System and method for utilizing SWIR detection in a vacuum cleaner

Abstract

A system and method for utilizing SWIR sensing in an autonomous vacuum cleaner includes a first illumination source for emitting radiation at a first wavelength within the SWIR towards a field of view (FOV), and a receiver that operates to acquire SWIR image data based on radiation reflected from elements disposed within the FOV and, based on the SWIR image data, determines the presence of an aqueous liquid within the FOV.

Description

Technical Field

[0001] This disclosure generally relates to cleaning machines. More specifically, this disclosure relates to automated cleaning machines having short range infra-red (SWIR) sensing capabilities.

[0002] Cross - reference to related applications This application claims priority to U.S. Provisional Patent Application No. 63 / 345,594, filed May 25, 2022, the entire disclosure of which is incorporated herein by reference.

Background Art

[0003] Automated or semi - automated cleaning machines, such as robotic devices, are commonly used in residential, public, and industrial environments. Such automated or semi - automated devices can include vacuum cleaners, lawn mowers, robotic mops, floor sweepers, window cleaners, and other devices.

[0004] In recent years, there has been rapid progress in the field of autonomous or robotic vacuum cleaners, particularly vacuum cleaners and floor cleaners, with the primary objective being to autonomously navigate the user's home while cleaning floors and / or carpets. To operate autonomously or with minimal external control while navigating an area, autonomous devices can generally utilize mapping, localization, object recognition, and path planning methods. Some of the methods used may involve vision systems that can capture still or moving images of the surrounding area. However, such systems can suffer from low-light conditions and poor image quality, and may have significant problems identifying certain obstacles or conditions, such as liquid splashes on the floor. Improved methods and systems are needed to overcome the shortcomings of conventional autonomous vacuum cleaners that use conventional vision systems operating in the visible spectrum. [Overview of the project]

[0005] Some embodiments may include an autonomous cleaning system and a method for utilizing SWIR sensing in autonomous cleaning. The system includes a first illumination source for emitting radiation at a first wavelength in the short-wave infrared range (SWIR) toward a field of view (FOV), a receiver operating within the SWIR for acquiring SWIR image data based on radiation reflected from elements placed within the FOV, and determining the presence of aqueous liquid within the FOV based on the SWIR image data.

[0006] Some embodiments include a second illumination source for emitting radiation at a second wavelength in the SWIR toward a target in the FOV, and determining the spectral characteristics of the target based on the absorption of the target at the first wavelength and the absorption of the target at the second wavelength. It works in this way,

[0007] According to some embodiments of the present disclosure, the second illumination source is for emitting radiation toward the target by emitting radiation at the second wavelength in the SWIR toward the second FOV contained within the first FOV.

[0008] According to some embodiments of the present disclosure, the second illuminating source may include a low-power illuminating source.

[0009] According to some embodiments of the present disclosure, the receiver may comprise one or more germanium (Ge) photodiodes (PDs).

[0010] According to some embodiments of the present disclosure, the first illumination source may include a laser source.

[0011] According to some embodiments of the present disclosure, the first wavelength may be between 1300 nm and 1400 nm.

[0012] According to some embodiments of the present disclosure, the second illumination source may include a light-emitting diode (LED).

[0013] According to some embodiments of this disclosure, the second wavelength is between 800 nm and 1000 nm.

[0014] Some embodiments may further include a third illumination source for emitting radiation at a third wavelength in the SWIR toward the target within the FOV, and the processor determines the spectral characteristics of the target based on the absorption of the target at the first wavelength, the absorption of the target at the second wavelength, and the absorption of the target at the third wavelength. It works in this way, [Brief explanation of the drawing]

[0015] The subject matter deemed to be disclosed herein is closely identified and explicitly claimed in the conclusion section of this specification. However, this disclosure, along with its purposes, features, and advantages, as well as both the organization and method of operation, can be best understood by referring to the following detailed description when read in conjunction with the accompanying drawings. [Figure 1] Figure 1 is a schematic diagram of the components of an exemplary and non-limiting autonomous cleaning system architecture according to an embodiment of the present disclosure. [Figure 2A] Figure 2A is a schematic diagram of an exemplary autonomous cleaning system according to an embodiment of the present disclosure. [Figure 2B] Figure 2B is a schematic diagram of an exemplary autonomous cleaning system according to an embodiment of the present disclosure. [Figure 2C] Figure 2C is a schematic diagram of an exemplary autonomous cleaning system according to an embodiment of the present disclosure. [Figure 3] Figure 3 is a flowchart relating to a method for using a SWIR vision system in an autonomous cleaning system according to some embodiments of the present disclosure. [Figure 4] Figure 4 illustrates the timing of three different detection signals arriving from the same direction within the FOV, according to an embodiment of the present disclosure. [Figure 5] Figure 5 is a block diagram depicting a computing device that may be included in an embodiment of a system for utilizing SWIR sensing in a vacuum cleaner, according to some embodiments of the present disclosure.

[0016] For the sake of simplicity and clarity, it should be understood that the elements shown in the diagrams are not necessarily drawn to scale. For example, the dimensions of some elements may be exaggerated relative to others for clarity. Furthermore, where deemed appropriate, reference numbers may be repeated between diagrams to indicate corresponding or similar elements. [Modes for carrying out the invention]

[0017] Those skilled in the art will recognize that this disclosure can be embodied in other specific forms without departing from its spirit or essential features. Accordingly, the embodiments described herein should be considered illustrative in all respects, rather than limiting the disclosure described herein. The scope of this disclosure is therefore indicated by the appended claims rather than by the foregoing description, and all modifications that fall within the meaning and scope of the equivalents of the claims are therefore intended to be encompassed therein.

[0018] The following detailed description includes numerous specific details to provide a complete understanding of the disclosure. However, it will be understood by those skilled in the art that the disclosure can be implemented without these specific details. In other instances, well-known methods, procedures, and components are not described in detail so as not to obscure the disclosure. Some features or elements described in relation to one embodiment may be combined with features or elements described in relation to other embodiments. For clarity, discussions of identical or similar features or elements may not be repeated.

[0019] The embodiments described in this specification are not limited in this regard. For example, descriptions using terms such as "processing", "computing", "calculating", "determining", "establishing", "analyzing", "checking" refer to operations and / or conversions of data represented as physical (e.g., electronic) quantities in a computer's registers and / or memory into other data similarly represented as physical quantities in the computer's registers and / or memory, which can be operations and / or processes performed by a computer, a computing platform, a computing system, or other electronic computing devices, or instructions that can store commands to cause a processor to execute an operation and / or process, and may refer to operations and / or processes related to a non - transitory storage medium of other information.

