; a controller connected to the driving module, the cutting mechanism and the light-emitting module, and used for executing the light-emitting control method according to any one of claims 1-13.

15. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the light-emitting control method according to any one of claims 1-13.

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