Time-of-flight sensor equipment and usage methods

Abstract

An apparatus (100) determines a time-of-flight measurement by performing sampling of a sensor based on light received via at least one first spectral filter (110), wherein the at least one first spectral filter is associated with a spectral range for the time-of-flight measurement; determines that a condition relating to the time-of-flight measurement is satisfied, wherein the condition relates to the orientation or position of the sensor or sensor device relative to the measurement target; triggers a spectral measurement to be performed based on the determination that the condition relating to the time-of-flight measurement is satisfied; and performs a spectral measurement of the measurement target (130) based on light received via at least one second spectral filter (105) and by performing sampling of the sensor based on the condition relating to the time-of-flight measurement being satisfied.

Description

[0001] Related applications

[0002] This application claims priority to U.S. Provisional Patent Application No. 62 / 804,609, filed February 12, 2019, entitled “Sensor Device and Method of Use”, and U.S. Non-Provisional Patent Application No. 16 / 784,766, filed February 7, 2020, entitled “Sensor Device and Method of Use”, which are hereby expressly incorporated herein by reference. Background Technology

[0003] Sensor devices can be used to capture information for spectral analysis. For example, a sensor device can capture information related to a set of electromagnetic frequencies. A sensor device may include a set of sensor elements (e.g., optical sensors, spectral sensors, and / or image sensors) for capturing information. For example, an array of sensor elements can be used to capture information related to multiple frequencies. Analysis can be performed on the information related to multiple frequencies to determine spectral information. Summary of the Invention

[0004] In some aspects, a device for wireless communication may include a sensor. The device may include at least one first spectral filter and at least one second spectral filter, wherein the at least one first spectral filter is associated with a spectral range for time-of-flight measurement, and wherein the at least one second spectral filter is associated with a spectral range for spectral measurement. The device may include one or more memories. The device may include one or more processors communicatively coupled to one or more memories to: determine a time-of-flight measurement value using the sensor, based on light received via the at least one first spectral filter; determine that a condition relating to the time-of-flight measurement is met, wherein the condition relates to the orientation or position of the sensor or sensor device relative to a measurement target; trigger a spectral measurement to be performed based on the determination that the condition relating to the time-of-flight measurement is met; perform a spectral measurement for a measurement target using the sensor and based on light received via the at least one second spectral filter, based on the condition relating to the time-of-flight measurement being met; and provide information identifying the spectral measurement.

[0005] In some aspects, a wireless communication method may include: performing a time-of-flight measurement based on light received via at least one first spectral filter, using a sensor device and employing a sensor, wherein the at least one first spectral filter is associated with a spectral range for the time-of-flight measurement; determining, using the sensor device, that a condition relating to the time-of-flight measurement is met, wherein the condition relates to the orientation or position of the sensor or sensor device relative to a measurement target; performing a spectral measurement for the measurement target based on light received via at least one second spectral filter, and based on the condition relating to the time-of-flight measurement being met; and providing information identifying the spectral measurement via the sensor device.

[0006] In some aspects, a non-transitory computer-readable medium may store one or more instructions for wireless communication. When executed by one or more processors of the device, the one or more instructions may cause the one or more processors to: determine a time-of-flight measurement by performing sampling of a sensor based on light received via at least one first spectral filter, wherein the at least one first spectral filter is associated with a spectral range for the time-of-flight measurement; determine that a condition relating to the time-of-flight measurement is satisfied, wherein the condition relates to the orientation or position of the sensor or sensor device relative to the measurement target; trigger a spectral measurement to be performed based on the determination that the condition relating to the time-of-flight measurement is satisfied; and perform a spectral measurement for the measurement target based on light received via at least one second spectral filter and by performing sampling of the sensor, based on the condition relating to the time-of-flight measurement being satisfied. Attached Figure Description

[0007] Figure 1A and Figure 1B This is an overview diagram of the example implementation described in this article.

[0008] Figure 2 This is an example diagram of the spectral filter described in this article.

[0009] Figure 3 This is an example environment diagram that can implement the systems and / or methods described in this article.

[0010] Figure 4 yes Figure 2 Example component diagram of one or more devices.

[0011] Figure 5 This is a flowchart of an example process for performing spectral measurements based on time-of-flight measurements.

[0012] Figure 6 This is a flowchart of an example process for performing spectral measurements based on time-of-flight measurements.

[0013] Figure 7This is a flowchart of an example process for performing spectral measurements based on time-of-flight measurements. Detailed Implementation

[0014] The following detailed description of the exemplary embodiments is with reference to the accompanying drawings. The same reference numerals in different drawings may identify the same or similar elements. A spectrometer is used as an example in the following description. However, the calibration principles, procedures, and methods described herein can be used with any sensor, including but not limited to other optical and spectral sensors.

[0015] Multispectral imaging can be used to capture image data across a specific wavelength range of the electromagnetic spectrum. In some cases, hyperspectral imaging can be performed, which can use more spectral bands and / or more tightly grouped spectral bands than multispectral imaging. However, for the purposes of the implementation described herein, "multispectral" and "hyperspectral" are used interchangeably. Using multispectral imaging data based on spectral analysis techniques, a sensor can determine a measurement. This measurement may be referred to herein as a spectral measurement. Spectral measurements can be useful for a variety of purposes, such as chemical composition analysis of materials, determination of moisture content, determination of vegetation cover, plant health, plant nutrition, human health assessment, etc.

[0016] Ensuring that sensor devices are correctly positioned for spectral measurements is challenging. For example, spectral measurements may be calibrated based on a specific distance between the sensor device and the measurement target, or they may require a fixed sensor device. Some sensor devices can be reinforced for the required positioning using mechanical clamps, such as shrouds, light tubes, positioning collars, spacers, and / or the like. However, mechanical clamps can be large, expensive, and / or bulky, and may be impractical for certain types of sensor devices, such as those used in mobile devices (e.g., smartphones).