[0020] The embodiments described in this specification are not limited in this regard. However, the terms "plurality" and "a plurality" as used in this specification may include, for example, "multiple" or "two or more". The term "plurality" can be used throughout this specification to describe two or more components, devices, elements, units, parameters, etc. As used in this specification, the term "set" may include one or more items.

[0021] Unless explicitly stated otherwise, embodiments of the methods described in this specification are not restricted to a particular order or sequence. Additionally, some embodiments of the methods described, or some of their elements, can occur, or be executed, simultaneously, at the same time, or concurrently.

[0022] The embodiments described in this specification can overcome the drawbacks of a general vision system implemented in an autonomous vacuum cleaner. An autonomous or robotic vacuum cleaner using a camera or sensor that detects visible light can utilize light wavelengths from 400 to 700 nanometers (nm). Such cameras or sensors have some drawbacks as they may not be able to detect certain obstacles on the floor or area being cleaned. For example, liquids such as water, cleaning solution, urine, or any other liquid may not be detected by a visible camera due to the transparency of the liquid. An autonomous vacuum cleaner utilizing a SWIR imaging system can easily detect and identify liquids, such as liquids containing water. The detection of water-based liquids can be based on specific properties of water. For example, water absorbs wavelengths in the area of 1450 nm and thus returns a dark area in the captured image. Another advantage of a vacuum cleaner utilizing a SWIR imaging system can include specific material detection. Material detection can be useful for identifying the material of the area being cleaned, such as a wooden floor, parquet floor, marble floor, ceramic tile floor, etc. As described in the embodiments of the present disclosure, utilizing a SWIR imaging system in a vacuum cleaner can improve the current system and overcome significant drawbacks of vacuum cleaners known in the art.

[0023] FIG. 1 shows a schematic diagram of the components of an architecture according to one exemplary and non-limiting autonomous vacuum cleaning system in accordance with an embodiment of the present disclosure. The autonomous vacuum cleaning system 100 can include a short-wave infrared (SWIR) imaging system 110, a control system 120, and a processor 130. As used herein, the autonomous vacuum cleaning system 100, also referred to herein as "system 100", can be any autonomous or semi-autonomous vacuum cleaner. For example, it can be a mobile robot, a robotic vacuum cleaner, an autonomous floor cleaner, a floor-running sweeper, or any other autonomous or semi-autonomous cleaning machine, sweeper, scrubber, vacuum cleaner, or any other cleaning machine.

[0024] The SWIR imaging system 110 may include one or more illumination sources 112, one or more SWIR receivers or sensors 111, and optical systems 113. The control system 120 may include an imaging system control unit 121, an analysis unit 122, and a navigation unit 123. A processor 130 may be connected to the SWIR imaging system 110 and the control system 120. In some embodiments of this disclosure, the processor 130 may be implemented as an internal processor in each of the control system 120 and / or the imaging system 110, or as an external processor, for example, outside of system 100. The SWIR imaging system 110 may detect light reflected from the field of view and operate to provide one or more images of the field of view or a portion thereof based on the light reaching the imaging system 110.

[0025] Illumination sources 112 may include one or more illumination sources for illuminating or emitting radiation in the SWIR band toward an object, area, or scene, all referred to herein as targets 140. The term “target” refers to any object, area, subject, element, surface, content, and / or anything contained within or positioned in the FOV of the imaging sensor, including solid, liquid, flexible, and rigid objects. Emitted illumination from system 100 is shown 141, and illumination reflected from target 140 toward system 100 is shown 142. Some of the emitted radiation 141 may also be reflected, deflected, or absorbed in other directions by target 140 (not shown).

[0026] The illumination source 112 may include any light source or illumination source that can provide a certain level of illumination to the area surrounding the system 100. Any suitable type of illumination source 112, such as a light-emitting diode (LED), laser diode, quasi-continuous wave (QCW) laser, vertical-cavity surface-emitting laser (VCSEL), Q-switched (QS) laser, etc., may be used. Any other illumination source, or any combination of illumination sources, may be included in the illumination source 112. The illumination source 112 may emit light of any bandwidth that can be detected by the receiver 111 to generate an image. For example, the light 141 emitted by the illumination source 112 may be in the SWIR area of ​​the electromagnetic spectrum.

[0027] The illumination source 112 may include a first illumination source for emitting radiation toward the FOV at a first wavelength in the SWIR, for example, a wavelength in the range of 1300 to 1500 nm. For example, by emitting radiation or transmitting illumination at a specific wavelength, e.g., 1450 nm or near 1450 nm, it may be possible to detect, observe, identify, or monitor the presence of water-based liquid in the FOV as water-absorbed radiation at the 1450 nm wavelength. SWIR image data may be acquired by the receiver 111 based on radiation reflected from the target 140. Based on the SWIR image data, the presence of water-based liquid in the FOV may be determined by identifying dark areas in the image. For example, dark or black areas in the SWIR image may indicate the presence of water, water-based liquid, and any material containing water.

[0028] In embodiments of this disclosure, the illumination source 112 may operate close to 1400 nm in the SWIR spectrum, also known as the “solar blind region”, where the SWIR becomes resilient to ambient noise from the sun. Illumination close to 1400 nm, for example between 1300 nm and 1500 nm, can result in a higher signal-to-noise ratio (SNR) and an overall improvement in image quality under common low-visibility scenarios such as glare, rain, smoke, and fog. This may enable the SWIR camera 111 to produce high-resolution images and an increased detection range.

[0029] The illumination source 112 may further include a second illumination source for emitting radiation at a second wavelength in the SWIR toward a target within the FOV or toward a second FOV contained within the first FOV. The second wavelength is predetermined to be different from the first wavelength (illuminated by the first illumination source) and enables the classification or detection of materials of surfaces, planes, objects, obstacles, or any other targets, areas, objects, or surfaces within the FOV, according to embodiments of the present disclosure. For example, the first illumination source may be a VCSEL emitting illumination at 1450 nm, while the second illumination source may be an LED emitting illumination at 940 nm. Any additional illumination sources on top of the first illumination source may be required for accurate material classification based on spectral analysis.

