Operation robot, cliff detection method and device thereof and computer equipment

Abstract

The invention relates to an operation robot, a cliff detection method and device thereof and computer equipment, and the method comprises the steps that the operation robot is provided with a first infrared transmitting tube and a second infrared transmitting tube, the first infrared transmitting tube is used for transmitting infrared light of a first wavelength, and the second infrared transmitting tube is used for transmitting infrared light of a second wavelength; the first wavelength infrared light is infrared light with the sunlight sensitivity not larger than a preset sensitivity lower limit value, and the second wavelength infrared light is infrared light with the sunlight sensitivity not smaller than a preset sensitivity upper limit value. When cliff detection is carried out, a first reflection signal corresponding to the first wavelength infrared light and a second reflection signal corresponding to the second wavelength infrared light are obtained; obtaining effective cliff signal intensity according to the ratio of the first reflection signal to the second reflection signal; and if the effective cliff signal intensity is greater than the preset cliff signal intensity threshold value, judging that the height of the cliff in front of the operation is the height of the cliff.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and in particular to a working robot and its cliff detection method, apparatus, computer equipment, storage medium and computer program product. Background Technology

[0002] As a significant achievement in modern automation technology, operational robots play an increasingly crucial role in numerous scenarios, including industrial production, domestic services, and logistics. Their core objective is to efficiently, accurately, and safely complete various tasks, and accurate environmental perception is indispensable for achieving this goal. Cliff detection, a vital component of the operational robot's environmental perception system, is essential for ensuring the robot's safe operation in complex terrain environments. It can monitor in real time for dangerous terrain such as cliffs ahead of the robot, triggering obstacle avoidance or stopping mechanisms in a timely manner, effectively preventing damage from accidental falls, and thus ensuring the continuity and stability of the operational tasks.

[0003] Currently, in many practical applications of robots, such as the robotic vacuum cleaners widely used in home cleaning, the infrared photocell (transmitter + receiver) technology is commonly used to achieve cliff detection. Infrared photocell detection technology gained widespread application in its early stages due to its low cost and simple implementation. Its basic principle is that the infrared emitter emits infrared light of a specific wavelength; when this infrared light shines on the surface of an object, it is reflected. The reflected light is received by the infrared receiver, and the presence of a cliff is determined by analyzing and processing the received signal.

[0004] However, as the application scenarios of robots continue to expand and become more complex, existing cliff detection solutions based on infrared photocells are easily affected by ambient light (sunlight) and cannot cope with sudden changes in light intensity. When a robot (sweeping robot) is working near a window or balcony or other sunny area, it may mistakenly believe that there is a cliff in front of it due to strong light interference, and thus stop working or change its route, which seriously affects the efficiency and effectiveness of the operation. Summary of the Invention

[0005] Therefore, it is necessary to provide an accurate cliff detection robot and its cliff detection method, device, computer equipment, storage medium and computer program products to address the above-mentioned technical problems.

[0006] In a first aspect, this application provides a cliff detection method for a work robot. The work robot is equipped with a first infrared emitting tube and a second infrared emitting tube. The first infrared emitting tube is used to emit infrared light of a first wavelength, and the second infrared emitting tube is used to emit infrared light of a second wavelength. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower sensitivity limit, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper sensitivity limit.

[0007] The cliff detection method for the operating robot includes:

[0008] Acquire the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light;

[0009] The effective cliff signal strength is obtained based on the ratio of the first reflected signal to the second reflected signal.

[0010] If the effective cliff signal strength is greater than the preset cliff signal strength threshold, then it is determined that there is a cliff drop ahead of the work site.

[0011] In one embodiment, obtaining the effective cliff signal strength based on the ratio of the first reflected signal to the second reflected signal includes:

[0012] Obtain ambient light intensity;

[0013] The signal strength of the second reflected signal is compensated based on the ambient light intensity to obtain the reference signal strength;

[0014] The effective cliff signal strength is obtained by calculating the ratio of the signal strength of the first reflected signal to the signal strength of the reference signal.

[0015] In one embodiment, the step of compensating the signal strength of the second reflected signal based on the ambient light intensity to obtain the reference signal strength includes:

[0016] The compensation coefficient is obtained based on the ambient light intensity.

[0017] Based on the ambient light intensity and the compensation coefficient, the light intensity correction amount is obtained;

[0018] Obtain the noise suppression constant;

[0019] The reference signal strength is obtained based on the signal strength of the second reflected signal, the light intensity correction amount, and the noise suppression constant.

[0020] In one embodiment, obtaining the compensation coefficient based on the ambient light intensity includes:

[0021] Compare the ambient light intensity with a preset benchmark ambient light intensity range threshold;

[0022] If the ambient light intensity is greater than the upper limit of the preset benchmark ambient light intensity range threshold, then the compensation coefficient is determined to be the first compensation value;

[0023] If the ambient light intensity is not greater than the upper limit of the preset benchmark ambient light intensity range threshold and not less than the lower limit of the preset benchmark ambient light intensity range threshold, then the compensation coefficient is determined to be the sum of the second compensation value and the light intensity correction amount, wherein the light intensity correction amount is positively correlated with the ambient light intensity.

[0024] If the ambient light intensity is less than the lower limit of the preset reference ambient light intensity range threshold, then the compensation coefficient is determined to be the second compensation value;

[0025] Among them, the sum of the first compensation value, the second compensation value and the light intensity correction amount, and the second compensation value decrease sequentially.