[0017] Some embodiments described herein provide time-of-flight (ToF) based techniques for determining the spectral measurement to be performed based on conditions related to the orientation or position of a sensor device. For example, the sensor device may perform a ToF measurement to determine that the sensor device is properly positioned for the spectral measurement to be performed by the sensor device. The sensor device may determine that it is positioned at an appropriate distance from the measurement target (e.g., using a single ToF measurement or multiple ToF measurements), or it may determine that the sensor device is properly aligned with the measurement target (e.g., using multiple ToF measurements to determine the plane of the sensor device and / or the measurement target). The ToF measurement may be performed based on light filtered by a ToF filter, which may be a region of a spectral filter designed to pass through light associated with the ToF. In some embodiments, the spectral measurement may be performed on the next available readout following the ToF measurement. In this way, the sensor device can perform spectral measurements based on conditions related to the orientation or position of the sensor device based on the ToF measurement. This can improve the accuracy of the spectral measurement and reduce the impact of inconsistencies in sensor device positioning. Furthermore, performing spectral measurements can reduce or eliminate reliance on mechanical fixtures for proper positioning of sensor devices, thereby reducing the size, cost, and weight of the sensor devices.

[0018] Figure 1A and Figure 1B This is an overview diagram of the example implementation 100 described herein. Example implementation 100 relates to determining spectral measurements based on ToF measurements from a sensor device. As shown, the sensor device may include a spectral filter 105, one or more ToF filters 110-1 and 110-2 (shown as ToF filter A and ToF filter B), a sensor 115, a light source 120, and a processor 125. The sensor device and its operation are described below. Figure 1A Described. Determination of spectral measurements based on ToF measurements from sensor devices. Figure 1B Described.

[0019] Spectral filter 105 may include: a spectral filter, a multispectral filter, a multichannel spectral filter, a bandpass filter, a bandstop filter, a long-pass filter, a short-pass filter, a dichroic filter, a linear variable filter (LVF), a circular variable filter (CVF), a Fabry-Perot filter, a Bayer filter, etc. Spectral filter 105 can transmit light of one or more wavelengths for the spectral measurements performed on the measurement target 130. For example, the light transmitted by spectral filter 105 may be in the subvisible wavelength range (e.g., ultraviolet and / or similar), the visible wavelength range (e.g., red, green, blue, and / or similar), the ultravisible wavelength range (e.g., infrared, near-infrared, mid-infrared, and / or similar), or different spectral ranges. In some embodiments, spectral filter 105 may include multiple filters.

[0020] The ToF filter 110 may include: a spectral filter, a multispectral filter, a bandpass filter, a bandstop filter, a long-pass filter, a short-pass filter, a dichroic filter, a linear variable filter (LVF), a circular variable filter (CVF), a Fabry-Perot filter, a Bayer filter, and / or the like. The ToF filter 110 can transmit light of one or more wavelengths for the execution of ToF measurements on the measurement target 130. For example, the light transmitted by the ToF filter 110 may be in the near-infrared range or in another range (e.g., a range of wavelengths described herein or a range of wavelengths not described herein).

[0021] In example implementation 100, there are two ToF filters 110. In some implementations, there can be any number of ToF filters 110. For example, combining... Figure 1B In more detail, a single ToF filter 110 can realize the measurement of distance between the sensor device and the measurement target 130, while multiple ToF filters 110 can realize the determination of the sensor device orientation relative to the measurement target 130. In some embodiments, the ToF filter 110 may be part of a spectral filter 105. For example, the spectral filter 105 and the ToF filter 110 may be a single filter or a set of filters, designed to pass wavelengths used for both ToF and spectral measurements. In some embodiments, the spectral filter 105 and the ToF filter 110 may be coplanar. In some embodiments, the spectral filter 105 and the ToF filter 110 may be in different planes.

[0022] Sensor 115 includes a device capable of measuring light directed to sensor 115 (e.g., via spectral filter 105 and / or ToF filter 110), such as an optical sensor, spectral sensor, image sensor, and / or the like. For example, sensor 115 may perform sensor measurements on the light directed to sensor 115. Sensor 115 may utilize one or more sensor technologies, such as complementary metal-oxide-semiconductor (CMOS) technology, charge-coupled device (CCD) technology, and / or similar technologies. Sensor 115 may include multiple sensor elements (e.g., an array of sensor elements – referred to as a sensor array), each sensor configured to acquire information. For example, a sensor element may provide an indication of the intensity of light incident on the sensor element (e.g., active / inactive or more fine-grained intensity indication). Using these indications, the sensor device may determine ToF measurements and / or spectral measurements, as described in more detail elsewhere herein. In some embodiments, sensor 115 may include multiple, different sensors (e.g., one or more first sensors for spectral measurements and one or more second sensors for ToF measurements).

[0023] Light source 120 can provide light for spectral measurements and / or ToF measurements. For example, light source 120 may include a laser, a light-emitting diode, etc. In some embodiments, such as in example embodiment 100, a single light source 120 can provide light for spectral measurements and (one or more) ToF measurements. This can reduce the cost, size, and complexity associated with providing multiple different light sources. In some embodiments, a corresponding individual light source 120 can provide light for both spectral measurements and ToF measurements. This allows for more accurate or continuous determination of spectral measurements while the light source 120 for ToF measurements is chopped or pulsed for ToF measurements. Here, sensor 115 and filters 105 / 110 are shown as being between the measurement target 130 and the light source 120. However, in some embodiments, sensor 115 and filters 105 / 110 may not be located between the measurement target 130 and the light source 120.

[0024] Such as combination Figure 1B In more detail, processor 125 can perform operations related to the determination of ToF measurements and / or spectral measurements. As an example, and as shown by reference numerals 135 and 140, processor 125 can determine one or more ToF measurements (shown as ToF) using ToF filters A and B respectively. A and ToF BProcessor 125 can use sensor 115 and determine the ToF measurement based on the light transmitted by light source 120. For example, processor 125 can use a region of sensor 115 associated with ToF filter 110 to identify a specific pattern or intensity of light transmitted by light source 120. Processor 125 can determine the ToF for that light based on the light's transmission time and the time when a specific pattern or intensity is detected. For example, processor 125 can determine the ToF based on the time it takes for light to be received by ToF filter A after it is emitted by light source 120. A Furthermore, the Time of Flight (ToF) can be determined based on the time it takes for light to be received by the ToF filter B after it is emitted by the light source 120. B In some implementations, ToF A and ToF B It can be associated with different wavelengths. In some implementations, ToF... A and ToF B They can be associated with the same wavelength.

