WO2017012505A1 - 自动行走设备 - Google Patents

自动行走设备 Download PDF

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Publication number
WO2017012505A1
WO2017012505A1 PCT/CN2016/090127 CN2016090127W WO2017012505A1 WO 2017012505 A1 WO2017012505 A1 WO 2017012505A1 CN 2016090127 W CN2016090127 W CN 2016090127W WO 2017012505 A1 WO2017012505 A1 WO 2017012505A1
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WO
WIPO (PCT)
Prior art keywords
vegetation
module
information
camera
heating
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2016/090127
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English (en)
French (fr)
Inventor
杜江
孙根
饶越
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Positec Power Tools Suzhou Co Ltd
Original Assignee
Positec Power Tools Suzhou Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from CN201520565150.7U external-priority patent/CN204925588U/zh
Application filed by Positec Power Tools Suzhou Co Ltd filed Critical Positec Power Tools Suzhou Co Ltd
Priority to EP16827196.3A priority Critical patent/EP3327500B1/en
Priority to US15/745,602 priority patent/US10691000B2/en
Publication of WO2017012505A1 publication Critical patent/WO2017012505A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/50—Constructional details
    • H04N23/52—Elements optimising image sensor operation, e.g. for electromagnetic interference [EMI] protection or temperature control by heat transfer or cooling elements
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03B—APPARATUS OR ARRANGEMENTS FOR TAKING PHOTOGRAPHS OR FOR PROJECTING OR VIEWING THEM; APPARATUS OR ARRANGEMENTS EMPLOYING ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ACCESSORIES THEREFOR
    • G03B17/00—Details of cameras or camera bodies; Accessories therefor
    • G03B17/55—Details of cameras or camera bodies; Accessories therefor with provision for heating or cooling, e.g. in aircraft
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Program-control systems
    • G05B19/02—Program-control systems electric
    • G05B19/04—Program control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Program control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R11/00—Arrangements for holding or mounting articles, not otherwise provided for
    • B60R11/04—Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
    • H—ELECTRICITY
    • H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
    • H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
    • H05B3/00—Ohmic-resistance heating
    • H05B3/84—Heating arrangements specially adapted for transparent or reflecting areas, e.g. for demisting or de-icing windows, mirrors or vehicle windshields

Definitions

  • the present invention relates to an autonomous walking device, and more particularly to an imaging heating device for an automatic walking device.
  • the camera device is usually installed on the automatic walking device.
  • the camera device can observe the environment around the automatic walking device in real time to prevent accidental collision or other accidents in the automatic walking device.
  • the camera device since the automatic walking equipment often works in an external environment, the camera device is susceptible to weather and geographical environment, resulting in abnormal operation of the camera device. For example, if the camera is operating in a rain or snow or a humid environment, the camera may condense water mist, affecting the camera function, and the like.
  • the normal growth of vegetation has an important impact on the environment. In the normal growing season of vegetation, it is necessary to judge the growth condition of the vegetation in time and find out whether the growth of the vegetation is normal, so as to treat the vegetation accordingly, including watering, fertilizing or adding trace particles.
  • the tradition is mainly to identify the health of the vegetation by the naked eye, which is obviously not accurate enough.
  • the vegetation grows normally, even if there are some undesirable growth phenomena, the overall change is not large, so it is difficult to identify it by the naked eye.
  • the early stage of poor growth of vegetation if it can not be judged, with the growth of vegetation, the subsequent growth problems will be treated again, which will be obviously not conducive to the healthy growth of vegetation.
  • Artificial identification of the growth of vegetation requires the caregiver to have a strong knowledge of vegetation, further increasing the difficulty of manual identification.
  • An automatic walking device includes a camera and an image heating device, and the image heating device includes a heating module that heats a lens of the camera to remove water mist on the lens.
  • the image capturing heating device further includes a transparent cover disposed outside the camera, the heating module being mounted inside the transparent cover, located at a side of the camera and in close proximity to the camera.
  • the transparent cover is a glass transparent cover or a plastic transparent cover.
  • the heating module includes a resistance wire that is coupled to a battery in the autonomous walking device.
  • the resistance wire is externally provided with a thermally conductive insulator.
  • a thermal conductive sheet is disposed on the lens of the camera, and the thermal conductive sheet is connected to the electric resistance wire.
  • the resistance wire is a continuously curved resistance wire.
  • the continuously curved resistance wire is a horizontally and vertically curved resistance wire.
  • the resistance wire has at least one.
  • a temperature sensor is further disposed in the transparent cover, and the temperature sensor is connected to a controller in the automatic walking device.
  • the heating module is located on or in the camera.
  • a wiper member is also included, the wiper member controllably erasing water mist on the lens.
  • a controller is further included, the controller controlling the heating module to heat or stop heating.
  • a sensor for detecting environmental information in the vicinity of the camera is further included, the sensor transmitting the detected environmental information to the controller, and the controller controls the heating module to heat according to whether the environmental information meets a preset condition. Or stop heating.
  • the senor is a temperature sensor, a humidity sensor, and a rain sensor. At least one of the devices.
  • a communication module is further included, the communication module receiving climate information and transmitting to the controller, the controller controlling the heating module to heat or stop heating according to whether the climate information satisfies a preset condition.
  • a clock module is further included, and the clock module records time information and sends the information to the controller, and the controller controls the heating module to heat or stop heating according to whether the time information satisfies a preset condition.
  • an identification system including a vegetation health condition
  • the vegetation health status identification system includes: an acquisition module, configured to acquire image information of the vegetation; and an extraction module, configured to extract a color of the corresponding vegetation from the image information a value, the color value is an RGB value of the vegetation; and an identification module configured to compare the RGB value of the vegetation with a color value of the healthy growth of the vegetation to identify whether the vegetation is healthy.
  • the acquisition module is a near infrared camera.
  • a vegetation health reminding module is further included, and the vegetation health reminding module sends information about whether the vegetation is healthy and/or vegetation maintenance suggestion information to the user.
  • the vegetation health reminding module includes a communication module, and the communication module communicates with the user personal smart device to transmit information about whether the vegetation is healthy and/or vegetation maintenance suggestion information to the user's personal smart device. .
  • the information on whether the vegetation is healthy includes an area where the vegetation is located, and a vegetation health level and/or a vegetation disease type of the area; the vegetation conservation suggestion information includes recommended fertilization, watering, loosening, weeding At least one of the medicines.
  • a vegetation conservation module is further included, the vegetation conservation module performing a vegetation conservation action on an unhealthy vegetation area.
  • the vegetation maintenance module comprises at least one of a fertilization module, a watering module, a loose soil module, a weeding module, and a sprinkling module.
  • the above-mentioned automatic heating device of the automatic walking device can effectively prevent the influence of dust and other pollutants on the camera head, and improve the imaging effect; the resistance wire is provided, and in the rain or snow or the wet and cold environment, the resistance wire can be used to heat the camera. The temperature prevents the camera from freezing or water mist and improves the camera effect.
  • a method for identifying vegetation health status of an automatic walking device comprising:
  • the RGB value of the vegetation is compared with the color value of the healthy growth of the vegetation to identify whether the vegetation is healthy.
  • the near infrared camera is used to acquire image information of the vegetation.
  • the Weber local feature algorithm is used to extract the color values of the corresponding vegetation from the image information.
  • the identifying method further includes:
  • the RGB values of the vegetation are filtered to filter out the RGB values of the vegetation color from the RGB values of the vegetation.
  • the RGB values of the vegetation are filtered by determining whether the RGB values of the vegetation are within a predetermined interval.
  • the predetermined interval includes RGB values of the vegetation in both healthy and non-healthy conditions.
  • the color value of the healthy growth of the vegetation is an interval corresponding to the R, G, and B values, and comparing the RGB value of the vegetation with the color value of the healthy growth of the vegetation, respectively comparing the Whether the values of R, G, and B in the RGB values of the vegetation are in the interval corresponding to the R, G, and B values.
  • the method further includes the steps of: transmitting information on whether the vegetation is healthy to the user, and/or transmitting vegetation conservation suggestion information to the user.
  • the information on whether the vegetation is healthy includes an area where the vegetation is located, and a vegetation health level and/or a vegetation disease type of the area; the vegetation conservation suggestion information includes recommended fertilization, watering, loosening, weeding At least one of the medicines.
  • the method further includes the step of performing a vegetation conservation action on an unhealthy region of the vegetation.
  • the vegetation conservation action comprises at least one of fertilization, watering, loosening, weeding, and spraying.
  • An automatic walking device comprising an identification system for vegetation health status, said vegetation health status knowledge
  • the system includes: an acquisition module for acquiring image information of the vegetation;
  • An extraction module configured to extract, from the image information, a color value of the corresponding vegetation, where the color value is an RGB value of the vegetation;
  • the identification module is configured to compare the RGB value of the vegetation with the color value of the healthy growth of the vegetation to identify whether the vegetation is healthy.
  • the acquisition module is a near infrared camera.