[0026] In one embodiment, before determining that there is a cliff ahead if the effective cliff signal strength is greater than a preset cliff signal strength threshold, the method further includes:

[0027] Obtain the initial cliff signal strength threshold;

[0028] When a cliff height setting message is received, the actual cliff height value carried in the cliff height setting message is read.

[0029] The initial cliff signal strength threshold is corrected based on the actual cliff height to obtain the preset cliff signal strength threshold.

[0030] The cliff height setting message is generated when the robot is placed at the cliff drop position in the user selection setting mode.

[0031] In one embodiment, the above-mentioned cliff detection method for the work robot further includes:

[0032] If the effective cliff signal strength is not greater than the preset cliff signal strength threshold, it is determined that there is no cliff drop in front of the work area.

[0033] After waiting for a preset time, return to the step of obtaining the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light.

[0034] In one embodiment, the first wavelength infrared light includes infrared light with a wavelength of 940nm ± 10nm; the second wavelength infrared light includes infrared light with a wavelength of 850nm ± 10nm.

[0035] Secondly, this application also provides a cliff detection device for a work robot. The work robot is equipped with a first infrared emitting tube and a second infrared emitting tube. The first infrared emitting tube is used to emit infrared light of a first wavelength, and the second infrared emitting tube is used to emit infrared light of a second wavelength. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower sensitivity limit, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper sensitivity limit.

[0036] The cliff detection device for the operating robot includes:

[0037] The receiving module is used to acquire the first reflected signal corresponding to the first wavelength infrared light and the second reflected signal corresponding to the second wavelength infrared light;

[0038] The intensity detection module is used to obtain the effective cliff signal intensity based on the ratio of the first reflected signal to the second reflected signal;

[0039] The processing module is used to determine that there is a cliff drop ahead when the effective cliff signal strength is greater than a preset cliff signal strength threshold.

[0040] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0041] Acquire the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light;

[0042] The effective cliff signal strength is obtained based on the ratio of the first reflected signal to the second reflected signal.

[0043] If the effective cliff signal strength is greater than the preset cliff signal strength threshold, then it is determined that there is a cliff drop ahead of the work site.

[0044] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0045] Acquire the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light;

[0046] The effective cliff signal strength is obtained based on the ratio of the first reflected signal to the second reflected signal.

[0047] If the effective cliff signal strength is greater than the preset cliff signal strength threshold, then it is determined that there is a cliff drop ahead of the work site.

[0048] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0049] Acquire the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light;

[0050] The effective cliff signal strength is obtained based on the ratio of the first reflected signal to the second reflected signal.

[0051] If the effective cliff signal strength is greater than the preset cliff signal strength threshold, then it is determined that there is a cliff drop ahead of the work site.

[0052] Sixthly, this application also provides a working robot, including a first infrared emitting tube, a second infrared emitting tube, and a controller. The first infrared emitting tube is used to emit infrared light of a first wavelength, and the second infrared emitting tube is used to emit infrared light of a second wavelength. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower sensitivity limit, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper sensitivity limit. The controller uses the detection method described above to perform cliff detection.

[0053] The aforementioned operational robot and its cliff detection method, device, computer equipment, storage medium, and computer program product include a first infrared emitter and a second infrared emitter. The first infrared emitter emits a first wavelength of infrared light, and the second infrared emitter emits a second wavelength of infrared light. The first wavelength of infrared light has a sensitivity to sunlight not exceeding a preset lower limit, and the second wavelength of infrared light has a sensitivity to sunlight not less than a preset upper limit. During cliff detection, the system acquires a first reflection signal corresponding to the first wavelength of infrared light and a second reflection signal corresponding to the second wavelength of infrared light. The effective cliff signal intensity is obtained based on the ratio of the first and second reflection signals. If the effective cliff signal intensity is greater than a preset cliff signal intensity threshold, a cliff drop is determined to be ahead of the operation. Throughout the detection process, the influence of ambient sunlight is eliminated by using the ratio of the reflection signal intensities corresponding to the two infrared bands with significantly different sensitivities to sunlight (one high, one low), thereby achieving stable and accurate cliff detection. Attached Figure Description

[0054] Figure 1 This is an application environment diagram of the cliff detection method for a work robot in one embodiment;

[0055] Figure 2 This is a flowchart illustrating a cliff detection method for a work robot in one embodiment;

[0056] Figure 3 This is a flowchart illustrating the cliff detection method for a work robot in another embodiment;

[0057] Figure 4 This is a structural block diagram of a cliff detection device for a work robot in one embodiment;

[0058] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] The cliff detection method for work robots provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown is a robotic vacuum cleaner. The vacuum cleaner is equipped with a first infrared emitter 101 (located inside the vacuum cleaner, indicated by a dashed line, its specific location is not limited) and a second infrared emitter 102 (located inside the vacuum cleaner, indicated by a dashed line, its specific location is not limited). The first infrared emitter 101 emits a first wavelength of infrared light, and the second infrared emitter 102 emits a second wavelength of infrared light. The first wavelength of infrared light has a sensitivity to sunlight not exceeding a preset lower sensitivity limit, and the second wavelength of infrared light has a sensitivity to sunlight not less than a preset upper sensitivity limit. A controller 103 with a built-in infrared receiver acquires the first reflected signal corresponding to the first wavelength of infrared light and the second reflected signal corresponding to the second wavelength of infrared light. Based on the ratio of the first and second reflected signals, the effective cliff signal strength is obtained. If the effective cliff signal strength is greater than a preset cliff signal strength threshold, it is determined that there is a cliff drop ahead. Furthermore, the controller 103 can also control the robot vacuum to stop moving forward after detecting a cliff drop, reset a new cleaning path based on its current position, and then continue cleaning according to the new cleaning path.