[0025] like Figure 1B As shown, and as indicated by reference numeral 145, processor 125 can use sensor 115 and ToF filters A and B to determine the ToF. A and ToF B For example, processor 125 can determine the Time of Flight (ToF) using a technique based on the ToF of light emitted by light source 120 and filtered by ToF filters A and B. A and ToF B In some implementations, processor 125 may perform one or more samplings of sensor 115 to determine the Time of Flight (ToF). A and / or ToF B For example, processor 125 can periodically perform sampling of sensor 115 to identify data for use with ToF. A and / or ToF B The signal is associated with the light. In some embodiments, the processor 125 may perform sampling of the region of the sensor 115 corresponding to the ToF filter 1 and / or the ToF filter B (e.g., overlapping, consistent in range, covering, and / or similar).

[0026] As indicated by reference numeral 150 in the attached figure, processor 125 may be based on ToF. A and ToF B Determine that one or more Time-of-Flight (ToF) conditions are met. For example, processor 125 can be based on ToF... A and / or ToF BConditions for determining the orientation or position of the sensor device and / or sensor 115 relative to the measurement target 130 are met. In some embodiments, processor 125 may determine that conditions for determining the position of sensor 115 relative to the measurement target 130 are met. For example, when the ToF value (e.g., ToF) is... A ToF B The processor 125 can determine that a condition is met when the sensor 115 is within a specific distance (or within an acceptable range of a specific distance) from the measurement target 130. In some implementations, the processor 125 can determine that a condition for the orientation of the sensor 115 or sensor device relative to the measurement object 130 is met. For example, the processor 125 can determine that a condition for the orientation of the sensor device and / or sensor 115 is met based on two or more Time-of-Flight (ToF) measurements. For example, a condition can be met when each of the two or more ToF measurements is within a threshold range of each other. This can indicate that the sensor device and / or sensor 115 is approximately parallel to the measurement target 130.

[0027] As indicated by reference numeral 155, processor 125 may perform spectral measurements based on one or more ToF conditions being met. For example, processor 125 may perform sampling of sensor 115 and / or sampling of a region of sensor 115 associated with the spectral measurement to determine image data for the spectral measurement, and may analyze the image data to determine the spectral measurement. In some embodiments, processor 125 may trigger the spectral measurement to be performed based on one or more ToF conditions being met. In some embodiments, the spectral measurement may involve measuring the spectral characteristics 130 of a target, the chemical composition 130 of a target, etc. In some implementations, the sensor device may determine characteristics of a person (e.g., health characteristics, heart rate, blood oxygen level, blood glucose level, activity level, etc.), and / or other characteristics based on the spectral measurement.

[0028] As indicated by reference numeral 160, in some cases, processor 125 may adjust spectral measurements based on one or more ToF measurements. For example, processor 125 may enhance, modify, or alter spectral measurements based on one or more ToF measurements. As a more specific example, processor 125 may determine an orientation offset (e.g., angular offset and / or other type) between one or more ToF measurements and the measurement target 130 and may apply transformations to the spectral measurements to improve accuracy in an orientation offset view. As another example, processor 125 may determine the velocity or rate of the sensor device or sensor 115 and may adjust the spectral measurements based on the velocity or rate. Additionally or alternatively, processor 125 may provide one or more ToF measurements and spectral measurements. For example, processor 125 may provide one or more ToF measurements and spectral measurements for display, processing by another device, etc.

[0029] In some implementations, processor 125 can determine the ToF measurement after the spectral measurement. For example, processor 125 can perform the spectral measurement and then perform the ToF measurement. This can help determine the validity of the spectral measurement. For example, the ToF measurement can provide an indication of whether sensor 115 is removing too quickly from ideal conditions for the spectral measurement. In some implementations, processor 125 can determine multiple ToF measurements before and after the spectral measurement to determine the speed of the image sensor device before and after the spectral scan. This can be useful for determining the accuracy of the spectral measurement or adjusting the spectral measurement based on the speed.

[0030] As mentioned above, Figure 1A and Figure 1B Provided as one or more examples. Other examples may be related to... Figure 1A and Figure 1B The descriptions are different.

[0031] Figure 2 This is an example diagram of the spectral filter 200 described in this article. Figure 2 In, with Figure 1A and Figure 1B The side view shown contrasts with the front view, where the spectral filter 200 is shown. The spectral filter 200 may include one or more spectral filters 105 (in combination with...). Figure 1A and Figure 1B (more detailed description) and one or more ToF filters 110-1 to 110-N (also combined with) Figure 1A and 1B(Described in more detail). In some embodiments, the spectral filter 200 may include a single ToF filter 110. This allows the distance of the sensor device from the measurement target (e.g., measurement target 130) to be measured using a single ToF filter 110. In some embodiments, the spectral filter 200 may include (e.g., spatially distributed) two ToF filters 110. This enables the measurement of the orientation of the sensor device relative to the measurement target about an axis (e.g., an axis coplanar and orthogonal to the axis connecting the two ToF filters 110). In some embodiments, the spectral filter 200 may include three or more spatially distributed ToF filters 110, such as... Figure 2 As shown. This allows for the measurement of the orientation of the sensor device relative to the measurement target around two axes (e.g., two axes in the plane of the spectral filter 200), provided that the three or more ToF filters 110 are not all placed on the common axis.

[0032] Therefore, based on the location of one or more ToF filters 110, location and / or orientation information can be determined using one or more ToF filters 110. For example, one or more ToF filters 110 can be spatially distributed to allow direction determination based on light passing through one or more ToF filters 110. As described above, this enables more accurate determination of spectral measurements without correspondingly increasing the size, weight, or complexity of the sensor device.

[0033] As mentioned above, Figure 2 Provided as an example only. Other examples may be found on [the website / platform]. Figure 2 The descriptions are different.

[0034] Figure 3 This is a diagram of an example environment 300 in which the systems and / or methods described in this paper can be implemented. (See diagram 300 for example environments 300.) Figure 3 As shown, environment 300 may include control device 310, sensor device 320, and network 330. The devices in environment 300 can be interconnected via wired connection, wireless connection, or a combination of wired and wireless connection.