  • the extraction module extracts the color value of the corresponding vegetation from the image information by using a Weber local feature algorithm.
  • the identification system further includes:
  • a filtering module for filtering the RGB values of the vegetation, and filtering the RGB values of the vegetation color from the RGB values of the vegetation.
  • the filtering module filters the RGB values of the vegetation by determining whether the RGB values of the vegetation are within a preset interval.
  • the predetermined interval includes RGB values of the vegetation in both healthy and non-healthy conditions.
  • the color value of the healthy growth of the vegetation is an interval corresponding to the R, G, and B values
  • the identification module compares the RGB value of the vegetation with the color value of the healthy growth of the vegetation, respectively. Whether the values of R, G, and B in the RGB values of the vegetation are in the interval of the corresponding R, G, and B values.
  • a vegetation health reminding module is further included, and the vegetation health reminding module sends information about whether the vegetation is healthy and/or vegetation maintenance suggestion information to the user.
  • the vegetation health reminding module includes a communication module, and the communication module communicates with the user personal smart device to transmit information about whether the vegetation is healthy and/or vegetation maintenance suggestion information to the user's personal smart device. .
  • the information on whether the vegetation is healthy includes an area where the vegetation is located, and a vegetation health level and/or a vegetation disease type of the area; the vegetation conservation suggestion information includes recommended fertilization, watering, loosening, weeding At least one of the medicines.
  • a vegetation conservation module is further included, the vegetation conservation module is not vegetation Healthy areas perform vegetation conservation actions.
  • the vegetation maintenance module comprises at least one of a fertilization module, a watering module, a loose soil module, a weeding module, and a sprinkling module.
  • the above-mentioned method and system for identifying vegetation health conditions extracts RGB values of vegetation from image information, determines vegetation growth status, improves efficiency and accuracy of judgment, and timely identifies whether vegetation growth is healthy and can be unhealthy in vegetation. Take appropriate treatment measures.
  • FIG. 1 is a structural view of an image pickup heating apparatus of an automatic traveling apparatus according to an embodiment
  • FIG. 2 is a structural view of the automatic traveling apparatus after the image heating device is mounted.
  • FIG. 3 is a flow chart showing a method for identifying a vegetation health condition according to an embodiment
  • Figure 4 is a schematic view showing a near infrared camera mounted on a lawn mower
  • FIG. 5 is a flowchart of a method for identifying a vegetation health condition of an automatic walking device according to another embodiment
  • FIG. 6 is a structural diagram of a vegetation health condition recognition system of an automatic walking device according to an embodiment
  • Fig. 7 is a structural diagram of a vegetation health condition recognition system of an automatic walking apparatus according to another embodiment.
  • Figure 8 is a block diagram of an automatic walking apparatus of another embodiment.
  • the image pickup heating device 2 of the automatic traveling apparatus of an embodiment includes a transparent cover 3 provided outside the camera 4.
  • a heating module 5 is mounted inside the transparent cover 3. The heating module 5 is in close proximity to the camera 4 and is located on the side of the camera 4.
  • the installation of the camera 4 on the automatic walking device 1 includes two purposes, one is to acquire image information of the surrounding environment, thereby analyzing the image information; and the other is that the automatic walking device 1 needs to complete the work task through the camera 4. Therefore, the autonomous walking device 1 can install the camera 4 of different pixel levels according to different situations.
  • the camera can be installed with a normal camera or an HD camera.
  • the camera 4 in order to facilitate collection of image information, it can be installed at the front position of the autonomous walking apparatus 1, as shown in FIG.
  • the transparent cover 3 should have good transparency, and the degree of transparency cannot affect the imaging effect of the camera.
  • the transparent cover 3 also needs to take into consideration that the resistance wire does not have thermal expansion and contraction when heated. Otherwise, the size of the transparent cover 3 is liable to be unstable, and the image acquired by the camera 4 is blurred.
  • the transparent cover 3 takes the glass transparent cover as the priority, and the transparent glass cover is transparent enough to ensure the imaging effect.
  • a plastic transparent cover can also be used to fully reduce the cost.
  • the heating module 5 includes a resistance wire.
  • the resistance wire can be separately powered, or can be connected to the battery in the moving device 1 to obtain power. If the resistance wire is separately powered, it is necessary to provide a separate power supply battery, which may be disposed in the transparent cover 3 or in the automatic walking device 1. When the power supply battery is disposed in the automatic traveling device 1, the power supply battery can be connected to the resistance wire through a connecting wire.
  • the resistance wire can be designed as a continuously curved resistance wire.
  • the curved resistance wire may be obliquely bent or otherwise bent, but the resistance wire which is linearly bent in the horizontal and vertical directions is more likely to equalize the generated heat, and the area of the resistance wire which generates heat is larger, and the specific shape is as shown in FIG.
  • the resistance wires may be connected in parallel with one or more.
  • a heat conductive sheet may be disposed on the lens, and the heat conductive sheet may be connected to the resistance wire.
  • the setting of the thermal pad can not affect the camera effect of the lens.
  • the thermal pad is not easy to be a rustable metal object, otherwise it will easily lead to rust, and the adhesion of the rust to the transparent cover will easily affect the camera effect of the camera. Therefore, when selecting a material, the thermal conductive sheet needs to select a material that has good thermal conductivity but is not easily rusted.
  • a temperature sensor may also be provided inside the transparent cover 3, and the temperature sensor is connected to a controller in the automatic walking device 1.
  • the temperature sensor can transmit the obtained temperature to the controller in real time, and the controller can automatically detect the temperature in the transparent cover 3. If the temperature is too low, water mist may occur, and the controller can automatically control the battery in the automatic walking device 1. Power is supplied to the resistance wire to heat the resistance wire, raising the temperature in the transparent cover 3, and removing water mist which may be generated by the lens in the camera 4.
  • the temperature sensor is obtained When the temperature is too high, when the controller detects that the temperature is too high, it can control the battery to stop supplying power to the resistance wire, so that the resistance wire stops heating.
  • the temperature sensor automatically controls the temperature in the transparent cover 3 to automatically remove the water mist phenomenon that may occur in the camera 4.
  • the control of heating the resistance wire can also be actively controlled by human operation.
  • the heating module is a hot air device comprising a resistance wire and a blowing mechanism, the hot air device having at least one air outlet facing the lens.
  • the heating module of the image capture heating device is disposed directly on the camera or inside the camera to be closer to the lens, reducing heat loss.
  • the heating module is a resistance wire
  • the resistance wire is embedded in the lens mount or directly embedded in the lens.
  • the image pickup heating device includes a transparent cover, the resistance wire is also disposed in the vicinity of the lens cover or in the lens cover.
  • the autonomous vehicle further includes a wiper member that can controllably wipe the water mist on the lens.
  • the wiper blade is driven by a separate small motor to move back and forth, wiping the lens.
  • the shape of the wiper member may be a rod shape, a sheet shape, or the like, and the number may be one or two, and will not be described again.
  • the combination of the wiper and the heating module can speed up the removal of water mist and water traces, and is especially useful under severe conditions such as heavy rain.
  • the wiper member is further disposed on the lens cover to wipe the water on the lens cover.
  • the heating and stopping of heating of the heating device are controlled by the temperature sensor and the controller.
  • the sensor may be of other types, such as a humidity sensor, a rain sensor, etc., or at least two combinations of a temperature sensor, a humidity sensor, and a rain sensor.
  • the sensor is located near the camera, detects environmental information near the camera and sends it to the controller.
  • the controller controls whether the heating module heats or stops heating according to whether the environmental information meets the preset condition. This preset condition represents whether there is a water mist on the lens.
  • the controller controls the heating module to heat when the ambient humidity is greater than a preset value, and controls the heating module to stop heating when the ambient humidity is less than a preset value; or the controller is in an ambient humidity greater than a preset value.
  • the heating module is controlled to heat for a preset length of time, the heating is stopped.
  • the controller controls the heating module to heat when the sensor detects rain, and controls the heating module to stop heating after the rain stops. If the autonomous walking equipment includes For multiple types of sensors, if the environmental information detected by any sensor means that the lens may have water mist, the controller controls the heating module to heat up.
  • the controller controls The heating module stops heating.
  • the preset condition of the controller integrates information sent back by different sensors to determine whether the lens has water mist, wherein the controller can assign different weights to information detected by different sensors. .
  • the autonomous vehicle further includes a communication module that receives the climate information and transmits to the controller, the controller controlling the heating module to heat or stop heating according to whether the climate information satisfies a preset condition.
  • the communication module is connected to the Internet or other information source to obtain climate information, and the climate information may be one or more of real-time weather information, future weather forecast, and historical weather statistics of the current region.
  • the controller determines that the lens or the transparent cover may have water, and then starts heating module heating.
  • the communication module can be a well-known module such as a WIFI module, a cellular communication module, a Zigbee module, a Bluetooth module, an RF module, and the like, and will not be described again.