[0030] The receiver 111 may include one or more SWIR sensors or detectors for receiving and collecting radiation reflected from the target 140 and / or from the illuminated FOV. The receiver 111 may operate within the SWIR to acquire SWIR image data based on radiation reflected from elements, regions, or areas located within the illuminated FOV. The receiver 111 may generate or produce electrical signals representing imagery of the illuminated FOV in response to detected electromagnetic radiation. The receiver 111 may be capable of capturing images of surrounding, neighboring, or near areas with respect to the position of the autonomous cleaning system 100. For example, the receiver 111 may be a forward-facing camera for capturing images in the forward direction of travel of the autonomous cleaning system 100, or may be implemented as such. In some embodiments, processing of the output of the receiver 111 may be performed by the processor 130 and, additionally or alternatively, by an external processor (not shown).

[0031] The receiver 111 and / or the illumination source 112 may utilize an optical system 113. The optical system 113 may include one or more optical elements, such as mirrors, lenses, diffusers, or any other elements to improve, enhance, and / or support the receiver 111 and / or the illumination source 112. For example, the optical system 113 may be arranged to collect, concentrate, and optionally filter reflected radiation 142, and to focus the electromagnetic radiation onto the focal plane of the receiver 111.

[0032] According to some embodiments of this disclosure, the receiver 111 may include a plurality of photodetector devices, such as a photodetector array or “PDA”, which may include a plurality of photosites. Each photosite includes one or more photodiodes for detecting incoming light and a capacitance for storing the charge supplied by the photodiodes. Hereinafter, “photosite” is often replaced with the acronym “PS”. The term “photosite” refers to a single sensor element relating to an array of sensors. Each PS may include one or more photodiodes. A PS may also include several circuits or additional components in addition to the photodiodes.

[0033] According to some embodiments of this disclosure, the receiver 111 may include a plurality of germanium (Ge) photodetectors (PDs) that operate to detect reflected SWIR radiation. In some embodiments, the receiver 111 may include a SWIR focal plane array (FPA), while the plurality of Ge PDs may be part of or form part of the SWIR FPA. The receiver 111 may generate an electrical signal for each of the plurality of Ge PDs representing the amount of incident SWIR light within its detectable spectral range. The amount of light detected in the receiver 111 may include the amount of SWIR radiation reflected from the target 140, and may also include additional SWIR light arriving, for example, from sunlight or an external light source.

[0034] The term "Ge PD" refers to any photodiode (PD) in which light-induced excitation of electrons (later detectable as a photocurrent) occurs within Ge, within a Ge alloy (e.g., SiGe), or at the interface between Ge (or a Ge alloy) and another material (e.g., silicon, SiGe). Specifically, the term "Ge PD" refers to both pure Ge PD and Ge-silicon PD. When Ge PDs containing both Ge and silicon are used, different concentrations of germanium may be used. For example, the relative proportion of Ge in a Ge PD (whether alloyed with or adjacent to silicon) may range from 5% to 99%. For example, the relative proportion of Ge in a Ge PD may be between 15% and 40%. Note that non-silicon materials such as aluminum, nickel, silicides, or any other suitable material may also be part of a Ge PD. In some implementations of this disclosure, Ge PD may be pure Ge PD (containing more than 99.0% Ge).

[0035] In some embodiments of this disclosure, the receiver 111 may be implemented as a PD array manufactured on a single chip. The PDs, for example, Ge PDs, may be configured in any suitable arrangement, such as a rectangular matrix (rows and columns of Ge PDs), honeycomb tiling, and even more irregular configurations. Preferably, the number of Ge PDs in the receiver 111 can enable the generation of high-resolution images. For example, the number of PDs may be on the order of 1 megapixel, 10 megapixels, or more.

[0036] The exemplary embodiments disclosed herein relate to a system and method for high SNR active SWIR imaging using a receiver comprising a Ge-based PD. Compared with InGaAs technology, the main advantage of Ge receiver technology is its compatibility with CMOS processes, enabling the manufacture of receivers as part of a CMOS production line. For example, Ge PDs can be integrated into a CMOS process by growing a Ge epilayer on a silicon (Si) substrate, such as in Si photonics. Ge PDs are therefore also more cost-effective than equivalent InGaAs optical receivers.

[0037] The control system 120 can control the operation of the imaging system 110 by the imaging system control unit 121. The imaging system control unit 121 can control the operation of the receiver 111, the illumination source 112, and the optical system 113. The control unit 121 can trigger the activation of the illumination source 112 in a predetermined manner and in accordance with the operation of the receiver 111. For example, in some embodiments of the present disclosure, the control unit 121 can trigger the illumination source to operate only during the time period in which the receiver 111 is open for detection of reflected light. In some embodiments of the present disclosure, the control unit 121 can trigger the illumination source 112 to operate continuously in pulses or in any other way during a specific time period.

[0038] According to some embodiments of the present disclosure, the control unit 121 may be configured to control the startup of the receiver 111 for relatively short integration times, thereby limiting the effect of accumulated dark current noise on the quality of the generated signal. For example, the control unit 121 may operate to control the startup of the receiver 111 during an integration time in which the accumulated dark current noise cannot exceed the readout noise, which is independent of the integration time.

[0039] The control system 120 can control and / or perform the analysis of imaging data by the analysis unit 122. The analysis unit 122 may be connected to the imaging system 110 and, specifically, may receive information from the receiver 111. The analysis unit 122 may receive electrical signals generated in response to electromagnetic radiation detected by the receiver 111. The received signals represent an image of the illuminated scene within the FOV. In some embodiments of this disclosure, the signals detected by the receiver 111 may be processed by the analysis unit 122 and / or transferred via the analysis unit 122 to the processor 130 for processing into a SWIR image of the target 140 or the illuminated FOV. The analysis unit 122 may further process the electrical signals generated in response to electromagnetic radiation to detect or observe the target 140, perform spectral analysis of the target 140, determine the spectral characteristics of the target 140, and / or determine the presence of one or more materials contained in the target 140.

[0040] In accordance with some embodiments of the present disclosure, spectral analysis may be performed based on the absorption of target 140 at a first wavelength and the absorption of target 140 at a second wavelength. Target 140 may be illuminated at two different SWIR wavelengths. For example, a first illuminator may emit radiation at a first wavelength, and a second illuminator may emit radiation at a second wavelength different from the first wavelength. Based on the absorption of target 140 at a first wavelength and the absorption of target 140 at a second wavelength, spectral analysis of target 140 is performed, and the spectral characteristics of target 140 are determined, or may be determined.