[0035] Control device 310 includes one or more devices capable of storing, processing, and / or routing information associated with multispectral sensing. For example, control device 310 may include a server, computer, wearable device, cloud computing device, etc. In some embodiments, control device 310 may be associated with a specific sensor device 320. In some embodiments, control device 310 may be associated with multiple sensor devices 320. In some embodiments, control device 310 may receive information from another device in environment 300, such as sensor device 320, and / or transmit information to another device in environment 300.

[0036] Sensor device 320 includes a device capable of performing measurements on light directed to sensor device 320. For example, sensor device 320 may include an image sensor, multispectral sensor, spectral sensor, etc., capable of performing sensor measurements on light directed to sensor device 320. Sensor device 320 may utilize one or more sensor technologies, such as complementary metal-oxide-semiconductor (CMOS) technology, charge-coupled device (CCD) technology, etc. Sensor device 320 may be able to perform Time-of-Flight (ToF) measurements (e.g., using a region 320 of the sensor device, based on light passing through a specific filter or filtering area 320 of the sensor device, etc.).

[0037] Network 330 includes one or more wired and / or wireless networks. For example, network 330 may include cellular networks (e.g., Long Term Evolution (LTE) networks, Code Division Multiple Access (CDMA) networks, 3G networks, 4G networks, 5G networks, another type of next-generation network), Public Land Mobile Networks (PLMN), Local Area Networks (LAN), Wide Area Networks (WAN), Metropolitan Area Networks (MAN), Telephone Networks (e.g., Public Switched Telephone Network (PSTN)), Private Networks, Self-organizing Networks, Intranets, the Internet, Fiber-based Networks, Cloud Computing Networks, etc., and / or networks combining these or other types.

[0038] Figure 3 The number and arrangement of devices and networks shown are provided as examples. In practice, with Figure 3 Compared to those shown, there may be additional equipment and / or networks, fewer equipment and / or networks, different equipment and / or networks, or equipment and / or networks with different arrangements. Furthermore, Figure 3 The two or more devices shown can be implemented within a single device, or Figure 3 The single device shown can be implemented as multiple distributed devices. Additionally or alternatively, a group of devices in environment 300 (e.g., one or more devices) can perform one or more functions described as being performed by another group of devices in environment 300.

[0039] Figure 4 This is a diagram of example components of device 400. Device 400 may correspond to control device 310 and / or sensor device 320. In some implementations, control device 310 and / or sensor device 320 may include one or more devices 400 and / or one or more components 400 of the device. Figure 4 As shown, device 400 may include bus 410, processor 420, memory 430, storage unit 440, input unit 450, output unit 460 and communication interface 470.

[0040] Bus 410 includes components that allow communication between multiple components of device 400. Processor 420 is implemented in hardware, firmware, and / or a combination of hardware and software. Processor 420 is a central processing unit (CPU), graphics processing unit (GPU), accelerated processing unit (APU), microprocessor, microcontroller, digital signal processor (DSP), field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), or other type of processing unit. In some embodiments, processor 420 includes one or more processors capable of being programmed to perform functions. Memory 430 includes one or more memories, such as random access memory (RAM), read-only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic storage, and / or optical storage), which store information and / or instructions for use by processor 420. An example of processor 420 is processor 125, which combines... Figure 1A and Figure 1B It is shown and described.

[0041] Storage component 440 stores information and / or software related to the operation and use of device 400. For example, storage component 440 may include hard disks (e.g., magnetic disks, optical disks, and / or magneto-optical disks), solid-state drives (SSDs), compact discs (CDs), digital versatile optical discs (DVDs), floppy disks, cassette tapes, magnetic tapes, and / or other types of non-transitory computer-readable media, and corresponding drives.

[0042] Input component 450 includes components that allow device 400 to receive information, such as via user input (e.g., touchscreen display, keyboard, keypad, mouse, button, switch, and / or microphone). Additionally or alternatively, input component 450 may include components for determining location (e.g., a Global Positioning System (GPS) component) and / or sensors (e.g., an accelerometer, gyroscope, actuator, another type of positioning or environmental sensor, etc.). Output component 460 includes components that provide output information from device 400 (via, for example, a display, speaker, haptic feedback component, audio or visual indicator, and / or other types).

[0043] Communication interface 470 includes transceiver-like components (e.g., transceiver, separate receiver, separate transmitter, and / or other types) that enable device 400 to communicate with other devices, for example, via a wired connection, a wireless connection, or a combination of wired and wireless connections. Communication interface 470 may allow device 400 to receive information from and / or provide information to another device. For example, communication interface 470 may include an Ethernet interface, an optical interface, a coaxial cable interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, etc.

[0044] Device 400 can perform one or more processes described herein. Device 400 can perform these processes based on software instructions stored by a non-transitory computer-readable medium, such as memory 430 and / or storage unit 440, which are executed by processor 420. As used herein, the term "computer-readable medium" refers to a non-transitory memory device. A memory device includes storage space within a single physical storage device or storage space distributed across multiple physical storage devices.

[0045] Software instructions may be read from another computer-readable medium or from another device via communication interface 470 into memory 430 and / or storage unit 440. When executed, the software instructions 440 stored in memory 430 and / or storage unit may cause processor 420 to perform one or more processes described herein. Additionally or alternatively, hardware circuitry may be used in place of or in conjunction with the software instructions to perform one or more processes described herein. Therefore, the implementations described herein are not limited to any particular combination of hardware circuitry and software.

[0046] Figure 4 The number and arrangement of the components shown are provided as an example. In practice, device 400 may include components related to... Figure 4 The components shown may be additional, fewer, different, or arranged differently. Alternatively or additionally, one set of components (e.g., one or more components) of device 400 may perform one or more functions described as being performed by another set of components of device 400.

[0047] Figure 5 This is a flowchart of an example procedure 500 for performing spectral measurements based on time-of-flight measurements. In some implementations, Figure 5 One or more processing blocks can be executed by a sensor device (e.g., the sensor device of Figure 1, sensor device 320, and / or other types). In some embodiments, Figure 5 One or more process blocks may be executed by another device or a group of devices that are separate from or include the sensor device, such as a control device (e.g., control device 310).