  • the autonomous walking apparatus further includes a clock module that records time information and transmits the time information to the controller, the controller controlling the heating module to heat or stop heating according to whether the time information satisfies a preset condition. For example, the controller starts the heating module heating when the fog is heavy in the morning, such as 6-8 am.
  • the autonomous vehicle 1 can be a lawn mower.
  • the mower can be used to obtain the growth of the grass in the lawn in real time, and automatically carry out the mowing operation when the grass is relatively high. It is also possible to observe and record the place where the operation has been carried out while mowing the grass.
  • the grass is used for mowing. Since the lawn mower often performs mowing work outside, if the camera 4 is separately installed, the camera 4 is liable to cause water mist when the weather or the working environment changes, resulting in poor imaging performance. Therefore, as shown in FIG. 2, the image pickup heating device 2 can be installed at the front position of the lawn mower, and the purpose of improving the image pickup effect in the above embodiment can be achieved by the heating device 2.
  • the automatic walking device 1 may be a lawn mower or other equipment. This embodiment only describes the lawn mower as a specific object, and is not limited to the protection of the lawn mower, which is an automatic walking device. Devices for the automatic walking function are all within the scope of the present invention.
  • the above image heating device of the automatic walking device sets the camera in a transparent cover, which can effectively prevent Stop the influence of dust and other pollutants on the camera head, and improve the camera effect;
  • the transparent cover is provided with a resistance wire.
  • the resistance wire can be used to heat the camera to prevent the camera from freezing or water. The fog phenomenon improves the camera effect.
  • the method for identifying the vegetation health condition of the autonomous walking apparatus of an embodiment includes steps S120 to S160. This embodiment can be combined with the foregoing embodiments to form an overall solution.
  • step S120 image information of the vegetation is acquired. It is judged whether the vegetation is healthy by whether the color of the vegetation is normal or not. Since the color is composed of three color channels of R, G and B, the three color values of R, G and B of the vegetation can be analyzed to identify the health of the vegetation. situation.
  • the color of the vegetation can be captured by a near-infrared camera.
  • the near-infrared camera can be installed on the automatic walking device. For example, if the user wants to observe the growth state of the lawn, the near-infrared camera can be installed on the lawn mower. As shown in Fig.
  • a near-infrared camera 7 can be mounted in front of the autonomous walking device 1, here specifically a lawn mower, which can be connected to a controller 9 mounted in the mower casing.
  • the near-infrared camera may be the same as the camera in the foregoing embodiment, or may be independently provided.
  • a separate imaging heating device can be provided for it, and the specific structure is as described in the previous embodiment.
  • the mower When the mower is in motion, it can control the work of the near-infrared camera 7, and timely obtain the image information of the vegetation in the whole lawn, so as to timely determine whether the vegetation in the lawn is healthy.
  • the near-infrared camera 7 is sensitive to electromagnetic waves having a wavelength in the range of 780 to 3000 nm, and can effectively acquire image information of vegetation, and is a vegetation-specific digital image forming apparatus.
  • the performance of the NIR camera 7 is stable and reliable and easy to install. It can be easily installed on the lawn mower.
  • the camera is compact and hard to damage. It has a long working time and can be used in a poor environment. It can be used continuously for 24 hours. Imaging work. This is an impossible task for manpower.
  • the near-infrared camera is progressive scan imaging, and the output is bare data.
  • the spectral range is wide and the imaging quality is very high, which is suitable for imaging vegetation.
  • the lawn mower described above is only one of the automatic walking devices, and other devices may adopt the same or similar methods. For example, an infrared camera or the like may be installed on a car that observes the growth state of the forest.
  • the color value of the corresponding vegetation is extracted from the image information, and the color value is the RGB value of the vegetation.
  • the RGB values in the image can be extracted from the image information acquired by the near-infrared camera, and the extracted algorithms have various types, which can be SIFT (scale invariant feature conversion), SURF (speeded up robust features), DAISY (DAISY is a fast-calculable partial map for dense feature extraction) Like feature description), Haar (rectangular feature), WLD (Weber local feature), LBP (Local Binary Patterns), ORB (a binary feature descriptor), BRIEF (a feature descriptor) , LDA-hash (a feature descriptor), MSER (Maximally Stable External Regions), HOG (Histogram of Oriented Gradient), gray value, color histogram, gray histogram, Algorithms such as gray moments.
  • SIFT scale invariant feature conversion
  • SURF speeded up robust features
  • DAISY DAISY is a fast-calc
  • the WLD (Weber Local Feature) algorithm can be selected to extract the color value of the corresponding vegetation from the image information.
  • the WLD algorithm can effectively obtain local information in the image, and the obtained local information is more accurate, and can more effectively determine whether the specific parts of the vegetation (such as branches, leaves, etc.) grow normally.
  • step S160 the RGB value of the vegetation is compared with the color value of the healthy growth of the vegetation to identify whether the vegetation is healthy.
  • the color values of the healthy growth of the vegetation are the corresponding values of R, G, and B. Data of color values at the time of healthy growth of the vegetation can be stored in advance.
  • the color value of the healthy growth of the vegetation is not necessarily fixed, and the change of conditions such as different moisture content may cause a corresponding change in the color value. Therefore, the pre-stored vegetation has a color value corresponding to the R, G, and B. The value can be a reasonable interval.
  • the controller 9 in the lawn mower can set a memory to store the color value when the vegetation grows healthily, the controller 9 sets an algorithm processing program, and extracts the color value in the image information according to step S140. Step S160 is further performed by program control to automatically identify whether the vegetation is healthy.
  • Setting the memory in the autonomous walking device is only one of the achievable modes, and the processor may separately set the processing of the image information, including performing step S140 and step S160. It is also possible to set up a memory in a separate processor to store the color values when the vegetation grows healthily.
  • the above method for identifying the health status of the vegetation extracts the RGB value of the vegetation from the image information, determines the growth state of the vegetation, improves the efficiency and the accuracy of the judgment, and timely identifies whether the vegetation growth is healthy, and can be adopted when the vegetation is unhealthy.
  • the corresponding treatment measures are the RGB value of the vegetation from the image information, determines the growth state of the vegetation, improves the efficiency and the accuracy of the judgment, and timely identifies whether the vegetation growth is healthy, and can be adopted when the vegetation is unhealthy.
  • the method for identifying the vegetation health condition of the automatic walking device of another embodiment further includes step S150.
  • This embodiment can be combined with the foregoing embodiments to form an overall solution.
  • step S150 the RGB values of the vegetation are filtered, and the RGB values of the vegetation color are filtered out from the RGB values of the vegetation.
  • the near-infrared camera acquires a variety of image information, which may include sky images, obstacles, or other images. Therefore, the RGB values extracted from the image information are also different, and the RGB values that are not belonging to the vegetation are directly recognized by the step S160, the operation time is long, and the processing performance of the junction controller has high requirements. Therefore, the RGB values of the vegetation can be filtered to eliminate the RGB values of non-plants.
  • the RGB value of the vegetation can be compared with the preset interval to determine whether the RGB value of the vegetation is in a preset interval. If not, the non-vegetation RGB value can be directly removed from it.
  • the preset interval should include the RGB values of the vegetation under healthy and non-healthy conditions, so as to ensure that the data is not deleted and the integrity of the data is maintained.
  • the method for identifying the vegetation health condition of the autonomous walking apparatus of another embodiment further includes steps S170 and S180.
  • This embodiment can be combined with the foregoing embodiments to form an overall solution.
  • Step S170 Send information about whether the vegetation is healthy to the user. Specifically, information on whether the vegetation is healthy includes the area where the vegetation is located, and the level of vegetation health and/or vegetation type in the area.
  • the information is sent graphically to personal smart devices held by the user, such as smart phones, smart tablets, smart watches, personal computers, and the like.
  • the graphical information may be in the form of a user's garden or lawn map on which the vegetation health level and/or vegetation type of each region is indicated in the form of colors, text, icons. For example, green, yellow, and red are used to indicate that the vegetation is in good health, medium, and poor; the text or icon indicates the lack of water, lack of fertilizer, need for loose soil, pests and diseases, etc.; The value of the sign, etc.
  • other forms of expression are also feasible.
  • the information is sent to the user's smart device in the form of a garden health report, which may be by mail, short message, or the like.
  • the Garden Health Report lists the health of the garden in categories and areas, such as the overall health status of the vegetation in each area, pest and disease conditions, water status, nutrient status, and trace elements.
  • the information on whether the vegetation is healthy is presented on the local device of the autonomous walking device, for example, displayed on the display screen of the autonomous walking device, or broadcasted in a sound form or the like.
  • the specific content of the information and the presentation form are similar to the previous embodiments, and details are not described herein.
  • step S180 the vegetation maintenance suggestion information is sent to the user.
  • Specific, vegetation conservation advice information It includes at least one of recommended fertilization, watering, loosening, weeding, and spraying.