[0041] According to some embodiments of the present disclosure, the illumination source 112 may emit illumination at a specific wavelength, which may be selected to enable the detection, observation, or determination of the presence of a particular material, for example, water or any liquid containing water. For example, since water has a prominent absorption peak around the wavelength of 1450 nm, the illumination source 112 may emit radiation at a wavelength of 1400 nm or 1450 nm.

[0042] The control system 120 may further control the navigation of the cleaning system 100 by the navigation unit 123. According to some embodiments of this disclosure, based on the SWIR image of the generated FOV, the analysis unit 122 may detect or observe a target 140. For example, any obstacle or element detected within the FOV may be identified and used to control the navigation of the cleaning system 100. The imaging system 110 may include additional types of sensors to provide the cleaning system 100 with information about its surrounding environment for navigation purposes. For example, the imaging system 110 may include one or more position-sensing devices, one or more physical contact sensors, an infrared (IR) sensor, one or more cameras or sensors that detect visible light, or any other type of sensor. The navigation unit 123 may receive signals from any of the sensors of the imaging system 110 and adjust the position and trajectory of the cleaning system 100 based on the received signals.

[0043] All information and data collected by the imaging system 110 can be supplied to the control system 120, and specifically to the analysis unit 122 and the navigation unit 123. The analysis unit 122 receives the images captured by the imaging system 110 and can analyze the images to find significant features or landmark features within the FOV, for example, the area surrounding the cleaning system 100. Significant features or landmark features may include high-contrast features that can be detected in the image, such as spilled water, table legs, shoes, cables, carpets, or any other objects. The detected landmark features can be used by the navigation unit 123 to triangulate and determine the position of the cleaning system 100 in the local environment, and to avoid obstacles without contact. For example, by identifying a puddle of spilled liquid, such as water, soapy water, urine, or any other aqueous liquid, the cleaning system 100 can avoid driving into the liquid and pass around it, etc.

[0044] Figures 2A, 2B, and 2C are schematic diagrams relating to an exemplary autonomous cleaning system according to embodiments of the present disclosure. Figure 2A is a top view of the cleaning system 100, and Figures 2B and 2C are side views of the cleaning system 100. The cleaning system 100 is the cleaning system 100 of Figure 1, and may include or utilize it. The cleaning system 100 may include a body 200, a vacuum cleaner head 213, and other components that enable the movement of the system 100, such as a motor, a transaction unit, a power supply unit, a battery, one or more wheels, and / or any other elements (not shown) necessary for movement and cleaning. It should be understood by those skilled in the art that the shapes and designs of the body 200 and any other components shown in Figures 2A-2C serve as exemplary designs, and the cleaning system 100 may have any shape, design, structure, or appearance.

[0045] In accordance with embodiments of this disclosure, the main unit 200 may include a camera 210 for capturing images of the area surrounding the cleaning system 100. The camera 210 may include the imaging system 110 of Figure 1. The camera 210 may be any type of camera, including the SWIR device or receiver 111 of Figure 1. The control system 120 of Figure 1 may be embodied in software and electronics contained within the cleaning system 100. It is capable of processing images captured by the camera 210, enabling the cleaning system 100 to understand, interpret, and autonomously navigate the local environment.

[0046] The illustrative diagrams in Figures 2A and 2B show an FOV 220 having a horizontal FOV 205 of 45 degrees and a vertical FOV 223 of 5 degrees. A first illuminator included in the cleaning system 100 can illuminate an area that can be positioned at a minimum distance 221, e.g., 25 centimeters (cm) from the cleaning system 100, and a maximum distance 222, e.g., 50 cm from the cleaning system 100. The first illuminator may emit illumination at a wavelength between 1300 nm and 1500 nm, e.g., 1450 nm, to identify or detect aqueous liquids on a surface illuminated by the first illuminator, as described in embodiments of the present disclosure.

[0047] In accordance with embodiments of the present disclosure, at least one additional illumination source may be used to illuminate the second FOV 230 at a second wavelength different from the first wavelength (used by the first illumination source) in order to enable high-precision material classification. By illuminating the second FOV 230 within the FOV 220 with the second illumination source at the second wavelength, material classification relating to, for example, a target or area 215 contained in the second FOV 230 can be improved. Since each material has a unique spectral response, illuminating the detected material relating to, for example, target 215 at two or more wavelengths makes it possible to identify, determine, or detect the spectral response of the detected material.

[0048] In embodiments described herein, for each of the additional wavelengths, it may be possible to use a first main illuminator, for example a VCSEL, to illuminate the main FOV 220, and to add one or more additional illuminators having a limited FOV 230. Since the additional illuminators are limited within the main FOV 220 and may require low energy to illuminate a partial FOV 230, this makes it possible to reduce the total power required for the cleaning system 100. Each of the one or more additional illuminators may include, for example, an IR LED that illuminates at a specific, predetermined selected wavelength.

[0049] In accordance with embodiments of this disclosure, the material of target 215, for example, the floor, may be determined based on at least two images of a particular area, target, or space, including the detected material. Since any material has an intrinsic spectral response, for example, an intrinsic spectral reflectance, such intrinsic spectral response may be used to determine the material of the illuminated area. Embodiments described herein may determine the material of a detected target based on at least two images taken at two different wavelengths in a SWIR. For example, a first image may be acquired based on illumination at a first wavelength relating to the main, larger FOV 220, and a second image may be acquired based on illumination at a second wavelength relating to a partial FOV 230 included in FOV 220. Other embodiments may include illuminating the same FOV using two or more wavelengths from two or more illumination sources.

[0050] Embodiments described herein may include illuminating a detected material, e.g., FOV 230, at a first and a second wavelength, and obtaining or identifying two values ​​relating to the reflectance and / or absorption of the detected material (a first value related to the first wavelength and a second value related to the second wavelength). The two values ​​of reflectance and / or absorption may correspond to the spectral response of a particular material that can be identified or determined as the detected material.

[0051] In embodiments of this disclosure, the two values ​​relating to reflectance and / or absorption may be the minimum number of values ​​based on which the spectral response can be determined. However, embodiments described herein may allow any number of additional illuminators emitting radiation at any number of additional wavelengths. For example, a third illuminator may be used to emit radiation at a third wavelength towards a target in the FOV within the SWIR, and the spectral characteristics of the target may be determined based on the target's absorption at a first wavelength, the target's absorption at a second wavelength, and the target's absorption at a third wavelength.