[0048] As shown in Figure 5, process 500 may include using a sensor to determine a time-of-flight measurement based on light received via at least one first spectral filter (block 510). For example, a sensor device (e.g., using processor 125, processor 420, sensor 115, etc.) may determine the time-of-flight measurement based on light received via at least one first spectral filter. In some embodiments, the at least one first spectral filter may be a ToF filter (e.g., ToF filter 110), as described in more detail elsewhere herein. In some embodiments, the sensor device may include at least one second spectral filter. In some embodiments, at least one first spectral filter is associated with a spectral range for time-of-flight measurement, and at least one second spectral filter is associated with a spectral range for spectral measurement.

[0049] like Figure 5 As further shown, process 500 may include determining that a condition for the time-of-flight measurement is met, wherein the condition relates to the orientation or position of the sensor or sensor device relative to the measurement target (block 520). For example, the sensor device (e.g., using processor 125 or processor 420) may determine that the condition related to the ToF measurement is met. This condition may relate to the orientation or position of the sensor or sensor device relative to the measurement target.

[0050] like Figure 5 As further shown, process 500 may include triggering a spectral measurement to be performed (block 530) based on determining that conditions regarding the Time-of-Flight (ToF) measurement are met. For example, the sensor device (e.g., using processor 125 or processor 420) may trigger the spectral measurement to be performed. The sensor device may trigger the spectral measurement to be performed based on determining that conditions regarding the ToF measurement are met.

[0051] like Figure 5 As further shown, process 500 may include performing a spectral measurement on a measurement target using a sensor and based on light received via at least one second spectral filter, based on conditions regarding time-of-flight measurement being met (block 540). For example, a sensor device (e.g., using processor 125, processor 420, sensor 115, and / or other types) may perform a spectral measurement based on light received via at least one second spectral filter. The sensor device may perform a spectral measurement using a sensor. The sensor device may perform a spectral measurement based on conditions regarding Time-of-Flight measurement being met.

[0052] like Figure 5As further shown, process 500 may include providing information identifying the spectral measurement (block 550). For example, a sensor device (e.g., using processor 125, processor 420, output component 460, and / or other types) may provide information identifying the spectral measurement. In some implementations, the sensor device may store information identifying the spectral measurement. In some embodiments, the sensor device may provide information identifying the spectral measurement to a user (e.g., through a user interface or display associated with the sensor device).

[0053] Process 500 may include additional implementations, such as any single implementation or any combination of implementations of one or more other processes described below and / or elsewhere herein.

[0054] In a first embodiment, at least one first spectral filter includes a plurality of first spectral filters in a plane, along with at least one second spectral filter. In a second embodiment, alone or in combination with the first embodiment, at least one first spectral filter includes a plurality of spatially distributed first spectral filters to allow orientation determination based on light passing through the plurality of first spectral filters. In a third embodiment, alone or in combination with one or more embodiments of the first and second embodiments, a time-of-flight measurement is a first time-of-flight measurement, and the sensor device further determines a second time-of-flight measurement after the spectral measurement, and determines the velocity or updated orientation or position of the sensor device based on the second time-of-flight measurement. In a fourth embodiment, alone or in combination with one or more embodiments of the first to third embodiments, at least one first spectral filter includes a single spectral filter, and orientation or position is determined based on light passing through the single spectral filter.

[0055] In a fifth embodiment, either alone or in combination with one or more embodiments of the first to fourth embodiments, the sensor device can modify the spectral measurement based on a time-of-flight measurement. In a sixth embodiment, either alone or in combination with one or more embodiments of the first to fifth embodiments, the sensor device can obtain a first sample of data from the sensor; and obtain a second sample of data from the sensor based on a triggered spectral measurement. In a seventh embodiment, either alone or in combination with one or more embodiments of the first to sixth embodiments, the interval between the first sample and the second sample is less than approximately ten milliseconds. In an eighth embodiment, either alone or in combination with one or more embodiments of the first to seventh embodiments, the first sample is associated with one or more first pixel regions of the sensor and the second sample is associated with one or more second pixel regions of the sensor.

[0056] although Figure 5An example block of process 500 is shown, but in some implementations, process 500 may include... Figure 5 Compared to the blocks described in the diagram, there may be additional blocks, fewer blocks, different blocks, or blocks with different arrangements. Alternatively or concurrently, two or more blocks of process 500 may be executed in parallel.

[0057] Figure 6 This is a flowchart of an example process 600 for performing spectral measurements based on time-of-flight measurements. In some implementations, Figure 6 One or more process blocks can be executed by a sensor device (e.g., the sensor device of Figure 1, sensor device 320, etc.). In some embodiments, Figure 6 One or more process blocks may be executed by another device or a group of devices that are separate from or include the sensor device, such as a control device (e.g., control device 310).

[0058] like Figure 6 As shown, process 600 may include using a sensor to perform a time-of-flight measurement based on light received via at least one first spectral filter, wherein the at least one first spectral filter is associated with a spectral range for the time-of-flight measurement (block 610). For example, a sensor device (e.g., using processor 125, processor 420, sensor 115, etc.) may perform the time-of-flight measurement based on light received via at least one first spectral filter. In some embodiments, the at least one first spectral filter may be a ToF filter (e.g., ToF filter 110), as described in more detail elsewhere herein. In some embodiments, the sensor device may include at least one second spectral filter. In some embodiments, at least one first spectral filter is associated with a spectral range for the time-of-flight measurement, and at least one second spectral filter is associated with a spectral range for the spectral measurement.

[0059] like Figure 6 As further shown, process 600 may include determining that a condition for the time-of-flight measurement is met, wherein the condition relates to the orientation or position of the sensor or sensor device relative to the measurement target (block 620). For example, the sensor device (e.g., using processor 125 or processor 420) may determine that a condition for the ToF measurement is met. This condition may relate to the orientation or position of the sensor or sensor device relative to the measurement target.

[0060] like Figure 6As further shown, process 600 may include performing a spectral measurement on a measurement target using a sensor and based on light received via at least one second spectral filter, based on conditions regarding the time-of-flight measurement being met. For example, a sensor device (e.g., using processor 125, processor 420, sensor 115, and / or other types) may perform the spectral measurement based on light received via at least one second spectral filter. The sensor device may perform the spectral measurement using a sensor. The sensor device may perform the spectral measurement based on conditions regarding the ToF measurement being met.