  • the vegetation maintenance suggestion information may also be sent to the user's personal device in a graphical or report form, such as prompting the user to perform a specific area in a manner of combining one or more of a map and an extension, a text, and an icon. Watering, fertilization, etc., will not be repeated here.
  • step S170 and step S180 may also have only one of them.
  • the method for identifying the vegetation health condition of the automatic walking device of another embodiment further includes step S190.
  • step S190 a vegetation conservation action is performed on an area where the vegetation is unhealthy.
  • the vegetation conservation action includes at least one of fertilization, watering, loosening, weeding, and spraying.
  • the automatic walking device performs one or more maintenance actions according to the specific health problems of the detected vegetation. For example, when the automatic walking device detects the lack of water in the vegetation, the watering action is performed; when the automatic walking device detects that the vegetation lacks the nutrient, the fertilizing, loosening or weeding action is performed; when the automatic walking device detects the vegetation encountering the pests and diseases, the execution is performed. Sprinkle the action.
  • the vegetation health status identification system of an embodiment includes an acquisition module 120, an extraction module 140, and an identification module 160. This embodiment can be combined with the foregoing embodiments to form an overall solution.
  • the obtaining module 120 is configured to acquire image information of the vegetation. It is judged whether the vegetation is healthy by whether the color of the vegetation is normal or not. Since the color is composed of three color channels of R, G and B, the three color values of R, G and B of the vegetation can be analyzed to identify the health of the vegetation. situation.
  • the color of the vegetation can be captured by a near-infrared camera.
  • the near-infrared camera can be installed on the automatic walking device. For example, if the user wants to observe the growth state of the lawn, the near-infrared camera can be installed in the automatic walking device 1 . For the lawn mower, as shown in Fig.
  • a near-infrared camera 7 can be mounted in front of the lawn mower, and the near-infrared camera 7 can be coupled to a controller 9 mounted in the lawn mower casing. When the mower is in motion, it can control the work of the near-infrared camera 7, and timely obtain the image information of the vegetation in the whole lawn, so as to timely determine whether the vegetation in the lawn is healthy.
  • the near-infrared camera 7 is sensitive to electromagnetic waves having a wavelength in the range of 780 to 3000 nm, and can effectively acquire image information of vegetation, and is a vegetation-specific digital image forming apparatus.
  • the performance of the NIR camera 7 is stable and reliable and easy to install. It can be easily installed on the lawn mower.
  • the camera is compact and hard to damage.
  • NIR camera is progressive scan imaging and output It is bare data, its spectral range is wide, and the quality of imaging is very high, which is more suitable for imaging vegetation.
  • the lawn mower described above is only one of the automatic walking devices, and other devices may adopt the same or similar methods.
  • an infrared camera or the like may be installed on a car that observes the growth state of the forest.
  • the extraction module 140 is configured to extract a color value of the corresponding vegetation from the image information, and the color value is an RGB value of the vegetation.
  • the RGB values in the image can be extracted from the image information acquired by the near-infrared camera, and the extracted algorithms have various types, which can be SIFT (scale invariant feature conversion), SURF (speeded up robust features), DAISY (DAISY is a fast-calculating local image feature descriptor for dense feature extraction), Haar (rectangular feature), WLD (Weber local feature), LBP (Local Binary Patterns), ORB (a type II) Value feature descriptor), BRIEF (a feature descriptor), LDA-hash (a feature descriptor), MSER (Maximally Stable External Regions), HOG (Histogram of Oriented Gradient) , gray value, color histogram, gray histogram, gray moment and other algorithms.
  • SIFT scale invariant feature conversion
  • SURF speeded up robust features
  • DAISY DAISY is
  • the WLD (Weber Local Feature) algorithm can be selected to extract the color value of the corresponding vegetation from the image information.
  • the WLD algorithm can effectively obtain local information in the image, and the obtained local information is more accurate, and can more effectively determine whether the specific parts of the vegetation (such as branches, leaves, etc.) grow normally.
  • the identification module 160 is configured to compare the RGB values of the vegetation with the color values of the healthy growth of the vegetation to identify whether the vegetation is healthy.
  • the color values of the healthy growth of the vegetation are the corresponding values of R, G, and B.
  • Data of color values at the time of healthy growth of the vegetation can be stored in advance.
  • the color value of the healthy growth of the vegetation is not necessarily fixed, and the change of conditions such as different moisture content may cause a corresponding change in the color value. Therefore, the pre-stored vegetation has a color value corresponding to the R, G, and B. The value can be a reasonable interval.
  • the controller 9 in the lawn mower can set a memory to store the color value when the vegetation grows healthily, the controller 9 sets an algorithm processing program, and extracts the color value in the image information according to step S140.
  • Step S160 is further performed by program control to automatically identify whether the vegetation is healthy. Setting up memory in an autonomous walking device is just one way to achieve it, or Processing the image information by separately setting the processor includes performing steps S140 and S160. It is also possible to set up a memory in a separate processor to store the color values when the vegetation grows healthily.
  • the above-mentioned vegetation health status identification system extracts the RGB value of the vegetation from the image information, determines the growth state of the vegetation, improves the efficiency and the accuracy of the judgment, and timely identifies whether the vegetation growth is healthy, and can be adopted when the vegetation is unhealthy.
  • the corresponding treatment measures extracts the RGB value of the vegetation from the image information, determines the growth state of the vegetation, improves the efficiency and the accuracy of the judgment, and timely identifies whether the vegetation growth is healthy, and can be adopted when the vegetation is unhealthy.
  • the vegetation health status identification system of another embodiment further includes a filtering module 150.
  • This embodiment can be combined with the foregoing embodiments to form an overall solution.
  • the filtering module 150 is configured to filter the RGB values of the vegetation, and filter the RGB values of the vegetation color from the RGB values of the vegetation.
  • the near-infrared camera acquires a variety of image information, which may include sky images, obstacles, or other images. Therefore, the RGB values extracted from the image information are also different, and the RGB values that are not belonging to the vegetation are directly recognized by the step S160, the operation time is long, and the processing performance of the junction controller has high requirements. Therefore, the RGB values of the vegetation can be filtered to eliminate the RGB values of non-plants.
  • the RGB value of the vegetation can be compared with the preset interval to determine whether the RGB value of the vegetation is in a preset interval. If not, the non-vegetation RGB value can be directly removed from it.
  • the preset interval should include the RGB values of the vegetation under healthy and non-healthy conditions, so as to ensure that the data is not deleted and the integrity of the data is maintained.
  • the auto-traveling apparatus of another embodiment further includes a vegetation health reminding module 170, and the vegetation health reminding module 170 transmits information about whether the vegetation is healthy to the user.
  • information on whether the vegetation is healthy includes the area where the vegetation is located, and the level of vegetation health and/or vegetation type in the area.
  • the vegetation health reminding module 170 includes a communication module, and the communication module communicates with the user personal smart device to send information about whether the aforementioned vegetation is healthy to the user's personal smart device, such as a smart phone, smart Tablets, smart watches, personal computers, etc.
  • the information on whether the vegetation is healthy is sent to the personal smart device held by the user in a graphical form
  • the imaged information may be in the form of a user's garden or lawn map, in the form of color, text, or icon.
  • other forms of expression are also feasible.
  • the information is sent to the user's smart device in the form of a garden health report, which may be by mail, short message, or the like.
  • the Garden Health Report lists the health of the garden in categories and areas, such as the overall health status of the vegetation in each area, pest and disease conditions, water status, nutrient status, and trace elements.
  • the vegetation health reminding module 170 includes a health indicating device located on the local machine, the health indicating device presenting information on whether the vegetation is healthy on the local device of the automatic walking device, for example, a health instruction
  • the device can be a display screen, a broadcaster, or the like. The specific content of the information and the presentation form are similar to the previous embodiments, and details are not described herein.
  • the health reminder module also sends vegetation conservation advice information to the user.
  • the vegetation conservation suggestion information includes at least one of recommended fertilization, watering, loosening, weeding, and spraying.
  • the vegetation conservation suggestion information can also be sent to the user's personal device in the form of a graphic or report, such as a combination of one or more of a map and an extension, a text, and an icon to prompt the user to perform a specific area. Water, fertilization and other actions are not repeated here.
  • the health alert module may only send one of information on whether the vegetation is healthy and vegetation conservation advice information.
  • the method for identifying the vegetation health condition of the autonomous vehicle 1 of another embodiment further includes a vegetation maintenance module 180.
  • the vegetation conservation module 180 performs vegetation conservation actions on areas where the vegetation is unhealthy. Specifically, the vegetation conservation action includes: at least one of fertilization, watering, loosening, weeding, and spraying.
  • the vegetation curing module includes: a fertilization module, a watering module, a loose soil module, a weeding module, and a medicine. At least one of the modules.
  • the automatic walking device 1 performs one or more maintenance actions correspondingly according to the specific health problems of the detected vegetation. For example, when the automatic walking device 1 detects that the vegetation lacks water, the watering action is performed; when the automatic walking device detects that the vegetation lacks nutrients, performing the fertilization, loosening or weeding action; when the automatic walking device detects the vegetation encountering pests and diseases, Perform the spraying action.