[0052] Refer to Figure 2C, a side view of a cleaning system 100 according to an embodiment of the present disclosure. The system 100 can provide indication of any obstacles that may be located near the main body 200 of the cleaning system 100 or in an area adjacent to the main body 110. This allows the cleaning system 100 to avoid obstacles, such as obstacle 228, without contact. Based on identifying obstacles in the image captured by the imaging system 110, the control system 120 in Figure 1 can generate control signals and command the cleaning system 100 to stop and / or adjust its position and trajectory. This can prevent the cleaning system 100 from causing any damage to itself or to obstacles.

[0053] The illustrative diagram in Figure 2C shows an FOV 220 consisting of a vertical FOV 223 with a 17-degree angle. The first illumination source can illuminate areas that can be positioned at a minimum distance 221, e.g., 25 cm from the cleaning system 100, and a maximum distance 224, e.g., 200 cm from the cleaning system 100. For example, an obstacle 228 positioned within a distance 224 of approximately 150 cm from the cleaning system 100 and having a reflectivity difference of at least 20% from the background may be detected in an image captured by the imaging system 110 of the cleaning system 100.

[0054] For example, in some embodiments of this disclosure, a 17-degree vertical FOV 223 may be selected to enable capturing the floor or other items at a height of 10 cm 227 within a distance 222 of 50 cm from the cleaning system 100. If a single light source can be implemented, for example in the imaging system 110 of Figure 1, the light source may have a Gaussian profile to have a sharp image at a height 227 of 10 cm within a distance 222 of 50 cm from the cleaning system 100. Adding one or more light sources may extend the detection range and total power, respectively.

[0055] Images captured by the imaging system 110 can be analyzed to identify significant features or landmark features within the FOV, such as obstacles 228 that may have high-contrast features, which can be detected in the SWIR image. Detecting obstacles 228 can be used, for example, by the navigation unit 123 in Figure 1 to determine the position of the cleaning system 100 in the local environment and to avoid contact with the obstacles 228, for example, by passing around them.

[0056] Refer to Figure 3. Figure 3 is a flowchart relating to a method for using a SWIR vision system in an autonomous cleaning system according to some embodiments of the present disclosure. One embodiment relating to a method for using a SWIR vision system in an autonomous cleaning system can be carried out, for example, by the exemplary system shown in Figure 1.

[0057] In operation 310, the first illuminator may emit radiation at a first wavelength in the SWIR toward the first FOV. For example, the first illuminator, e.g., illuminator 112 in Figure 1, may emit radiation at a wavelength in the range of 1300 nm to 1500 nm. In some embodiments of the present disclosure, the presence of an aqueous liquid in the first FOV may be detected, observed, identified, or monitored by emitting radiation or transmitting illumination at a specific wavelength, e.g., 1450 nm or a wavelength close to 1450 nm.

[0058] In operation 320, a receiver operating in SWIR may receive reflected radiation from elements located within the FOV, for example, from areas, objects, items, or any other components located within the FOV. The receiver, for example, receiver 112 in Figure 1, may include one or more SWIR sensors or detectors for receiving and collecting radiation reflected from elements located within the FOV. In response to the detected electromagnetic radiation, the receiver may generate an electrical signal representing an image of the illuminated FOV.

[0059] In operation 330, SWIR image data may be acquired based on radiation reflected from elements placed within the FOV. For example, elements placed within the FOV may refer to any object, area, subject, surface, content, and / or anything included in or placed within the FOV of the image sensor, such as solid, liquid, flexible, and rigid objects.

[0060] In operation 340, the presence of aqueous liquids within the FOV can be determined based on SWIR image data. For example, SWIR image data is acquired based on radiation reflected from the illuminated FOV as water absorption radiation at a wavelength of 1450 nm, while the presence of aqueous liquids within the FOV can be determined by identifying dark areas in the image.

[0061] In operation 350, the second illumination source may emit radiation at a second wavelength in the SWIR toward a target within the FOV and / or toward the second FOV which is included in the first FOV. In accordance with embodiments of the present disclosure, the second wavelength is selected to be different from the first wavelength in order to enable the detection and spectral classification of materials relating to surfaces, planes, objects, obstacles, or any other targets within the FOV.

[0062] In operation 360, the spectral characteristics of the target may be determined based on the target's absorption at a first wavelength and the target's absorption at a second wavelength. Based on the target's absorption at the first wavelength and the target's absorption at the second wavelength, a spectral analysis of the target is performed, and the target's spectral characteristics are determined, or may be determined.

[0063] Unless expressly stated otherwise, embodiments of the methods described herein are not restricted to any particular order or sequence. Furthermore, all operations described herein are intended only as examples, and other or different operations may be used. In addition, embodiments of the methods described herein, or some of their elements, may occur or be performed at the same time.

[0064] In some embodiments, the receiver 111 is activated multiple times to create “time slices”, each covering a specific distance range. The image processor 130 may combine these slices to create a single image with greater visual depth, enabling the determination or measurement of distances to objects within the field of view.

[0065] According to some embodiments of this disclosure, different techniques may be used to determine the depth based on the output of one or more photosites, for example, the photosite included in receiver 111 in Figure 1. Embodiments described herein may be used to determine the distance of an object in the field of view of a SWIR electro-optic system, for example, imaging system 110 in Figure 1, as well as other electro-optic systems that are sensitive to other parts of the electromagnetic spectrum.

[0066] According to some embodiments of this disclosure, a method for determining depth may be used by a control system 120 of a cleaning system 100 to provide the cleaning system 100 with information about its surrounding environment, for example, for navigation purposes. For example, the navigation unit 123 in Figure 1 may adjust the position and trajectory of the cleaning system 100 based on depth measurements that may indicate the distance to one or more obstacles, landmarks, or any other elements located in the vicinity of the cleaning system 100.

[0067] Embodiments of the present invention can generate depth images of a scene based on detection by a SWIR electro-optic imaging system (SEI system). The SEI system described herein may be implemented in any of the systems of the cleaning system 100, for example, in the imaging system 110, control system 120, or processor 130 of Figure 1, according to examples of the subject matter disclosed herein. The SEI system may be any of the systems described above, or any other suitable SWIR electro-optic system (e.g., a sensor, camera, lidar, etc.). The method described herein may be performed by one or more processors of the SEI system, for example, processor 130 of Figure 1, and / or one or more processors outside the SEI system, or a combination of both.