[0061] In one embodiment, this application provides a cliff detection method for a work robot, which is specifically applied to a work robot. The work robot is equipped with a first infrared emitting tube and a second infrared emitting tube. The first infrared emitting tube is used to emit infrared light of a first wavelength, and the second infrared emitting tube is used to emit infrared light of a second wavelength. The first wavelength infrared light is infrared light whose sensitivity to sunlight is not greater than a preset lower limit value, and the second wavelength infrared light is infrared light whose sensitivity to sunlight is not less than a preset upper limit value.

[0062] The operational robot may include, but is not limited to, robotic vacuum cleaners, lawnmowers, and food delivery robots. For ease of explanation, the following content of this application will use a robotic vacuum cleaner as an example to describe the technical solution of this application in detail. In specific applications, the operational robot is equipped with a first infrared emitting tube and a second infrared emitting tube. The first infrared emitting tube is used to emit infrared light of a first wavelength, which is infrared light with a sensitivity to sunlight not greater than a preset lower sensitivity limit. This means that the infrared light in this band is minimally affected by sunlight interference, has strong anti-interference capabilities, and can maintain relatively stable emission characteristics under different lighting conditions, providing a reliable basis for subsequent accurate detection. The second infrared emitting tube is used to emit infrared light of a second wavelength, which is infrared light with a sensitivity to sunlight not less than a preset upper sensitivity limit. That is, the infrared light in this band is more sensitive to changes in sunlight, and its emission and reception will change significantly with changes in ambient light (mainly sunlight). Simply put, the first infrared emitting tube serves as the main infrared emitting tube, and the first wavelength infrared light emitted by the main infrared emitting tube has low sensitivity to sunlight and stronger anti-interference capabilities. The second infrared emitter serves as an auxiliary infrared emitter. The second wavelength of infrared light emitted by this auxiliary emitter is highly sensitive to sunlight and easily affected by ambient light. With this configuration, the first infrared light is a highly interference-resistant infrared band, while the second infrared light is sensitive to sunlight. Compensation is achieved through an ambient light sensor. The ratio of the received intensities of the two bands eliminates the influence of visible light. When ambient light changes, this ratio is insensitive to changes in ambient light, thus ensuring stable and accurate detection.

[0063] Here, the preset lower and upper sensitivity limits constitute a baseline range for sunlight sensitivity. Infrared light above this baseline range is considered to have high sunlight sensitivity and is used as the first wavelength infrared light. Infrared light below this baseline range is considered to have low sunlight sensitivity and is used as the second wavelength infrared light. This baseline range can be determined based on industry standards. More specifically, the first wavelength infrared light can be infrared light with a wavelength of 940nm ± 10nm; the second wavelength infrared light is infrared light with a wavelength of 850nm ± 10nm. Preferably, the first wavelength infrared light is infrared light with a wavelength of 940nm; the second wavelength infrared light is infrared light with a wavelength of 850nm.

[0064] like Figure 2 As shown, the cliff detection method for the operation robot includes:

[0065] S200: Acquire the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light.

[0066] During operation, the robot emits infrared light of a first wavelength from a first infrared emitter and infrared light of a second wavelength from a second infrared emitter. These two types of infrared light are reflected after striking the surface of an object in front of the robot. The corresponding receiving devices on the robot acquire the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light. This step collects intensity information of infrared light of different wavelengths after reflection from the environment in front of the robot, providing a data basis for subsequent analysis.

[0067] S400: Obtain the effective cliff signal strength based on the ratio of the first reflected signal and the second reflected signal.

[0068] Based on the acquired first and second reflected signals, their ratio is calculated to obtain the effective cliff signal intensity. Since the first wavelength infrared light has strong anti-interference properties, while the second wavelength infrared light is sensitive to sunlight, changes in ambient light (such as sunlight) will affect both the first and second reflected signals to some extent. However, by calculating their ratio, the influence of visible light (mainly sunlight) can be effectively eliminated. Because the changing trends of the two reflected signals are correlated to some extent when ambient light changes, the ratio is not sensitive to changes in ambient light, thus yielding a relatively stable and accurate effective cliff signal intensity that reflects the actual situation ahead of the operation. Here, a unique dual-band ratio method achieves stable detection under complex lighting conditions.

[0069] S600: If the effective cliff signal strength is greater than the preset cliff signal strength threshold, it is determined that there is a cliff drop ahead of the operation.

[0070] The calculated effective cliff signal strength is compared with a preset cliff signal strength threshold. If the effective cliff signal strength is greater than the preset threshold, it is determined that there is a cliff drop ahead of the work area. The preset cliff signal strength threshold was determined through extensive experiments and real-world scenario testing. When the effective cliff signal strength exceeds this threshold, it indicates a significant height difference ahead, i.e., a cliff. The robot needs to take appropriate measures in a timely manner, such as stopping or changing its path, to avoid danger. Here, based on the previously calculated effective signal strength, an accurate judgment is made on the terrain conditions ahead of the work area, ensuring the safe operation of the robot.