[0061] like Figure 6 As further shown, process 600 may include providing information identifying the spectral measurement (block 640). For example, a sensor device (e.g., using processor 125, processor 420, output component 460, and / or other types) may provide information identifying the spectral measurement. In some implementations, the sensor device may store the information identifying the spectral measurement. In some implementations, the sensor device may provide the information identifying the spectral measurement to a user (e.g., through a user interface or a display associated with the sensor device).

[0062] Process 600 may include additional implementations, such as any single implementation or any combination of implementations of one or more other processes described below and / or elsewhere herein.

[0063] In a first embodiment, light received via at least one first spectral filter and light received via at least one second spectral filter originate from the same light source. In a second embodiment, alone or in combination with the first embodiment, light received via at least one first spectral filter and light received via at least one second spectral filter originate from different light sources. In a third embodiment, alone or in combination with one or more of the first and second embodiments, at least one first spectral filter comprises a plurality of first spectral filters coplanar with at least one second spectral filter. In a fourth embodiment, alone or in combination with one or more of the first to third embodiments, at least one first spectral filter comprises a plurality of spatially distributed first spectral filters to allow orientation determination based on light passing through the plurality of first spectral filters. In a fifth embodiment, alone or in combination with one or more of the first to fourth embodiments, the condition relates to whether the sensor is parallel to the surface of the measurement target. In a sixth embodiment, alone or in combination with one or more of the first to fifth embodiments, at least one first spectral filter comprises a plurality of spectral filters. The sensor device can perform time-of-flight measurements for multiple wavelengths corresponding to the plurality of spectral filters. In a seventh embodiment, alone or in combination with one or more of the first to sixth embodiments, the condition relates to a threshold distance between the sensor device and the measurement target.

[0064] although Figure 6 An example block of process 600 is shown, but in some implementations, process 600 may include... Figure 6 Compared to the blocks depicted in the diagram, there may be additional blocks, fewer blocks, different blocks, or blocks with different arrangements. Alternatively or concurrently, two or more blocks of process 600 may be executed.

[0065] Figure 7 This is a flowchart of an example process 700 for performing spectral measurements based on time-of-flight measurements. In some implementations, Figure 7 One or more process blocks can be executed by a sensor device (e.g., the sensor device of FIG. 1, sensor device 320, and / or other types). In some embodiments, Figure 7 One or more process blocks may be executed by another device or a group of devices that are separate from or include the sensor device, such as a control device (e.g., control device 310).

[0066] like Figure 7 As shown, process 700 may include determining a time-of-flight measurement by performing sensor sampling based on light received via at least one first spectral filter, wherein the at least one first spectral filter is associated with a spectral range for the time-of-flight measurement (block 710). For example, a sensor device (e.g., using processor 125, processor 420, sensor 115, and / or other types) may perform sensor sampling and determine the time-of-flight measurement based on light received via at least one first spectral filter. In some embodiments, the at least one first spectral filter may be a ToF filter (e.g., ToF filter 110), as described in more detail elsewhere herein. In some embodiments, the sensor device may include at least one second spectral filter. In some embodiments, at least one first spectral filter is associated with a spectral range for the time-of-flight measurement, and at least one second spectral filter is associated with a spectral range for the spectral measurement.

[0067] like Figure 7 As further shown, process 700 may include determining that a condition for the time-of-flight measurement is met, wherein the condition relates to the orientation or position of the sensor or sensor device relative to the measurement target (block 720). For example, the sensor device (e.g., using processor 125 or processor 420) may determine that a condition for the ToF measurement is met. This condition may relate to the orientation or position of the sensor or sensor device relative to the measurement target.

[0068] like Figure 7As further shown, process 700 may include triggering a spectral measurement to be performed (block 730) based on determining that a condition relating to the Time-of-Flight (ToF) measurement is met. For example, a sensor device (e.g., using processor 125 or processor 420) may trigger the spectral measurement to be performed. The sensor device may trigger the spectral measurement to be performed based on determining that a condition relating to the ToF measurement is met.

[0069] like Figure 7 As further shown, process 700 may include performing a spectral measurement on the measurement target based on light received via at least one second spectral filter and by performing sensor sampling, based on conditions regarding the time-of-flight measurement being met (block 740). For example, a sensor device (e.g., using processor 125, processor 420, sensor 115, etc.) may perform sensor sampling and may perform a spectral measurement based on light received via at least one second spectral filter. The sensor device may perform a spectral measurement using a sensor. The sensor device may perform a spectral measurement based on conditions regarding the ToF measurement being met.

[0070] Process 700 may include additional implementations, such as any single implementation or any combination of implementations of one or more other processes described below and / or elsewhere herein.

[0071] In a first embodiment, the sensor device can determine pixel values ​​in at least one region of the sensor corresponding to at least one first spectral filter; determine that the pixel values ​​match a pattern associated with time-of-flight measurement; and determine a time-of-flight measurement value based on the pixel values. In a second embodiment, either alone or in combination with the first embodiment, the spectral measurement is based on the near-infrared (NIR) wavelength range.

[0072] although Figure 7 An example block of process 700 is shown, but in some implementations, process 700 may include... Figure 7 The blocks described herein may include additional blocks, fewer blocks, different blocks, or blocks with different arrangements. Alternatively or concurrently, two or more blocks of process 700 may be executed.

[0073] The foregoing disclosure provides illustrations and descriptions, but is not intended to be exhaustive or to limit implementation to the precise forms disclosed. Modifications or variations can be made based on the foregoing disclosure or obtained from practice of the embodiments.

[0074] As used herein, the term “component” is intended to be interpreted broadly as hardware, firmware, and / or a combination of hardware and software.

[0075] As used in this article, depending on the context, satisfying the threshold can refer to a value greater than the threshold, exceeding the threshold, higher than the threshold, greater than or equal to the threshold, less than the threshold, slightly less than the threshold, lower than the threshold, less than or equal to the threshold, equal to the threshold, etc.

[0076] It is evident that the systems and / or methods described herein can be implemented in various forms of hardware, firmware, and / or combinations of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods is not limited to the embodiments described herein. Therefore, while the operation and behavior of the systems and / or methods are described herein without reference to specific software code, it should be understood that software and hardware can be designed to implement systems and / or methods based on those described herein.