[0068] Multiple detection signals can be acquired from the SEI system. Each detection signal can indicate the amount of light captured by at least one FPA detector of the SEI system from a specific direction within the SEI system's FOV over its respective detection time frame (i.e., the detection time frame measured from the trigger of illumination by an associated light source, such as a laser, over which each detection signal is captured). At least one FPA may include multiple individual photosites. Each photosite may include a Ge element where incident photons are converted into detected charges. Any type of photosite characterized by a high dark current can be implemented in the SEI system, even if it does not contain Ge, but rather other elements.

[0069] For each of the multiple directions within the FOV, a different detection signal (among the multiple detection signals mentioned above) indicates the level of reflected SWIR illumination from different distance ranges along that direction.

[0070] Refer to Figure 4. Figure 4 illustrates the timing of three different detection signals arriving from the same direction within the FOV, according to an embodiment of the present disclosure. Diagram 571 in Figure 4 shows the timing of three different detection signals arriving from the same direction within the FOV. The y-axis (vertical coordinate) in the figure indicates the level of response of the detection system to reflected photons arriving from the relevant direction. The reflected illumination originates from one or more light sources (e.g., lasers, LEDs) arbitrarily controlled by the same processor controlling the FPA, and is reflected from a portion of the FOV (e.g., corresponding to a spatial volume detectable by a single photosite). Note that the different detection signals may be associated with similar but not entirely overlapping portions of the FOV (e.g., if the sensor, scene, or intermediate optical system between the two is moving in time, detection signals from the same photosite may be reflected from somewhat different angles within the FOV in different detection time windows associated with the different detection signals).

[0071] Note that Diagram 571 does not show the detection levels of each signal, but rather the response of the detection signals to photons reflected from a complete reflector at different times from the start of light emission. Diagram 572 shows three objects positioned at different distances from the SEI system, for example, from the cleaning system 100. Note that in many instances, only one object is detected at each time in each direction, and this is the object closest to the SEI system. However, in some scenarios, two or more objects may be detected (for example, if the foreground object is partially transparent or does not block light from the entire photosite).

[0072] Diagram 573 shows the levels of three returning signals in a direction for one of the objects – in this example, a dog in the near field, a shoe in the middle range, and a table in the far field (the selection of objects is arbitrary, and only the light reflected from a portion of each object is typically detected by a single photosite). The light returning from the object at distance D1 is represented by the shape of the dog for three different detection signals (corresponding to different detection timing windows and different ranges from the SEI system). Similarly, the levels of detection signals corresponding to the light reflected from the objects at distances D2 and D3 are represented accordingly by the shoe symbol and the table symbol.

[0073] As shown in Diagram 574, reflections from an object placed at a given distance can be converted into a tuple (or any other representation of the data as a directional-related data structure (DADS) of any suitable form) indicating the relative levels of the detected signals in different time windows. In the illustrated example, each number in the tuple indicates the detected signal level in one detection window. The indication of the detected levels in the tuple may be corrected for distance from the sensor (because reflected light from the same object decreases with distance), but this is not necessarily the case. In the illustrated example, three partially overlapping time windows are used, but any number of time windows may be used. The number of time windows may be the same for different areas of the FOV, but this is not necessarily the case.

[0074] Embodiments described herein may include processing multiple detection signals to determine a three-dimensional (3D) detection map containing multiple 3D locations within the FOV where an object is detected. Processing may include compensating for accumulated dark current (DC) levels during the acquisition of multiple detection signals originating from Ge elements. Compensation may include applying different degrees of dark current compensation to detection signals detected by different photosites of at least one focal plane array. Referring to the example in the accompanying drawings, different detection signals may be acquired at different times by different readout structures of any of the applicable photosites described above. Alternatively, detection signals may be acquired by a group of interconnected photosites, as described in more detail below. Other implementations may also be used.

[0075] In addition to, or instead of, compensating for accumulated dark current, processing may include compensating for high integration noise levels and / or readout noise levels during the readout of multiple detection signals. Compensation may include applying different degrees of noise level compensation to detection signals detected by different photosites on at least one focal plane array.

[0076] Compensation for dark current acquisition, readout noise, and / or integration noise can be performed by any suitable method, such as by using any combination of one or more of the following software, hardware, and firmware. In particular, compensation for dark current acquisition can be performed using any combination of one or more of the systems, methods, and computer program products described above, or any part thereof. Some non-limiting examples of systems, methods, and computer program products can be used to compensate for dark current and to apply the degree of dark current compensation to detection signals detected by different photosites.

[0077] In some embodiments, compensation may be performed while acquiring multiple detection signals (for example, at the sensor hardware level). Processing may then be performed on detection signals that have already been compensated for dark current accumulation.

[0078] In some embodiments of the present disclosure, compensation may optionally include subtracting a first dark current compensation offset from a first detection signal detected by a first photosite corresponding to a first detection range, and subtracting a second dark current compensation offset, different from the first dark current compensation offset, from a second detection signal detected by a first photosite corresponding to a second detection range further away from the SEI system than the first detection range.

[0079] Embodiments described herein may include coordination of active illumination (e.g., by at least one light source of the SEI system) and acquisition of detection signals. Optionally, embodiments described herein may further include: (a) triggering the emission of a first illumination (e.g., a laser, an LED) in conjunction with the start of exposure of a first gate image, where a plurality of first detection signals are detected in different directions of a plurality of directions; (b) triggering the emission of a second illumination (e.g., a laser, an LED) in conjunction with the start of exposure of a second gate image, where a plurality of second detection signals are detected in different directions; and (c) triggering the emission of a third illumination (e.g., a laser, an LED) in conjunction with the start of exposure of a third gate image, where a plurality of third detection signals are detected in different directions.

[0080] In such cases, the processing may optionally include: determining the presence of a first object at a first 3D position in a first direction of different directions based on at least one detection signal from each of the first, second, and third images; and determining the presence of a second object at a second 3D position in a second direction of different directions based on at least one detection signal from each of the first, second, and third images. Here, the distance of the first object from the SEI system is at least twice the distance of the second object from the SEI system.

[0081] Optionally, applying different degrees of DC compensation to the detection signals detected by different photosites of at least one FPA may include using detected dark current levels from different reference photosites that are shielded from light arriving from the FOV.

[0082] Optionally, compensation may include applying different degrees of DC compensation to detection signals simultaneously detected by different photosites of at least one FPA.

[0083] With respect to integration noise and readout noise, it should be noted that compensation for such noise may be correlated to the number of illumination pulses used to illuminate portions of the FOV during the acquisition of each detected signal by at least one processor performing the embodiment. Different numbers of illumination pulses may result in significant nonlinearity of the detected signal, which is optionally corrected as part of the processing preceding the determination of the distance / 3D position of different objects within the FOV.