[0071] The aforementioned cliff detection method using a robotic operation robot includes a first infrared emitter and a second infrared emitter. The first emitter emits infrared light of a first wavelength, and the second emitter emits infrared light of a second wavelength. The first wavelength infrared light has a sensitivity to sunlight not exceeding a preset lower limit, and the second wavelength infrared light has a sensitivity to sunlight not less than a preset upper limit. During cliff detection, the robot acquires the first reflected signal corresponding to the first wavelength infrared light and the second reflected signal corresponding to the second wavelength infrared light. The effective cliff signal intensity is obtained based on the ratio of the first and second reflected signals. If the effective cliff signal intensity is greater than a preset cliff signal intensity threshold, the robot is determined to be facing a cliff with a drop. Throughout the detection process, the influence of ambient sunlight is eliminated by using the ratio of the reflected signal intensities corresponding to the two infrared light bands with significantly different sensitivities to sunlight (one high, one low), thereby achieving stable and accurate cliff detection.

[0072] In one embodiment, such as Figure 3 As shown, the effective cliff signal strength is obtained based on the ratio of the first reflected signal and the second reflected signal, including:

[0073] S420: Acquire ambient light intensity.

[0074] Ambient light intensity is monitored in real time using ambient light sensors mounted on the robot. These sensors accurately detect changes in ambient light, capturing variations in intensity under different lighting conditions such as direct sunlight and indoor lighting, and converting them into corresponding electrical signals to obtain quantifiable ambient light intensity values. Strong light (such as direct sunlight and indoor lighting) simultaneously amplifies reflection signals across all wavelengths, causing drastic fluctuations in the absolute value of single-band sensors, rendering threshold determination methods based on single-band signals ineffective. Acquiring ambient light intensity is crucial for subsequent accurate compensation of reflection signals affected by ambient light, eliminating ambient light interference, and ensuring the accuracy of the detection results.

[0075] S440: Compensate the signal strength of the second reflected signal based on the ambient light intensity to obtain the reference signal strength.

[0076] Because the second wavelength infrared light emitted by the second infrared emitter (auxiliary infrared emitter) is sensitive to sunlight, changes in ambient light can significantly affect its reflected signal. In this step, the signal strength of the second reflected signal is compensated based on the ambient light intensity, and the intensity of the reflected signal emitted by the second infrared emitter after eliminating ambient light interference is calculated to obtain the reference signal strength.

[0077] S460: Calculate the ratio of the signal strength of the first reflected signal to the reference signal strength to obtain the effective cliff signal strength.

[0078] The first reflected signal is the signal received after reflection of the first wavelength infrared light. It is less affected by ambient light interference and can more accurately reflect the actual situation ahead of the work area. The reference signal intensity is the intensity of the second reflected signal after ambient light compensation. The effective cliff signal intensity is obtained by calculating the ratio of the intensity of the first reflected signal to the intensity of the reference signal. Because the influence of ambient light on the first and second wavelength bands is similar, the ratio of the reflected signals in the two bands is not affected by changes in light intensity; it depends only on the spectral characteristics of the material itself. By calculating this ratio to obtain the effective cliff signal intensity, the influence of ambient light variations on the detection results can be eliminated, ensuring a stable and accurate detection signal under different lighting conditions. This provides a reliable basis for accurately determining whether there is a cliff ahead of the work area.

[0079] In practical applications, the effective cliff signal is calculated in real time based on the following formula, using the dual-band ratio method (dual-band ratio = reflected signal intensity of band A / reflected signal intensity of band B, mathematical expression: R = ρA / ρB, where ρA = reflected signal intensity of band A (i.e., the first reflected signal intensity), and ρB = reflected signal intensity of band B (reference signal intensity). Because the second wavelength infrared light is sensitive to sunlight, the corresponding content in sunlight needs to be subtracted to calculate the infrared content reflected back by the second infrared emitter, thus reducing interference from sunlight.

[0080] In one embodiment, the reference signal strength is obtained by compensating the signal strength of the second reflected signal based on the ambient light intensity, including:

[0081] Step 1: Obtain the compensation coefficient based on the ambient light intensity.

[0082] The compensation coefficient k is based on the ambient light intensity I. env The parameters are dynamically calculated. Because the second wavelength (the wavelength corresponding to the second wavelength infrared light) is relatively close to the visible light band, ambient light has a significant impact on it. The degree of interference from ambient light varies depending on the ambient light intensity. Through a specific algorithm or a preset mapping relationship, the ambient light intensity I is... env This is converted into the corresponding compensation coefficient k. For example, the compensation coefficient values ​​corresponding to different ambient light intensity ranges can be determined in advance through numerous experiments and stored in the control system of the robot. During actual detection, the compensation coefficient is calculated based on the real-time measured ambient light intensity I. env Find the corresponding compensation coefficient k. Alternatively, determine the corresponding compensation coefficient k according to a certain range of light intensity values.

[0083] Step 2: Based on the ambient light intensity and the compensation coefficient, obtain the light intensity correction amount.

[0084] The light intensity correction is achieved by adjusting the ambient light intensity I. env The result is obtained by multiplying by the compensation coefficient k, i.e., k*I env This calculation is based on the influence of ambient light on the received signal of the second wavelength infrared light. The greater the intensity of ambient light, the stronger the interference on the received signal of the second wavelength infrared light. The compensation coefficient k reflects the proportional relationship of this interference. Therefore, the light intensity correction obtained by multiplying the two can accurately represent the interference component of ambient light in the received signal of the second wavelength infrared light.

[0085] Step 3: Obtain the noise suppression constant.