  • One or more of the vegetation maintenance modules 180 may be an accessory that is replaceably mounted on the autonomous walking device, and when the automatic walking device detects that a specific maintenance action needs to be performed, if the corresponding specific accessory is not installed on the body, Automatically pick up this particular attachment for maintenance or send a reminder Information, prompting the user to install the specific maintenance attachment for it.
  • a positioning device is installed on the automatic walking device 1 to associate the regional geographical location information with the vegetation health state information as a basis for generating the aforementioned various types of information and performing various types of actions.
  • the positioning device can be a GPS device (such as a DGPS device), a UWB high-precision positioning device, an image position recognition device, and the like.

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Abstract

本发明涉及一种自动行走设备，包括摄像仪、以及摄像加热装置，所述摄像加热装置包括加热模块，所述加热模块给摄像仪的镜头加热以去除镜头上的水雾。本发明可有效防止摄像仪出现结冰或者水雾现象，提高摄像效果。

Description

自动行走设备 技术领域
本发明涉及自动行走设备，特别是涉及一种自动行走设备的摄像加热装置。
背景技术
随着科学技术的发展，智能的自动行走设备为人们所熟知，由于自动行走设备可以自动预先根据设置的程序执行预先设置的相关任务，无须人为的操作与干预，因此在工业应用及家居产品上的应用非常广泛。工业上的应用如执行各种功能的机器人，家居产品上的应用如割草机、吸尘器等，这些智能的自动行走设备极大地节省了人们的时间，给工业生产及家居生活都带来了极大的便利。
自动行走设备上通常也会安装摄像装置，通过摄像装置可以实时观察自动行走设备周围的环境，防止自动行走设备发生误撞或者其它事故。但由于自动行走设备经常工作在外部环境当中，摄像装置容易受到天气及地理上环境的影响，导致摄像装置工作异常。例如，摄像装置如果工作在雨雪或湿冷环境中，摄像装置可能会凝结水雾，影响摄像功能等。
此外，植被的正常生长对于环境具有重要影响。在植被正常的生长季节，需要及时判断植被的生长状况，发现植被的生长是否正常，从而对植被进行相应治疗，包括浇水、施肥或者添加微量粒子等。
传统主要是通过肉眼识别植被的健康状况，这种方法明显不够准确。植被在正常生长时，即使有某些不良的生长现象，但由于整体的变化并不大，因此，很难以肉眼的方式识别出来。在植被生长的不良初期如果无法判断识别出来，随着植被的生长，后续生长问题严重时再进行治疗，会明显不利于植被的健康生长。人工识别植被的生长状况，需要看护人具有较强的植被专业知识，进一步加大了人工识别的难度。
此外，即使识别出某些植被的健康情况不好，目前仍然需要用户手动进行养护，这样就带来两个弊端，首先，养护工作耗时费力，用户觉得麻烦，第二，若用户并非植物专家，往往不知如何养护来改善植物的健康状态。
发明内容
基于此，有必要提供一种自动行走设备的摄像加热装置，解决摄像装置如果工作在雨雪或湿冷环境中，可能会凝结水雾，影响摄像功能的问题。
一种自动行走设备，包括摄像仪、以及摄像加热装置，所述摄像加热装置包括加热模块，所述加热模块给摄像仪的镜头加热以去除镜头上的水雾。
在其中一个实施例中，所述摄像加热装置还包括在摄像仪外部设置的透明罩，所述加热模块安装于所述透明罩内部，位于所述摄像仪的侧部并紧邻所述摄像仪。
在其中一个实施例中，所述透明罩为玻璃透明罩或塑料透明罩。
在其中一个实施例中，所述加热模块包括电阻丝，所述电阻丝与所述自动行走设备中的电池连接。
在其中一个实施例中，所述电阻丝外部设置有导热绝缘体。
在其中一个实施例中，所述摄像仪的镜头上设置上导热片，所述导热片与所述电阻丝连接。
在其中一个实施例中，所述电阻丝为连续弯曲状电阻丝。
在其中一个实施例中，所述连续弯曲状电阻丝为横竖弯曲状电阻丝。
在其中一个实施例中，所述电阻丝至少具有一个。
在其中一个实施例中，所述透明罩内还设置有温度传感器，所述温度传感器与所述自动行走设备中的控制器连接。
在其中一个实施例中，所述加热模块位于所述摄像仪上或者内部。
在其中一个实施例中，还包括雨刮件，所述雨刮件可控地擦除所述镜头上的水雾。
在其中一个实施例中，还包括控制器，所述控制器控制所述加热模块加热或停止加热。
在其中一个实施例中，还包括检测摄像仪附近环境信息的传感器，所述传感器将检测的环境信息发送给控制器，所述控制器根据环境信息是否满足预设条件，控制所述加热模块加热或停止加热。
在其中一个实施例中，所述传感器为温度传感器、湿度传感器、雨淋传感 器中的至少一个。
在其中一个实施例中，还包括通信模块，所述通信模块接收气候信息并发送给控制器，所述控制器根据气候信息是否满足预设条件，控制所述加热模块加热或停止加热。
在其中一个实施例中，还包括时钟模块，所述时钟模块记录时间信息并发送给控制器，所述控制器根据时间信息是否满足预设条件，控制加热模块加热或停止加热。
在其中一个实施例中，包括植被健康状况的识别系统，所述植被健康状况识别系统包括：获取模块，用于获取植被的图像信息；提取模块，用于从图像信息中提取出对应植被的颜色值，所述颜色值为植被的RGB值；识别模块，用于将所述植被的RGB值与植被健康生长时的颜色值进行对比识别植被是否健康。
在其中一个实施例中，所述获取模块为近红外相机。
在其中一个实施例中，还包括植被健康提醒模块，所述植被健康提醒模块将植被是否健康的信息和/或植被养护建议信息发送给用户。
在其中一个实施例中，所述植被健康提醒模块包括通信模块，所述通信模块和用户个人智能设备通信，以将前述植被是否健康的信息和/或植被养护建议信息发送到用户个人智能设备上。
在其中一个实施例中，所述植被是否健康的信息包括植被所在区域，以及该区域的植被健康水平和/或植被病害类型；所述植被养护建议信息包括建议施肥、浇水、松土、除草、洒药中的至少一种。
在其中一个实施例中，还包括植被养护模块，所述植被养护模块对植被不健康的区域执行植被养护动作。
在其中一个实施例中，所述植被养护模块包括：施肥模块、浇水模块、松土模块、除草模块、洒药模块中的至少一种。
以上所述自动行走设备的摄像加热装置，可有效防止灰尘等污染物对摄影头的影响，提高摄像效果；设置有电阻丝，在雨雪或湿冷环境，可采用电阻丝加热，提高摄像仪的温度，防止摄像仪出现结冰或者水雾现象，提高摄像效果。
基于此，有必要提供一种自动化的园艺用自动行走设备及其制备健康状态 识别方法，及时识别植被生长是否健康。
一种自动行走设备的植被健康状况识别方法，包括：
获取植被的图像信息；
从图像信息中提取出对应植被的颜色值，所述颜色值为植被的RGB值；
将植被的RGB值与植被健康生长时的颜色值进行对比识别植被是否健康。
在其中一个实施例中，采用近红外相机获取植被的图像信息。
在其中一个实施例中，采用韦伯局部特征算法从图像信息中提取出对应植被的颜色值。
在其中一个实施例中，所述识别方法还包括：
对植被的RGB值进行过滤，从植被的RGB值中过滤剔除非植被颜色的RGB值。
在其中一个实施例中，通过判断植被的RGB值是否在预设的区间对植被的RGB值进行过滤。
在其中一个实施例中，所述预设的区间包括植被在健康和非健康状况时RGB值。