[0084] When referring to the use of DADS to determine the distance / 3D position of different objects within the FOV, note that different transformation functions of DADS (e.g., tuples) for distance may be used for different directions within the FOV to compensate for, for example, non-uniformity of the detection channel across the FOV (e.g., sensors and / or detected objects), non-uniformity of illumination (e.g., using multiple light sources, light source non-uniformity, or optical system non-uniformity), etc.

[0085] According to some embodiments of this disclosure, different detection signals from the same direction within the FOV may correspond to different detection windows. These may be at the same distance or at different distances; for example, the detection window may correspond to a range of distances of approximately 50 cm (e.g., between 80 cm from the SEI system and 130 cm from the SEI system). In different examples, part or all of the detection window used to determine the distance / 3D position of an object within the FOV may be in distance ranges such as between 0.01m-0.1m, between 0.1m-10m, between 5m-25m, between 20m-50m, between 50m-100m, between 100m-250m, etc. The distance ranges associated with different detection signals may overlap. For example, the first detection window can detect returning light from objects between 0cm and 50cm away from the SEI system, the second window can handle objects between 25cm and 75cm away, and the third window can handle objects between 50cm and 150cm away.

[0086] Embodiments disclosed herein may include a system for generating a depth image of a scene based on detection from a short-range infrared (SWIR) electro-optical imaging system (SEI system). The system includes at least one processor configured to acquire multiple detection signals from the SEI system, each detection signal indicating the amount of light captured by at least one FPA detector of the SEI system over each detection time frame from a specific direction within the SEI system's field of view (FOV), the at least one FPA comprising a plurality of separate photosites, each photosite comprising a Ge element where incident photons are converted into detected charges, where for each of the plurality of directions within the FOV, a different detection signal indicates the reflected SWIR illumination level from a different distance range along the direction. The system is configured to process multiple detection signals and to determine a three-dimensional (3D) detection map including multiple 3D locations within the FOV where an object was detected, wherein processing includes compensating for dark current (DC) levels accumulated during the collection of multiple detection signals resulting from Ge elements, wherein compensating includes applying different degrees of DC compensation to detection signals detected by different photosites of at least one FPA.

[0087] In some embodiments of the present disclosure, compensation may include subtracting a first DC compensation offset from a first detection signal detected by a first DE corresponding to a first detection range, and subtracting a second DC compensation offset, different from the first DC compensation offset, from a second detection signal detected by a first DE corresponding to a second detection range further away from the SEI system than the first detection range.

[0088] In some embodiments of the present disclosure, at least one processor may be further configured to: (a) trigger the emission of a first illumination in coordination with the start of exposure of a first gate image, in which a plurality of first detection signals are detected for different directions among a plurality of directions; (b) trigger the emission of a second illumination in coordination with the start of exposure of a second gate image, in which a plurality of second detection signals are detected for different directions; and (c) trigger the emission of a third illumination in coordination with the start of exposure of a third gate image, in which a plurality of third detection signals are detected for different directions. In such cases, at least one processor may be further configured to determine, as part of determining the 3D detection map: That is, (a) the presence of a first object at a first 3D position in a first direction of different directions, based on at least one detection signal from each of the first, second, and third images, and (b) the presence of a second object at a second 3D position in a second direction of different directions, based on at least one detection signal from each of the first, second, and third images. Here, the distance of the first object from the SEI system is at least twice the distance of the second object from the SEI system. The gate image (or equivalent thereof) can be achieved, for example, by utilizing different readout structures of the PDA's photosite in one of the methods described above.

[0089] In some embodiments of this disclosure, applying different degrees of DC compensation to detection signals detected by different photosites of at least one FPA includes using detected dark current levels of different reference photosites that are shielded from light arriving from the FOV. Optionally, compensation may include applying different degrees of DC compensation to detection signals detected simultaneously by different photosites of at least one FPA. Optionally, one or more (and possibly all) of at least one processors may be part of the SEI system.

[0090] Referring now to Figure 5, Figure 5 is a block diagram depicting a computing device that may be included in an embodiment of a system for utilizing SWIR sensing in a vacuum cleaner, according to some embodiments of the present disclosure.

[0091] Computing device 1 may include, for example, a central processing unit (CPU) processor, a chip, or any suitable computing device, a controller 2, an operating system 3, memory 4, executable code 5, a storage system 6, an input device 7, and an output device 8. Controller 2 (or one or more controllers or processors across multiple units or devices) may be configured to perform and / or operate as various modules, units, etc., in the manner described herein. Two or more computing devices 1 may be included in a system according to embodiments of the present disclosure, and one or more computing devices 1 may act as components of a system according to embodiments of the present disclosure. For example, computing devices 1 may be included in the imaging system 1, control system 120, and / or processor 130 of the cleaning system 100 in Figure 1.

[0092] Operating System 3 may be, or may include, any code segment (for example, similar to executable code 5 described herein) designed and / or configured to perform tasks including coordinating, scheduling, mediating, supervising, controlling, or otherwise managing the operation of computing device 1. For example, scheduling the execution of a software program or task, or enabling a software program or other module or unit to communicate. Operating System 3 may be a commercial operating system. It should be noted that Operating System 3 may be any component, and for example, in some embodiments, the system may include computing devices that do not require or have Operating System 3.

[0093] Memory 4 may be, or include, random access memory (RAM), read-only memory (ROM), dynamic RAM (DRAM), synchronous DRAM (SD-RAM), double data rate (DDR) memory chips, flash memory, volatile memory, non-volatile memory, cache memory, buffers, short-term memory units, long-term memory units, or other suitable memory units or storage units. Memory 4 may be, or include, multiple, possibly different memory units. Memory 4 may be a non-temporarily readable medium of a computer or processor, or a non-temporarily stored medium of a computer, such as RAM.

[0094] Executable code 5 may be any executable code, such as an application, program, process, task, or script. Executable code 5 may be executed by controller 2, possibly under the control of operating system 3. For example, executable code 5 may be an application that enables the automatic acquisition of SWIR images. For clarity, a single item of executable code 5 is shown in Figure 4, but systems according to some embodiments include multiple executable code segments similar to executable code 5, which are loaded into memory 4 and can cause controller 2 to execute them in the manner described herein.