[0086] Noise suppression constant This is a pre-set constant, its purpose being to prevent the denominator from approaching 0 during subsequent calculations of the effective cliff signal, which would lead to an infinitely large calculation result. In practical applications, due to various noises and measurement errors, the received signal intensity I2 of the second wavelength infrared light is reduced by the light intensity correction amount k*I. env Afterwards, the denominator may approach 0. This can be addressed by introducing a noise suppression constant. This ensures that the denominator is always greater than a minimum value, thus ensuring the stability and reliability of the calculation results.

[0087] Step 4: Obtain the reference signal strength based on the signal strength of the second reflected signal, the light intensity correction amount, and the noise suppression constant.

[0088] The reference signal strength is calculated by subtracting the light intensity correction amount k*I from the signal strength I2 of the second reflected signal. env In addition to the noise suppression constant The obtained value is the reference signal strength = I² + -k*I env This calculation process integrates the key parameters obtained in the previous steps, aiming to eliminate the interference of ambient light on the 850nm wavelength infrared light reflection signal and avoid the problem of the denominator being 0.

[0089] In one embodiment, obtaining the compensation coefficient based on the ambient light intensity includes:

[0090] Step 1: Compare the ambient light intensity with the preset baseline ambient light intensity range threshold.

[0091] The preset baseline ambient light intensity range threshold includes an upper and lower limit, which were determined through extensive experiments and data analysis. These thresholds are used to define the range of interference levels between different lighting environments and the received second-wavelength infrared light signals. The ambient light sensor measures the light intensity of the environment in which the robot operates in real time and compares this measurement with the preset baseline ambient light intensity range threshold to determine the type of current ambient lighting conditions.

[0092] Step 2: If the ambient light intensity is greater than the upper limit of the preset benchmark ambient light intensity range threshold, then the compensation coefficient is determined as the first compensation value.

[0093] When the ambient light intensity exceeds the upper limit of the preset baseline ambient light intensity range threshold, it indicates that the robot is in a strong light environment. According to the technical disclosure document, ambient light significantly interferes with the received second-wavelength infrared light signal in this situation, requiring a large compensation coefficient to effectively eliminate the interference. In a specific application example, the first compensation value can be set to 0.15. This is based on the fact that in a strong light environment, the second-wavelength infrared light has a high content in the ambient light. To ensure that the received second-wavelength signal is mainly the signal emitted by the transmitter, and to reduce ambient light interference, a suitable compensation value is determined.

[0094] Step 3: If the ambient light intensity is not greater than the upper limit of the preset benchmark ambient light intensity range threshold and not less than the lower limit of the preset benchmark ambient light intensity range threshold, then the compensation coefficient is determined to be the sum of the second compensation value and the light intensity correction amount. The light intensity correction amount is positively correlated with the ambient light intensity.

[0095] When the ambient light intensity is between the upper and lower limits of the preset baseline ambient light intensity range, the robot is in a medium lighting environment. At this time, the ambient light interferes with the second-wavelength infrared light reception signal to some extent, but not as strongly as in a strong light environment. The second compensation value is set to a relatively small value, such as 0.025. In addition to the second compensation value, the compensation coefficient further considers the light intensity correction amount, which is positively correlated with the ambient light intensity. Its calculation formula can be 0.00005*I. env (I) env (Ambient light intensity). This setting is based on the fact that, under moderate lighting conditions, the compensation coefficient can be dynamically adjusted according to the actual changes in ambient light intensity by summing the second compensation value and the light intensity correction amount, thus more accurately eliminating ambient light interference.

[0096] Step 4: If the ambient light intensity is less than the lower limit of the preset reference ambient light intensity range threshold, then the compensation coefficient is determined as the second compensation value; wherein, the sum of the first compensation value, the second compensation value and the light intensity correction amount, and the second compensation value decrease sequentially.

[0097] When the ambient light intensity is less than the lower limit of the preset baseline ambient light intensity range threshold, the robot is in a low-light environment. At this time, ambient light interference is minimal, and the infrared receiver detects the second reflected signal within a linear response range. To avoid overcompensation of the infrared signal, the compensation coefficient is set to a second compensation value of 0.05. The sum of the first compensation value, the second compensation value, and the light intensity correction, as well as the second compensation value, decrease sequentially. This setting conforms to the law that the interference of ambient light on the second reflected signal gradually decreases under different lighting conditions, ensuring reasonable compensation under various lighting conditions.

[0098] In specific application examples, using the visible light intensity measured by the ambient light sensor as a benchmark, the content of the second wavelength infrared light in the ambient light is typically 5%~15%. When the ambient light intensity < 500, k = 0.05, indicating a low-light mode; when 500 ≤ k ≤ 2500, k = 0.025 + 0.00005 * I env The system dynamically adjusts to reduce the impact of ambient light; when k > 2500, k = 0.15, indicating that it has entered the strong light mode.

[0099] In one embodiment, before determining that there is a cliff ahead of the work area if the effective cliff signal strength is greater than a preset cliff signal strength threshold, the method further includes:

[0100] Step 1: Obtain the initial cliff signal strength threshold.

[0101] The initial cliff signal strength threshold is a standard value preset at the factory for the robot. This value is derived from extensive experimental data and analysis of common scenarios, and is used to determine whether there is a cliff ahead under normal circumstances. For example, it might be set that if the effective cliff signal strength exceeds this initial threshold, it is preliminarily considered that a cliff may exist.