在其中一个实施例中，所述植被健康生长时的颜色值为对应R、G和B值的区间，所述将植被的RGB值与植被健康生长时的颜色值进行对比时，分别对比所述植被的RGB值中的R、G和B的值是否在所述对应R、G和B值的区间。
在其中一个实施例中，还包括以下步骤：将植被是否健康的信息发送给用户，和/或将植被养护建议信息发送给用户。
在其中一个实施例中，所述植被是否健康的信息包括植被所在区域，以及该区域的植被健康水平和/或植被病害类型；所述植被养护建议信息包括建议施肥、浇水、松土、除草、洒药中的至少一种。
在其中一个实施例中，还包括以下步骤：对植被不健康的区域执行植被养护动作。
在其中一个实施例中，所述植被养护动作包括：施肥、浇水、松土、除草、洒药中的至少一种。
一种自动行走设备，包括植被健康状况的识别系统，所述植被健康状况识 别系统包括：获取模块，用于获取植被的图像信息；
提取模块，用于从图像信息中提取出对应植被的颜色值，所述颜色值为植被的RGB值；
识别模块，用于将植被的RGB值与植被健康生长时的颜色值进行对比识别植被是否健康。
在其中一个实施例中，所述获取模块为近红外相机。
在其中一个实施例中，所述提取模块采用韦伯局部特征算法从图像信息中提取出对应植被的颜色值。
在其中一个实施例中，所述识别系统还包括：
过滤模块，用于对植被的RGB值进行过滤，从植被的RGB值中过滤剔除非植被颜色的RGB值。
在其中一个实施例中，所述过滤模块通过判断植被的RGB值是否在预设的区间对植被的RGB值进行过滤。
在其中一个实施例中，所述预设的区间包括植被在健康和非健康状况时RGB值。
在其中一个实施例中，所述植被健康生长时的颜色值为对应R、G和B值的区间，所述识别模块将植被的RGB值与植被健康生长时的颜色值进行对比时，分别对比所述植被的RGB值中的R、G和B的值是否在所述对应R、G和B值的区间。
在其中一个实施例中，还包括植被健康提醒模块，所述植被健康提醒模块将植被是否健康的信息和/或植被养护建议信息发送给用户。
在其中一个实施例中，所述植被健康提醒模块包括通信模块，所述通信模块和用户个人智能设备通信，以将前述植被是否健康的信息和/或植被养护建议信息发送到用户个人智能设备上。
在其中一个实施例中，所述植被是否健康的信息包括植被所在区域，以及该区域的植被健康水平和/或植被病害类型；所述植被养护建议信息包括建议施肥、浇水、松土、除草、洒药中的至少一种。
在其中一个实施例中，还包括植被养护模块，所述植被养护模块对植被不 健康的区域执行植被养护动作。
在其中一个实施例中，所述植被养护模块包括：施肥模块、浇水模块、松土模块、除草模块、洒药模块中的至少一种。
以上所述植被健康状况的识别方法及系统，从图像信息中提取出植被的RGB值，判断植被的生长状况，提高了效率和判断的准确率；及时的识别植被生长是否健康，可以在植被不健康时采取相应的治疗措施。
附图说明
图1为一实施例的自动行走设备的摄像加热装置的结构图；
图2为自动行走设备安装摄像加热装置后的结构图。
图3为一实施例的植被健康状况的识别方法的流程图；
图4为近红外相机安装在割草机上的示意图；
图5为另一实施例的自动行走设备的植被健康状况识别方法的流程图；
图6为一实施例的自动行走设备的植被健康状况识别系统的结构图；
图7为另一实施例的自动行走设备的植被健康状况识别系统的结构图。
图8为另一实施例的自动行走设备的模块图。
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
如图1和图2所示，一实施例的自动行走设备的摄像加热装置2包括在摄像仪4外部设置的透明罩3。透明罩3内部安装有加热模块5。加热模块5紧邻摄像仪4并位于摄像仪4的侧部。
通常自动行走设备1上安装摄像仪4包括两种目的，一种是为了获取周围环境的图像信息，从而对图像信息进行分析；另一种是自动行走设备1需要通过摄像仪4完成工作任务。因此，自动行走设备1可以根据不同的情况安装不同像素级别的摄像仪4，例如，摄像仪可安装普通摄像头，也可以安装高清摄像头。摄像仪4在安装时，为利于收集图像信息，可以安装在自动行走设备1的前部位置，如图2中所示。
透明罩3要具有良好的透明性，透明程度不能影响摄像仪的成像效果。透明罩3还需要兼顾电阻丝在加热时不能具有热胀冷缩的情况，否则，容易导致透明罩3大小不稳定，致使摄像仪4获取的图像模糊。在材料选择上，透明罩3以玻璃透明罩为优先，玻璃透明罩充分透明，可以保证成像效果，但在成像效果要求不高时，也可以采用塑料透明罩，以充分降低成本。
加热模块5包括有电阻丝，为方便提供电源，电阻丝可以采用单独供电，或者也可以通过与动行走设备1中的电池连接以获取电源。如果对电阻丝采取单独供电，需要设置单独的供电电池，该供电电池可以设置于透明罩3内，也可以设置于自动行走设备1中。供电电池设置于自动行走设备1中时，可以通过连接线将供电电池与电阻丝连接起来。
为了使电阻丝在加热时，使透明罩3内部均匀受热，快速地去除摄像仪4中镜头的水雾，如图1所示，可以将电阻丝设计为连续弯曲状电阻丝。弯曲状电阻丝可以是斜线弯曲或者其它弯曲方式，但采用横竖线性弯曲的电阻丝更容易使产生的热量均衡，且产生热量的电阻丝的面积更大，具体形状如图1中所示。根据透明罩3内部空间的大小，电阻丝可以并联有一个或者一个以上。
为了防止电阻丝加热可能出现的不良情况，需要在电阻丝的外部设置导热绝缘体。设置绝缘体可以防止透明罩3内部的水气凝结在电阻丝上，导致可能发生的短路情况。
为了更快速地给摄像仪4的镜头加热去除水雾，可以在镜头上设置导热片，并将导热片与电阻丝连接。导热片的设置不能影响镜头的摄像效果，导热片不易为可生锈的金属物，否则容易导致生锈，而锈滓粘附于透明罩则容易影响摄像仪的摄像效果。因此，导热片在选择材料时，需要选择导热性能好，但又不容易生锈的材料。
透明罩3内部还可以设置温度传感器，温度传感器与自动行走设备1中的控制器连接。温度传感器可以实时将获得的温度传递给控制器，控制器可以自动检测透明罩3内的温度，如果温度过低，则有可能产生水雾现象，控制器可以自动控制自动行走设备1中的电池向电阻丝提供电源，使电阻丝加热，升高透明罩3中的温度，去除摄像仪4中的镜头可能产生的水雾。当温度传感器获 取的温度过高时，控制器检测到温度过高时，则可以控制电池停止向电阻丝提供电源，使电阻丝停止加热。通过温度传感器实现对透明罩3中温度自动控制，自动清除摄像仪4可能产生的水雾现象。对电阻丝进行加热的控制，也可以由人为操作主动控制。以上只是本发明中的一种实施例，本发明不限于其它类似或相同的实现方式。
在另一实施例中，加热模块为热风装置，包括电阻丝和吹风机构，热风装置至少有一个吹风口朝向镜头。
在另一实施例中，摄像加热装置的加热模块直接设置在摄像仪上或者摄像仪内部，以更加靠近镜头，减少热量散失。例如，加热模块为电阻丝时，电阻丝嵌入式的装配在镜头安装座中、或者直接嵌入式的安装在镜头中。在本实施例中，若摄像加热装置包括透明罩，则电阻丝还设置在镜头罩附近或者镜头罩中。
在另一实施例中，自动行走设备还包括雨刮件，雨刮件能够可控的擦除镜头上的水雾。雨刮件由单独的小电机驱动而来回移动，擦拭镜头。雨刮件的形状可以为杆状、片状等，数量可以为一个、两个，不再赘述。雨刮件和加热模块配合工作，能够加快水雾、水迹的去除速度，在大雨等恶劣工况下尤为实用。在本实施例中，若摄像加热装置包括透明罩，则雨刮件还设置在镜头罩上，以擦除镜头罩上的水。
在之前实施例中，已经提及通过温度传感器和控制器控制加热装置的启动加热和停止加热。在另一实施例中，传感器可以为其他类型，例如湿度传感器、雨淋传感器等，或者温度传感器、湿度传感器和雨淋传感器的至少两个组合。传感器位于摄像仪附近，检测摄像仪附近的环境信息并发送给控制器，控制器根据环境信息是否满足预设条件，控制加热模块加热或者停止加热。该预设条件代表镜头上是否存在水雾。例如，在传感器为湿度传感器时，控制器在环境湿度大于预设值时，控制加热模块加热，在环境湿度小于预设值时，控制加热模块停止加热；或者控制器在环境湿度大于预设值时控制加热模块加热预设时间长度后停止加热。在传感器为雨淋传感器时，控制器在传感器检测到下雨时，控制加热模块加热，在雨停后，控制加热模块停止加热。若自动行走设备包括 多个类型的传感器，则任一传感器检测到的环境信息代表镜头可能有水雾时，控制器控制加热模块加热，在所有传感器检测到的环境信息都代表镜头应无水雾时，控制器控制加热模块停止加热。或者，若自动行走设备包括多个类型的传感器，控制器的预设条件综合不同的传感器发回的信息，判断镜头是否有水雾，其中，控制器可为不同传感器检测的信息分配不同的权重。