[0077] Although specific combinations of features are stated in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of various embodiments. In fact, many of these features can be combined in ways not specifically stated in the claims and / or not disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of various embodiments includes combinations of each dependent claim with every other claim in the claim set.

[0078] No element, operation, or instruction used herein should be construed as critical or essential unless explicitly described as such. Furthermore, as used herein, "a" is intended to include one or more items and may be used interchangeably with "one or more". Additionally, as used herein, the term "set" is intended to include one or more items (e.g., related items, unrelated items, combinations of related items and / or unrelated items, etc.) and may be used interchangeably. If only one item is intended to be used, the term "only one" or similar language is used. Furthermore, as used herein, the term "having" is intended to be an open-ended term. Furthermore, unless explicitly stated otherwise, the phrase "based on" is intended to mean "at least partially based on".

Claims

1. A sensor device, comprising: a sensor; at least one first spectral filter and at least one second spectral filter, wherein the at least one first spectral filter is associated with a spectral range for a time-of-flight measurement, and wherein the at least one second spectral filter is associated with a spectral range for a spectral measurement; and one or more processors: determine, using the sensor, the time-of-flight measurement based on light received via the at least one first spectral filter; determine that a condition with respect to the time-of-flight measurement is satisfied, wherein the condition relates to an orientation or a position of the sensor or the sensor device relative to a measurement target; based on determining that the condition with respect to the time-of-flight measurement is satisfied, trigger the spectral measurement to be performed; perform, using the sensor, and based on light received via the at least one second spectral filter, the spectral measurement on the measurement target based on the condition with respect to the time-of-flight measurement being satisfied; and provide information identifying the spectral measurement.

2. The sensor device of claim 1, wherein the at least one first spectral filter comprises a plurality of first spectral filters in a plane with the at least one second spectral filter.

3. The sensor device of claim 1, wherein the at least one first spectral filter comprises a plurality of first spectral filters spatially distributed to allow the orientation to be determined based on light passing via the plurality of first spectral filters.

4. The sensor device of claim 1, wherein the time-of-flight measurement is a first time-of-flight measurement, and wherein the one or more processors further: determine, after the spectral measurement, a second time-of-flight measurement; and based on the second time-of-flight measurement, determine a velocity, or an updated orientation or position of the sensor device.

5. The sensor device of claim 1, wherein the at least one first spectral filter comprises a single spectral filter, and wherein the orientation or the position is determined based on light passing via the single spectral filter.

6. The sensor device of claim 1, wherein the one or more processors further: based on the time-of-flight measurement, modify the spectral measurement.

7. The sensor device of claim 1, wherein in determining the time-of-flight measurement, the one or more processors are to: obtain a first sample of data from the sensor; and wherein the one or more processors, in performing the spectral measurement, are to: based on the spectral measurement being triggered, obtain a second sample of data from the sensor.

8. The sensor device of claim 7, wherein the first sample is spaced less than ten milliseconds from the second sample.

9. The sensor device of claim 7, wherein the first sample is associated with one or more first pixel regions of the sensor, and the second sample is associated with one or more second pixel regions of the sensor.

10. A method, comprising: performing, by a sensor device and using a sensor, a time-of-flight measurement based on light received via at least one first spectral filter, wherein the at least one first spectral filter is associated with a spectral range used for the time-of-flight measurement; determining, by the sensor device, that a condition is fulfilled with respect to the time-of-flight measurement, wherein the condition relates to an orientation or a position of the sensor or the sensor device relative to a measurement target; performing, by the sensor device, a spectral measurement on the measurement target using the sensor and based on light received via the at least one second spectral filter based on the condition being fulfilled with respect to the time-of-flight measurement; and providing, by the sensor device, information identifying the spectral measurement.

11. The method of claim 10, wherein the light received via the at least one first spectral filter and the light received via the at least one second spectral filter are from the same light source.

12. The method of claim 10, wherein the light received via the at least one first spectral filter and the light received via the at least one second spectral filter are from different light sources.

13. The method of claim 10, wherein the at least one first spectral filter comprises a plurality of first spectral filters in a plane with the at least one second spectral filter.

14. The method of claim 10, wherein the at least one first spectral filter comprises a plurality of first spectral filters that are spatially distributed to allow determining the orientation based on light passing via the plurality of first spectral filters.

15. The method of claim 10, wherein the condition relates to whether the sensor is parallel to a surface of the measurement target.

16. The method of claim 10, wherein the at least one first spectral filter comprises a plurality of spectral filters, and wherein performing the time-of-flight measurement further comprises: performing the time-of-flight measurement for a plurality of wavelengths corresponding to the plurality of spectral filters.

17. The method of claim 10, wherein the condition relates to a threshold distance between the sensor device and the measurement target.

18. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors of a sensor device, cause the one or more processors to: determine a time-of-flight measurement by performing sampling of a sensor based on light received via at least one first spectral filter, wherein the at least one first spectral filter is associated with a spectral range used for the time-of-flight measurement; determine that a condition is fulfilled with respect to the time-of-flight measurement, wherein the condition relates to an orientation or a position of the sensor or the sensor device relative to a measurement target; trigger a spectral measurement to be performed based on determining that the condition is fulfilled with respect to the time-of-flight measurement; and provide information identifying the spectral measurement. performing a sampling of the sensor based on light received via at least one second spectral filter, and based on the conditions being satisfied with respect to the time-of-flight measurement, performing the spectral measurement for the measurement target.

19. The non-transitory computer-readable medium of claim 18, wherein the one or more instructions that cause the one or more processors to determine the time-of-flight measurement further cause the one or more processors to: determine a pixel value in at least one region of the sensor corresponding to the at least one first spectral filter; determine that the pixel value matches a pattern associated with the time-of-flight measurement; and determine the time-of-flight measurement based on the pixel value.

20. The non-transitory computer-readable medium of claim 18, wherein the spectral measurement is based on a visible wavelength range or a near-infrared wavelength range.

21. A method comprising: determining, by a device comprising a component, that one or more conditions with respect to a time-of-flight measurement are satisfied, wherein the one or more conditions relate to an orientation or positioning of the device or the component of the device relative to a measurement target; performing, by the device, a spectral measurement for the measurement target based on determining that the one or more conditions with respect to the time-of-flight measurement are satisfied; and performing, by the device, one or more actions based on the spectral measurement.