[0102] Step 2: When a cliff height setting message is received, read the actual cliff height value carried in the cliff height setting message.

[0103] The generation of the cliff height setting message depends on the user selecting a setting mode and placing the robot at the cliff's drop position. In actual user applications, users can operate the robot using the pre-installed human-machine interface / buttons or a mobile app. For example, the user enters the calibration threshold state through the app or interface, at which point the robot waits for the user to input relevant information. When the user places the robot at a position slightly higher than the actual cliff (e.g., placing the robot at 61 / 62mm if there is a 60mm height difference in the user's home), the user's interaction triggers the generation of the cliff height setting message, which carries the actual cliff height value corresponding to the user's location.

[0104] Step 3: Correct the initial cliff signal strength threshold based on the actual cliff height to obtain the preset cliff signal strength threshold; wherein, the cliff height setting message is generated when the operation robot is placed at the cliff drop position in the user selection setting mode.

[0105] After receiving the cliff height setting message and reading the actual cliff height value, the system will correct the initial cliff signal strength threshold according to a preset algorithm or rule. For example, the initial threshold may be adjusted according to a certain proportion or a specific functional relationship based on the difference between the actual cliff height value and the factory-set cliff height (e.g., 50mm). Through this correction operation, a preset cliff signal strength threshold that better reflects the actual situation of the current user environment is obtained.

[0106] In one embodiment, such as Figure 3 As shown, the above-mentioned cliff detection method for robots also includes:

[0107] S800: If the effective cliff signal strength is not greater than the preset cliff signal strength threshold, it is determined that there is no cliff drop in front of the operation.

[0108] When the cliff detection signal strength is not greater than the preset cliff signal strength threshold, it indicates that the reflected signal characteristics in front of the robot are consistent with the signal characteristics when there is no cliff drop. This determination step clearly tells the robot that there is no cliff drop in front of it, providing an accurate basis for subsequent operational decisions and preventing the robot from taking unnecessary evasive actions due to misjudgment, which would affect normal operational efficiency.

[0109] S900: After waiting for the preset time, return to S200.

[0110] The preset time can be set according to actual needs, such as 30 seconds, 1 minute, 3 minutes, 5 minutes, etc. After waiting for the preset time, the infrared reflection signal is reacquired, realizing dynamic monitoring of the environment in front of the operation. Since the working environment may change at any time, for example, obstacles or small drops may suddenly appear in places that were originally without cliff drops. By periodically reacquiring signals, these changes can be detected in a timely manner, ensuring that the robot can make correct decisions based on the latest environmental information, thus ensuring the safety and reliability of the operation.

[0111] To illustrate the technical solution of this application in detail, the following will use a specific application example, taking a sweeping robot as the working robot and 940nm infrared light as the first wavelength and 850nm infrared light as the second wavelength, to illustrate the technical solution of this application in detail.

[0112] The implementation process is as follows: illumination detection → compensation calculation → cliff determination.

[0113] The core technology principle is: by using two infrared tubes that emit infrared light of different wavelengths to emit infrared light outwards, receiving the signal reflected back from the bottom surface, and then performing compensation calculations on the signal, the calculated value is used to determine whether there is a cliff in front of the body.

[0114] The illumination detection employs two infrared emitting diodes and their corresponding receiving diodes, along with an ambient light sensor: the main infrared emitting diode has a wavelength of 940nm, the auxiliary infrared emitting diode has a wavelength of 850nm, and the receiving diode is used to receive the reflected signal. The ambient light sensor monitors the ambient light intensity.

[0115] The main infrared emitter has strong resistance to visible light interference and is used for the primary detection band. This band has low energy density in sunlight and is less affected by visible light interference. The auxiliary infrared emitter has high emissivity and is used for ambient light compensation. This band is sensitive to sunlight, and an algorithm distinguishes its true reflection from ambient light. The ambient light sensor is used to monitor ambient light intensity in real time. Strong light (such as direct sunlight or indoor lighting) will simultaneously amplify the reflection signals of all bands, causing drastic fluctuations in the absolute value of a single-band sensor (e.g., ground reflection value from 100 to 500, cliff reflection value from 5 to 250), rendering the threshold invalid. Let the reflection signal intensities of the two bands (first reflection signal intensity and second reflection signal intensity) be I... 940 and I 850 Since the influence of ambient light on the two bands is similar, the ratio of the two bands is not affected by changes in light intensity, but depends only on the spectral characteristics of the material itself.

[0116] Algorithm section: The effective cliff signal is calculated in real time based on the following formula, using the dual-band ratio method (dual-band ratio = reflected signal intensity of band A / reflected signal intensity of band B, mathematical expression: R = ρA / ρB, ρA = reflected signal intensity of band A (i.e., the first reflected signal intensity), ρB = reflected signal intensity of band B (reference signal intensity) to calculate the effective cliff signal. The signals detected by the two infrared sensors (represented as ρA and ρB in the formula) are compared. Because I 850 It is quite sensitive to sunlight, so the corresponding amount of sunlight needs to be subtracted. This involves calculating the infrared content reflected back from the transmitter to reduce interference from sunlight. Simultaneously, to prevent the denominator from approaching zero and resulting in an infinitely large calculation, a suppression constant needs to be added. Therefore, the formula for calculating the final effective cliff signal is as follows:

[0117]

[0118] In the formula, I 940 : Signal strength received at 940nm wavelength; I 850 : Received signal strength at 850nm wavelength; k: Compensation coefficient dynamically calculated based on ambient light intensity; I env Parameters detected by the ambient light sensor. Noise suppression constant: This avoids a denominator of 0, which would result in an infinitely large result. The 850nm wavelength is close to the visible light band, therefore ambient light has a significant impact (it can misclassify visible light as this band). Ground sunlight irradiance at 850nm accounts for 10-20% of total solar radiation; dynamic supplementation removes the influence of ambient light. In low-light environments (illuminance <500 lux), ambient light interference is minimal (visible light radiation intensity <50 lux, accounting for 10%). The infrared receiver tube detects 850nm signals (I... 850 The detection is within the linear response range. In this case, the compensation coefficient k needs to be set to the minimum value of 0.1 to avoid overcompensation of the infrared signal.