在另一实施例中，自动行走设备还包括通信模块，通信模块接收气候信息并发送给控制器，所述控制器根据气候信息是否满足预设条件，控制所述加热模块加热或停止加热。通信模块连接到互联网或者其他信息源以获取气候信息，气候信息可以为当前地区的实时天气信息、未来天气预报、历史天气统计数据中的一种或者多种。在气候信息表示当前有雨、或者湿度很高、雾气重、容易结霜等时，控制器判断镜头或者透明罩可能有水，则启动加热模块加热。通信模块可以为WIFI模块、蜂窝通信模块、Zigbee模块、蓝牙模块、RF模块等业内周知的模块，不再赘述。
在另一实施例中，自动行走设备还包括时钟模块，所述时钟模块记录时间信息并发送给控制器，所述控制器根据时间信息是否满足预设条件，控制加热模块加热或停止加热。例如，控制器在清晨雾气浓重的时候，如早上6点-8点，启动加热模块加热。
如图2所示，自动行走设备1可以是割草机。割草机安装摄像仪4可以实时获取草坪中草的生长情况，在草比较高的时侯自动进行割草作业；也可以在割草的同时，观察记录已经作业过的地方，对未进行割草作业的地方进行割草作业。由于割草机经常在外面进行割草作业，因此，如果单独安装摄像仪4则容易导致摄像仪4在天气或工作环境变化时产生水雾现象，导致摄像效果较差。因此，如图2中所示，可以在割草机的前部位置安装摄像加热装置2，通过加热装置2即可实现以上本实施例中提高摄像效果的目的。
自动行走设备1可以是割草机，也可以是其它的设备，本实施例只是将割草机作为具体的一种对象进行说明，并不限于保护割草机这一种自动行走设备，凡具有自动行走功能的设备均在本发明的保护范围之内。
以上自动行走设备的摄像加热装置，将摄像仪设置于透明罩内，可有效防 止灰尘等污染物对摄影头的影响，提高摄像效果；透明罩内设置有电阻丝，在雨雪或湿冷环境，可采用电阻丝加热，提高摄像仪的温度，防止摄像仪出现结冰或者水雾现象，提高摄像效果。
如图3所示，一实施例的自动行走设备的植被健康状况的识别方法包括步骤S120至步骤S160。本实施例可以与前述实施例组合而形成整体方案。
步骤S120，获取植被的图像信息。通过植被在生长时的颜色是否正常即可判断植被是否健康，由于颜色由R、G、B三种颜色通道组成，因此，分析植被的R、G、B三种颜色值即可识别植被的健康状况。植被的颜色可以由近红外相机拍摄获取。通常在采集植被的图像信息时，人为的操作比较费时费力，可以将近红外相机安装在自动行走设备上，比如，用户如果要观察草坪的生长状况，可以将近红外相机安装在割草机上，如图4所示，可以在自动行走设备1，此处具体为割草机的前方安装近红外相机7，近红外相机7可以与安装在割草机外壳中的控制器9连接。近红外相机与前述实施例中的摄像仪可以为同一个，也可以分别独立设置。在近红外相机7独立设置时，可以为其设置单独的摄像加热装置，具体结构如前实施例所述。割草机在运动时，可以控制近红外相机7工作，及时获取整个草坪中植被的图像信息，从而及时判断草坪中的植被是否健康。近红外相机7对波长在780～3000nm范围的电磁波感应敏感，可有效获取植被的图像信息，是一种植被专用的数字图像成像设备。近红外相机7的性能稳定可靠且易于安装，可方便的安装于割草机上；相机结构紧凑结实不易损坏，连续工作时间长，可在较差的环境下使用，可以连续二十四小时不间断成像工作。这对于人工来说，是一种不可能实现的任务。近红外相机是逐行扫描成像，且输出的是裸数据，其光谱范围较宽，成像的质量非常高，较宜适合对植被进行成像。以上所述割草机只是自动行走设备中的一种，其它设备也可以采取相同或相近的做法，比如，可以在观察林林生长状况的汽车上安装红外相机等。
步骤S140，从图像信息中提取出对应植被的颜色值，颜色值为植被的RGB值。从近红外相机获取的图像信息中可以提取出图像中的RGB值，提取的算法具有多种，可以是SIFT(尺度不变特征转换)、SURF(speeded up robust features，快速鲁棒性特征)、DAISY(DAISY是面向稠密特征提取的可快速计算的局部图 像特征描述子)、Haar(矩形特征)、WLD(韦伯局部特征)、LBP(Local Binary Patterns，局部二值模式)、ORB(一种二值特征描述子)、BRIEF(一种特征描述子)、LDA-hash(一种特征描述子)、MSER(Maximally Stable External Regions，区域特征提取)、HOG(Histogram of Oriented Gradient，方向梯度直方图)、灰度值、颜色直方图、灰度直方图、灰度矩等算法。在此，可以选择WLD(韦伯局部特征)算法从图像信息中提取出对应植被的颜色值。WLD算法可有效获取图像中的局部信息，获取的局部信息更加准确，可以更有效的判断植被具体的部分(如枝、叶等)是否生长正常。
步骤S160，将植被的RGB值与植被健康生长时的颜色值进行对比识别植被是否健康。植被健康生长时的颜色值为对应的R、G和B的值。可以预先存储植被健康生长时的颜色值的数据。通常，植被健康生长时的颜色值并不一定是固定的，不同的水分含量等条件变化会导致颜色值相应的变化，因此，预先存储的植被健康生长时的颜色值对应的R、G和B的值可以是一个合理的区间。将植被的RGB值与植被健康生长时的颜色值进行对比时，分别对比植被的RGB值中的R、G和B的值是否在对应R、G和B值的区间即可。如果在对应的区间，说明植被生长健康，否则，说明生长可能有问题，可以分析植被生长出现了哪些问题，找出具体的原因，进行综合的治疗，使植被恢复正常，健康生长。如图4所示，可以在割草机中的控制器9设置存储器，将植被健康生长时的颜色值存储在其中，控制器9设置算法处理程序，根据步骤S140提取图像信息中的颜色值，并进一步通过程序控制执行步骤S160，从而自动化的识别植被是否健康。在自动行走设备中设置存储器只是可实现的方式的一种，也可以单独设置处理器对图像信息进行处理，包括执行步骤S140和步骤S160。也可以在单独的处理器中设置存储器，以存储植被健康生长时的颜色值。
以上所述植被健康状况的识别方法，从图像信息中提取出植被的RGB值，判断植被的生长状况，提高了效率和判断的准确率；及时的识别植被生长是否健康，可以在植被不健康时采取相应的治疗措施。
如图5所示，另一实施例的自动行走设备的植被健康状况的识别方法还包括步骤S150。本实施例可以与前述实施例组合而形成整体方案。
步骤S150，对植被的RGB值进行过滤，从植被的RGB值中过滤剔除非植被颜色的RGB值。近红外相机在获取植被的图像信息时，获取的图像信息多种多种，可能包括天空图像，障碍物，或者其它的图像等等。因此，从图像信息中提取出来的RGB值也不同，而不属于植被的RGB值如果直接由步骤S160判断识别，运算时间较长，且结控制器的处理性能具有较高的要求。因此，可以对植被的RGB值进行过滤，剔除其中非植物的RGB值。可以将植被的RGB值与预设的区间进行对比，判断植被的RGB值是否在预设的区间，如果不在，说明其非植被的RGB值，可以直接从中剔除。预设的区间应当包括植被在健康和非健康状况下的RGB值，这样可保证不误删除数据，保持数据的整体性。
另一实施例的自动行走设备的植被健康状况的识别方法还包括步骤S170和S180。本实施例可以与前述实施例组合而形成整体方案。
步骤S170，将植被是否健康的信息发送给用户。具体的，植被是否健康的信息包括植被所在区域，以及该区域的植被健康水平和/或植被病害类型。
在本实施例的一种实施方案中，该信息以图形化形式发送到用户持有的个人智能设备，如智能手机，智能平板电脑，智能手表，个人电脑等。该图像化信息可以为用户的花园或草坪地图形式，其上以颜色、文字、图标的形式标示出各个区域的植被健康水平和/或植被病害类型。如，以绿、黄、红分别标示植被健康状态好、中、差；以文字或图标标示相应区域的植被缺水、缺肥、需要松土、有病虫害等；以数值标示植物的各个健康指征的数值等。当然，其他的表现形式也是可行的。
在本实施例的另一种实施方案中，该信息以花园健康报告的形式发送给用户的智能设备，可以通过邮件、短消息等合适方式。花园健康报告分类别、区域列出花园的健康情况，例如各区域的植被的总体健康状态，病虫害情况、水分情况、养分情况、微量元素情况等等。
在本实施例的另一种实施方案中，植被是否健康的信息呈现于自动行走设备的本机上，例如，显示于自动行走设备的显示屏上，或者以声音形式播报等。信息具体内容以及呈现形式类似前面的实施方案，具体不再赘述。
步骤S180，将植被养护建议信息发送给用户。具体的，植被养护建议信息 包括建议施肥、浇水、松土、除草、洒药中的至少一种。类似步骤S170，植被养护建议信息也可以以图形化或者报告的形式发送到用户的个人设备，如以地图和延伸、文字、图标中的一种或多种结合的方式提示用户特定区域需要执行如浇水、施肥等动作等，在此不再赘述。