22. The method of claim 21, wherein the component comprises a sensor, and wherein performing the spectral measurement comprises: performing the spectral measurement based on determining that the one or more conditions with respect to the time-of-flight measurement are satisfied and based on a sample of the sensor or a region of the sensor.

23. The method of claim 21, further comprising: determining image data for the spectral measurement; wherein performing the spectral measurement comprises: analyzing the image data to determine the spectral measurement.

24. The method of claim 21, wherein the spectral measurement relates to one or more of: a spectroscopic characteristic of the measurement target, or a chemical component of the measurement target.

25. The method of claim 21, wherein performing the one or more actions comprises: determining a characteristic of a person based on the spectral measurement.

26. The method of claim 21, further comprising: determining that the time-of-flight measurement or another time-of-flight measurement indicates an orientation offset from the measurement target; wherein performing the one or more actions comprises: adjusting the spectral measurement by applying a transform to the spectral measurement to improve accuracy in the orientation offset.

27. The method of claim 21, wherein performing the one or more actions comprises: determining a velocity or speed of the device or a sensor of the device, wherein performing the one or more actions comprises: adjusting the spectral measurement based on the velocity or speed.

28. The method of claim 21, wherein performing the one or more actions comprises: determining a different time-of-flight measurement after the spectral measurement is performed; wherein the different time-of-flight measurement indicates whether the sensor of the device was removed too quickly from the particular condition of the spectral measurement.

29. The method of claim 21, wherein the device is a sensor device; and wherein the time-of-flight measurement is a time-of-flight measurement of the sensor device.

30. A device comprising: a sensor; and one or more processors configured to: determine that one or more conditions are satisfied with respect to a time-of-flight measurement, wherein the one or more conditions relate to an orientation or positioning of the sensor or the device relative to a measurement target; perform a spectral measurement for the measurement target based on determining that the one or more conditions are satisfied with respect to the time-of-flight measurement; and perform one or more actions based on the spectral measurement.

31. The device of claim 30, wherein the one or more processors are further configured to: determine image data for the spectral measurement based on a sample of the sensor or the sensor region, wherein when performing the spectral measurement, the one or more processors are configured to: analyze the image data to determine the spectral measurement.

32. The device of claim 30, wherein the one or more processors are further configured to: determine that the time-of-flight measurement or another time-of-flight measurement indicates an orientation offset from the measurement target, wherein when performing the one or more actions, the one or more processors are configured to: adjust the spectral measurement by applying a transformation to the spectral measurement to improve accuracy in the orientation offset.

33. The device of claim 30, wherein when performing the one or more actions, the one or more processors are configured to: determine a velocity or speed of the device, or a velocity or speed of a sensor of the device; wherein when performing the one or more actions, the one or more processors are configured to: adjust the spectral measurement based on the velocity or speed.

34. The device of claim 30, wherein when performing the one or more actions, the one or more processors are configured to: determine a different time-of-flight measurement after performing the spectral measurement; wherein the different time-of-flight measurement indicates whether the sensor was removed too quickly from the particular condition of the spectral measurement.

35. The device of claim 30, wherein the time-of-flight measurement is a time-of-flight measurement of the device.

36. A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising: one or more instructions that, when executed by one or more processors of a device, cause the device to: determine that one or more conditions are satisfied with respect to a time-of-flight measurement, wherein the one or more conditions relate to an orientation or positioning relative to a measurement target; perform a spectral measurement for the measurement target based on the one or more conditions being satisfied with respect to the time-of-flight measurement; and perform one or more actions based on the spectral measurement.

37. The non-transitory computer-readable medium of claim 36, wherein the one or more instructions that, when executed by the one or more processors, cause the device to: determine image data for the spectral measurement based on a sample of the sensor or the sensor region, wherein when performing the spectral measurement, the one or more instructions that, when executed by the one or more processors, cause the device to: analyze the image data to determine the spectral measurement.

38. The non-transitory computer-readable medium of claim 36, wherein the one or more instructions that, when executed by the one or more processors, cause the device to: determine that the time-of-flight measurement or another time-of-flight measurement indicates an orientation offset from the measurement target, wherein when performing the one or more actions, the one or more instructions that, when executed by the one or more processors, cause the device to: adjust the spectral measurement by applying a transformation to the spectral measurement to improve accuracy in the orientation offset.

39. The non-transitory computer-readable medium of claim 36, wherein when performing the one or more actions, the one or more instructions that, when executed by the one or more processors, cause the device to: determine a velocity or speed of the device, or a velocity or speed of a sensor of the device; wherein when performing the one or more actions, the one or more instructions that, when executed by the one or more processors, cause the device to: adjust the spectral measurement based on the velocity or speed.

40. The non-transitory computer-readable medium of claim 36, wherein when performing the one or more actions, the one or more instructions that, when executed by the one or more processors, cause the device to: determine a different time-of-flight measurement after performing the spectral measurement; wherein the different time-of-flight measurement indicates whether the sensor was removed too quickly from the particular condition of the spectral measurement.

37. The non-transitory computer-readable medium of claim 36, wherein the spectral measurement is further performed based on a sample of a sensor of the device or a region of the sensor.

38. The non-transitory computer-readable medium of claim 36, wherein the one or more instructions further cause the device to: determine image data for the spectral measurement; wherein the one or more instructions that cause the device to perform the spectral measurement cause the device to: analyze the image data to determine the spectral measurement.

39. The non-transitory computer-readable medium of claim 36, wherein the one or more instructions further cause the device to: determine that the time-of-flight measurement or another time-of-flight measurement indicates an orientation offset from the measurement target, wherein the one or more instructions that cause the device to perform the one or more actions cause the device to: adjust the spectral measurement by applying a transform to the spectral measurement to improve accuracy in the orientation offset.

40. The non-transitory computer-readable medium of claim 36, wherein the one or more instructions that cause the device to perform the one or more actions cause the device to: determine a velocity or speed of the device or a velocity or speed of a sensor of the device; wherein the one or more instructions that cause the device to perform the one or more actions cause the device to: adjust the spectral measurement based on the velocity or speed.

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