[0119] Dynamic compensation logic: Based on the visible light intensity measured by the ambient light sensor, the content of 850nm infrared light in ambient light is typically 5%~15%. When the ambient light intensity < 500, k = 0.05, indicating a low-light mode; when 500 ≤ k ≤ 2500, k = 0.025 + 0.00005 * I env Dynamic adjustment reduces the impact of ambient light; when k > 2500, k = 0.15, indicating entry into strong light mode; through dynamic compensation, it ensures that the received 850nm band signal is the signal emitted by the transmitter tube, reducing interference from ambient light. The value of I is mainly based on 850 The selection is based on the principle that "when the signal amplitude is less than twice the noise standard deviation, a compensation term (usually 10%–20% of the signal mean) needs to be added to the denominator." For example, when I... 850 ≈0.1, then ≥0.01, to avoid the denominator being 0, which would cause the data to grow indefinitely.

[0120] Cliff detection criteria: When the effective cliff signal > the set cliff signal, the system determines that there is a cliff ahead. The set cliff signal is determined based on the cliff height set by the product itself (e.g., test data at a height of 50mm under normal lighting conditions). Cliff detection I 940 As the molecular weight decreases, the effective cliff signal increases; when there is no cliff, I... 940 Normal, the molecules remain basically unchanged, and the effective cliff signal remains basically unchanged.

[0121] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0122] Based on the same inventive concept, this application also provides a cliff detection device for a work robot to implement the cliff detection method for work robots described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the cliff detection device for work robots provided below can be found in the limitations of the cliff detection method for work robots described above, and will not be repeated here.

[0123] In one embodiment, such as Figure 4 As shown, a cliff detection device for a work robot is provided, comprising:

[0124] The robot is equipped with a first infrared emitter and a second infrared emitter. The first infrared emitter emits infrared light of a first wavelength, and the second infrared emitter emits infrared light of a second wavelength. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower limit, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper limit.

[0125] The aforementioned cliff detection device for the robotic operation includes:

[0126] The receiving module 200 is used to acquire the first reflected signal corresponding to the first wavelength infrared light and the second reflected signal corresponding to the second wavelength infrared light;

[0127] The intensity detection module 400 is used to obtain the effective cliff signal intensity based on the ratio of the first reflected signal and the second reflected signal;

[0128] The processing module 600 is used to determine that there is a cliff drop ahead when the effective cliff signal strength is greater than the preset cliff signal strength threshold.

[0129] In one embodiment, the intensity detection module 400 is further configured to acquire ambient light intensity; compensate the signal intensity of the second reflected signal based on the ambient light intensity to obtain a reference signal intensity; and calculate the ratio of the signal intensity of the first reflected signal to the reference signal intensity to obtain the effective cliff signal intensity.

[0130] In one embodiment, the intensity detection module 400 is further configured to obtain a compensation coefficient based on the ambient light intensity; obtain a light intensity correction amount based on the ambient light intensity and the compensation coefficient; obtain a noise suppression constant; and obtain a reference signal intensity based on the signal intensity of the second reflected signal, the light intensity correction amount, and the noise suppression constant.

[0131] In one embodiment, the intensity detection module 400 is further configured to compare the ambient light intensity with a preset reference ambient light intensity range threshold; if the ambient light intensity is greater than the upper limit of the preset reference ambient light intensity range threshold, then the compensation coefficient is determined to be a first compensation value; if the ambient light intensity is not greater than the upper limit of the preset reference ambient light intensity range threshold and not less than the lower limit of the preset reference ambient light intensity range threshold, then the compensation coefficient is determined to be the sum of a second compensation value and a light intensity correction amount, wherein the light intensity correction amount is positively correlated with the ambient light intensity; if the ambient light intensity is less than the lower limit of the preset reference ambient light intensity range threshold, then the compensation coefficient is determined to be a second compensation value; wherein the first compensation value, the sum of the second compensation value and the light intensity correction amount, and the second compensation value decrease sequentially.

[0132] In one embodiment, the processing module 600 is further configured to obtain an initial cliff signal strength threshold; when a cliff height setting message is received, read the actual cliff height value carried in the cliff height setting message; and correct the initial cliff signal strength threshold based on the actual cliff height value to obtain a preset cliff signal strength threshold; wherein the cliff height setting message is generated when the operation robot is placed at the cliff drop position in the user selection setting mode.

[0133] In one embodiment, the processing module 600 is configured to determine that there is no cliff drop ahead if the effective cliff signal strength is not greater than a preset cliff signal strength threshold; and after waiting for a preset time, control the receiving module 200 to re-execute the operation of acquiring the first reflected signal corresponding to the first wavelength infrared light and the second reflected signal corresponding to the second wavelength infrared light.