[0095] The storage system 6 may be, for example, a flash memory known in the art, a memory located inside or embedded in a microcontroller or chip known in the art, a hard disk drive, a write-once (CD-R) drive, a Blu-ray disc (BD), a Universal Serial Bus (USB) device, or other suitable removable and / or fixed storage unit, or may include them. Content is stored in the storage system 6 and may be loaded from the storage system 6 into memory 4, where it can be processed by controller 2. In some embodiments, some of the components shown in Figure 4 may be omitted. For example, memory 4 may be a non-volatile memory having the storage capacity of the storage system 6. Thus, although shown as a separate component, the storage system 6 may be embedded in or included in memory 4.

[0096] Input device 7 may be, or include, any suitable input device, component, or system, such as a detachable keyboard or keypad, a mouse, etc. Output device 8 may include one or more (possibly detachable) displays or monitors, speakers, and / or any other suitable output devices. Any applicable input / output (I / O) devices may be connected to computing device 1 as shown by blocks 7 and 8. For example, a wired or wireless network interface card (NIC), a Universal Serial Bus (USB) device, or an external hard drive may be included in input device 7 and / or output device 8. It will be recognized that any suitable number of input devices 7 and output devices 8 may be operably connected to computing device 1 as shown by blocks 7 and 8.

[0097] In some embodiments, the system may include, but is not limited to, multiple central processing units (CPUs), or any other suitable multipurpose or specific processors, controllers (e.g., a controller similar to controller 2), microprocessors, microcontrollers, field-programmable gate arrays (FPGAs), programmable logic devices (PLDs), or application-specific integrated circuits (ASICs). In some embodiments, the system may include multiple input units, multiple output units, multiple memory units, and multiple storage units. The system may additionally include other suitable hardware components and / or software components. Where applicable, modules or units described herein may be similar to or include components of device 1 described herein.

[0098] Unless otherwise indicated, the functions described above in this specification may be performed by executable code and instructions stored on a computer-readable medium and running on one or more processor-based systems. Furthermore, those skilled in the art will understand that this disclosure may be implemented in other computer system configurations, including multiprocessor systems, microprocessor-based electronic devices, minicomputers, and mainframe computers.

[0099] The terms “for example,” “eg,” and “optionally” as used herein are intended to introduce non-restrictive examples. While a given example system component or algorithm is referenced, other components and algorithms may be used in the same way, and / or the example component may be combined into fewer components, and / or further divided into more components.

[0100] While certain features of this disclosure have been illustrated and described herein, many modifications, substitutions, alterations, and equivalents will come to mind for those skilled in the art. It should therefore be understood that the appended claims are intended to encompass all such modifications and alterations as they fall within the true spirit of this disclosure.

[0101] Various embodiments have been presented. Each of these embodiments may, of course, include features from other embodiments presented. And embodiments not specifically described may include various features described herein.

Claims

1. It is an autonomous cleaning system, A first illumination source for emitting radiation at a first wavelength in the short-wave infrared (SWIR) range toward a first field of view (FOV), wherein the first FOV includes an area to be cleaned around the cleaning system. A receiver that operates within the SWIR and acquires SWIR image data based on radiation reflected from elements located within the first FOV, A processor for determining the presence of aqueous liquid in the first FOV based on the SWIR image data, It includes, and further, The system includes a second illumination source for emitting radiation at a second wavelength different from the first wavelength in the SWIR toward a target in a second FOV contained within the first FOV, The processor operates to determine the material by determining the spectral characteristics of the target based on the absorption of the target at the first wavelength and the absorption of the target at the second wavelength, and, Based on the presence of aqueous liquid within the first FOV determined above, the autonomous cleaning system is controlled to avoid driving into the identified aqueous liquid or to pass around the identified aqueous liquid. Autonomous cleaning system.

2. The second lighting source includes a low-power lighting source. The autonomous cleaning system according to claim 1.

3. The receiver comprises one or more germanium (Ge) photodiodes (PDs). The autonomous cleaning system according to claim 1.

4. The first illumination source includes a laser source. The autonomous cleaning system according to claim 1.

5. The first wavelength is between 1300 nm and 1400 nm. The autonomous cleaning system according to claim 1.

6. The second light source comprises a light-emitting diode (LED), The autonomous cleaning system according to claim 1.

7. The second wavelength is between 800 nm and 1000 nm. The autonomous cleaning system according to claim 1.

8. The aforementioned autonomous cleaning system further, A third illumination source for emitting radiation at a third wavelength within the SWIR toward the target within the first FOV, The processor operates to determine the spectral characteristics of the target based on the absorption of the target at the first wavelength, the absorption of the target at the second wavelength, and the absorption of the target at the third wavelength. An autonomous cleaning system according to any one of claims 1 to 7.

9. A method for using a short-wave infrared range (SWIR) vision system in an autonomous cleaning system, The steps include: emitting radiation at a first wavelength within the SWIR toward a first field of view (FOV) using a first illumination source, wherein the first FOV includes an area to be cleaned around the cleaning system; The steps include: receiving radiation reflected from an element located within the first field of view using a receiver operating within the SWIR; A step of acquiring SWIR image data based on radiation reflected from elements placed within the first FOV, A step of determining the presence of aqueous liquid in the first FOV based on the SWIR image data, It includes, and further, A second illumination source emits radiation at a second wavelength different from the first wavelength in the SWIR toward a target in the second FOV contained within the first FOV, The steps include determining the spectral characteristics of the target based on the absorption of the target at the first wavelength and the absorption of the target at the second wavelength, and determining the material, A step of controlling the autonomous cleaning system based on the presence of the aqueous liquid in the first FOV determined, the step of avoiding driving into the identified aqueous liquid or passing around the identified aqueous liquid, including, method.

10. The second lighting source includes a low-power lighting source. The method according to claim 9.

11. The receiver comprises one or more germanium (Ge) photodiodes (PDs). The method according to claim 9.

12. The first illumination source includes a laser source. The method according to claim 9.

13. The first wavelength is between 1300 nm and 1400 nm. The method according to claim 9.

14. The second light source comprises a light-emitting diode (LED), The method according to claim 9.

15. The second wavelength is between 800 nm and 1000 nm. The method according to claim 9.

16. The above method further, The third illumination source emits radiation at a third wavelength in the SWIR toward the target within the first FOV, A step of determining the spectral characteristics of the target based on the absorption of the target at the first wavelength, the absorption of the target at the second wavelength, and the absorption of the target at the third wavelength. The method according to any one of claims 9 to 15, including

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