[0134] In one embodiment, the first wavelength infrared light includes infrared light with a wavelength of 940nm ± 10nm; the second wavelength infrared light includes infrared light with a wavelength of 850nm ± 10nm.

[0135] Each module in the aforementioned cliff detection robot can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0136] In addition, this application also provides a robot, including a first infrared emitter, a second infrared emitter, and a controller. The first infrared emitter is used to emit a first wavelength infrared light, and the second infrared emitter is used to emit a second wavelength infrared light. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower sensitivity limit, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper sensitivity limit. The controller uses the detection method described above to perform cliff detection.

[0137] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a cliff detection method for a work robot. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0138] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0139] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described cliff detection method for a work robot.

[0140] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described cliff detection method for a work robot.

[0141] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described cliff detection method for a work robot.

[0142] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0143] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0144] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A cliff detection method for a work robot, characterized in that, The working robot is equipped with a first infrared emitter and a second infrared emitter. The first infrared emitter is used to emit infrared light of a first wavelength, and the second infrared emitter is used to emit infrared light of a second wavelength. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower limit value, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper limit value. The cliff detection method for the operating robot includes: Acquire the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light; The effective cliff signal strength is obtained based on the ratio of the first reflected signal to the second reflected signal. If the effective cliff signal strength is greater than the preset cliff signal strength threshold, then it is determined that there is a cliff drop ahead of the work site.

2. The method according to claim 1, characterized in that, Obtaining the effective cliff signal strength based on the ratio of the first reflected signal to the second reflected signal includes: Obtain ambient light intensity; The signal strength of the second reflected signal is compensated based on the ambient light intensity to obtain the reference signal strength; The effective cliff signal strength is obtained by calculating the ratio of the signal strength of the first reflected signal to the signal strength of the reference signal.

3. The method according to claim 2, characterized in that, The step of compensating the signal strength of the second reflected signal based on the ambient light intensity to obtain the reference signal strength includes: The compensation coefficient is obtained based on the ambient light intensity. Based on the ambient light intensity and the compensation coefficient, the light intensity correction amount is obtained; Obtain the noise suppression constant; The reference signal strength is obtained based on the signal strength of the second reflected signal, the light intensity correction amount, and the noise suppression constant.

4. The method according to claim 3, characterized in that, The process of obtaining the compensation coefficient based on the ambient light intensity includes: Compare the ambient light intensity with a preset benchmark ambient light intensity range threshold; If the ambient light intensity is greater than the upper limit of the preset benchmark ambient light intensity range threshold, then the compensation coefficient is determined to be the first compensation value; If the ambient light intensity is not greater than the upper limit of the preset benchmark ambient light intensity range threshold and not less than the lower limit of the preset benchmark ambient light intensity range threshold, then the compensation coefficient is determined to be the sum of the second compensation value and the light intensity correction amount, wherein the light intensity correction amount is positively correlated with the ambient light intensity. If the ambient light intensity is less than the lower limit of the preset reference ambient light intensity range threshold, then the compensation coefficient is determined to be the second compensation value; Among them, the sum of the first compensation value, the second compensation value and the light intensity correction amount, and the second compensation value decrease sequentially.

5. The method according to claim 1, characterized in that, Before determining that there is a cliff ahead if the effective cliff signal strength is greater than a preset cliff signal strength threshold, the method further includes: Obtain the initial cliff signal strength threshold; When a cliff height setting message is received, the actual cliff height value carried in the cliff height setting message is read. The initial cliff signal strength threshold is corrected based on the actual cliff height to obtain the preset cliff signal strength threshold. The cliff height setting message is generated when the robot is placed at the cliff drop position in the user selection setting mode.

6. The method according to claim 1, characterized in that, The method further includes: If the effective cliff signal strength is not greater than the preset cliff signal strength threshold, it is determined that there is no cliff drop in front of the work area. After waiting for a preset time, return to the step of obtaining the first reflection signal corresponding to the first wavelength infrared light and the second reflection signal corresponding to the second wavelength infrared light.

7. The method according to claim 1, characterized in that, The first wavelength infrared light includes infrared light with a wavelength of 940nm±10nm; the second wavelength infrared light includes infrared light with a wavelength of 850nm±10nm.

8. A cliff detection device for a work robot, characterized in that, The working robot is equipped with a first infrared emitter and a second infrared emitter. The first infrared emitter is used to emit infrared light of a first wavelength, and the second infrared emitter is used to emit infrared light of a second wavelength. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower limit value, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper limit value. The cliff detection device for the operating robot includes: The receiving module is used to acquire the first reflected signal corresponding to the first wavelength infrared light and the second reflected signal corresponding to the second wavelength infrared light; The intensity detection module is used to obtain the effective cliff signal intensity based on the ratio of the first reflected signal to the second reflected signal; The processing module is used to determine that there is a cliff drop ahead when the effective cliff signal strength is greater than a preset cliff signal strength threshold.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A work robot, characterized in that, The device includes a first infrared emitting tube, a second infrared emitting tube, and a controller. The first infrared emitting tube is used to emit infrared light of a first wavelength, and the second infrared emitting tube is used to emit infrared light of a second wavelength. The first wavelength infrared light is infrared light with a sensitivity to sunlight not greater than a preset lower sensitivity limit, and the second wavelength infrared light is infrared light with a sensitivity to sunlight not less than a preset upper sensitivity limit. The controller performs cliff detection using the method described in any one of claims 1 to 7.

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