在可选的实施例中，步骤S170和步骤S180也可仅具有其中一个。
另一实施例的自动行走设备的植被健康状况的识别方法还包括步骤S190。
步骤S190，对植被不健康的区域执行植被养护动作。具体的，植被养护动作包括：施肥、浇水、松土、除草、洒药中的至少一种。
自动行走设备根据检测到的植被具体的健康问题，相应的执行一种或者多种养护动作。例如，当自动行走设备检测到植被缺水时，执行浇水动作；当自动行走设备检测到植被缺少养分时，执行施肥、松土或除草动作；当自动行走设备检测到植被遭遇病虫害时，执行洒药动作。
如图6所示，一实施例的植被健康状况的识别系统包括获取模块120、提取模块140和识别模块160。本实施例可以与前述实施例组合而形成整体方案。
获取模块120用于获取植被的图像信息。通过植被在生长时的颜色是否正常即可判断植被是否健康，由于颜色由R、G、B三种颜色通道组成，因此，分析植被的R、G、B三种颜色值即可识别植被的健康状况。植被的颜色可以由近红外相机拍摄获取。通常在采集植被的图像信息时，人为的操作比较费时费力，可以将近红外相机安装在自动行走设备上，比如，用户如果要观察草坪的生长状况，可以将近红外相机安装在自动行走设备1，具体为割草机上，如图4所示，可以在割草机的前方安装近红外相机7，近红外相机7可以与安装在割草机外壳中的控制器9连接。割草机在运动时，可以控制近红外相机7工作，及时获取整个草坪中植被的图像信息，从而及时判断草坪中的植被是否健康。近红外相机7对波长在780～3000nm范围的电磁波感应敏感，可有效获取植被的图像信息，是一种植被专用的数字图像成像设备。近红外相机7的性能稳定可靠且易于安装，可方便的安装于割草机上；相机结构紧凑结实不易损坏，连续工作时间长，可在较差的环境下使用，可以连续二十四小时不间断成像工作。这对于人工来说，是一种不可能实现的任务。近红外相机是逐行扫描成像，且输出的 是裸数据，其光谱范围较宽，成像的质量非常高，较宜适合对植被进行成像。以上所述割草机只是自动行走设备中的一种，其它设备也可以采取相同或相近的做法，比如，可以在观察林林生长状况的汽车上安装红外相机等。
提取模块140用于从图像信息中提取出对应植被的颜色值，颜色值为植被的RGB值。从近红外相机获取的图像信息中可以提取出图像中的RGB值，提取的算法具有多种，可以是SIFT(尺度不变特征转换)、SURF(speeded up robust features，快速鲁棒性特征)、DAISY(DAISY是面向稠密特征提取的可快速计算的局部图像特征描述子)、Haar(矩形特征)、WLD(韦伯局部特征)、LBP(Local Binary Patterns，局部二值模式)、ORB(一种二值特征描述子)、BRIEF(一种特征描述子)、LDA-hash(一种特征描述子)、MSER(Maximally Stable External Regions，区域特征提取)、HOG(Histogram of Oriented Gradient，方向梯度直方图)、灰度值、颜色直方图、灰度直方图、灰度矩等算法。在此，可以选择WLD(韦伯局部特征)算法从图像信息中提取出对应植被的颜色值。WLD算法可有效获取图像中的局部信息，获取的局部信息更加准确，可以更有效的判断植被具体的部分(如枝、叶等)是否生长正常。
识别模块160用于将植被的RGB值与植被健康生长时的颜色值进行对比识别植被是否健康。植被健康生长时的颜色值为对应的R、G和B的值。可以预先存储植被健康生长时的颜色值的数据。通常，植被健康生长时的颜色值并不一定是固定的，不同的水分含量等条件变化会导致颜色值相应的变化，因此，预先存储的植被健康生长时的颜色值对应的R、G和B的值可以是一个合理的区间。将植被的RGB值与植被健康生长时的颜色值进行对比时，分别对比植被的RGB值中的R、G和B的值是否在对应R、G和B值的区间即可。如果在对应的区间，说明植被生长健康，否则，说明生长可能有问题，可以分析植被生长出现了哪些问题，找出具体的原因，进行综合的治疗，使植被恢复正常，健康生长。如图4所示，可以在割草机中的控制器9设置存储器，将植被健康生长时的颜色值存储在其中，控制器9设置算法处理程序，根据步骤S140提取图像信息中的颜色值，并进一步通过程序控制执行步骤S160，从而自动化的识别植被是否健康。在自动行走设备中设置存储器只是可实现的方式的一种，也可 以单独设置处理器对图像信息进行处理，包括执行步骤S140和步骤S160。也可以在单独的处理器中设置存储器，以存储植被健康生长时的颜色值。
以上所述植被健康状况的识别系统，从图像信息中提取出植被的RGB值，判断植被的生长状况，提高了效率和判断的准确率；及时的识别植被生长是否健康，可以在植被不健康时采取相应的治疗措施。
如图7所示，另一实施例的植被健康状况的识别系统还包括过滤模块150。本实施例可以与前述实施例组合而形成整体方案。
过滤模块150用于对植被的RGB值进行过滤，从植被的RGB值中过滤剔除非植被颜色的RGB值。近红外相机在获取植被的图像信息时，获取的图像信息多种多种，可能包括天空图像，障碍物，或者其它的图像等等。因此，从图像信息中提取出来的RGB值也不同，而不属于植被的RGB值如果直接由步骤S160判断识别，运算时间较长，且结控制器的处理性能具有较高的要求。因此，可以对植被的RGB值进行过滤，剔除其中非植物的RGB值。可以将植被的RGB值与预设的区间进行对比，判断植被的RGB值是否在预设的区间，如果不在，说明其非植被的RGB值，可以直接从中剔除。预设的区间应当包括植被在健康和非健康状况下的RGB值，这样可保证不误删除数据，保持数据的整体性。
如图8，另一实施例的自动行走设备的还包括植被健康提醒模块170，植被健康提醒模块170将植被是否健康的信息发送给用户。具体的，植被是否健康的信息包括植被所在区域，以及该区域的植被健康水平和/或植被病害类型。本实施例可以与前述实施例组合而形成整体方案。
在本实施例的一种实施方案中，植被健康提醒模块170包括通信模块，通信模块和用户个人智能设备通信，以将前述植被是否健康的信息发送到用户个人智能设备上，如智能手机，智能平板电脑，智能手表，个人电脑等。
在一种实施方案中，植被是否健康的信息以图形化形式发送到用户持有的个人智能设备，该图像化信息可以为用户的花园或草坪地图形式，其上以颜色、文字、图标的形式标示出各个区域的植被健康水平和/或植被病害类型。如，以绿、黄、红分别标示植被健康状态好、中、差；以文字或图标标示相应区域的植被缺水、缺肥、需要松土、有病虫害等；以数值标示植物的各个健康指征的 数值等。当然，其他的表现形式也是可行的。
在本实施例的另一种实施方案中，该信息以花园健康报告的形式发送给用户的智能设备，可以通过邮件、短消息等合适方式。花园健康报告分类别、区域列出花园的健康情况，例如各区域的植被的总体健康状态，病虫害情况、水分情况、养分情况、微量元素情况等等。
在本实施例的另一种实施方案中，植被健康提醒模块170包括位于本机上的健康指示装置，健康指示装置将植被是否健康的信息呈现于自动行走设备的本机上，例如，健康指示装置可以为显示屏，播音器等。信息具体内容以及呈现形式类似前面的实施方案，具体不再赘述。
健康提醒模块还将植被养护建议信息发送给用户。具体的，植被养护建议信息包括建议施肥、浇水、松土、除草、洒药中的至少一种。类似的，植被养护建议信息也可以以图形化或者报告的形式发送到用户的个人设备，如以地图和延伸、文字、图标中的一种或多种结合的方式提示用户特定区域需要执行如浇水、施肥等动作等，在此不再赘述。
在可选的实施例中，健康提醒模块可以仅发送植被是否健康的信息和植被养护建议信息中的一个。
继续参照图8，另一实施例的自动行走设备1的植被健康状况的识别方法还包括植被养护模块180。植被养护模块180对植被不健康的区域执行植被养护动作。具体的，植被养护动作包括：施肥、浇水、松土、除草、洒药中的至少一种，相应的，植被养护模块包括：施肥模块、浇水模块、松土模块、除草模块、洒药模块中的至少一种。本实施例可以与前述实施例组合而形成整体方案。
自动行走设备1根据检测到的植被具体的健康问题，相应的执行一种或者多种养护动作。例如，当自动行走设备1检测到植被缺水时，执行浇水动作；当自动行走设备检测到植被缺少养分时，执行施肥、松土或除草动作；当自动行走设备检测到植被遭遇病虫害时，执行洒药动作。
植被养护模块180中的一个或者多个可以为可替换的安装在自动行走设备上的附件，自动行走设备在检测到需要执行特定的养护动作时，若机身上没有安装相应的特定附件，则自动拾取该特定附件进行养护动作，或者发出提醒信 息，提示用户为其安装该特定的养护附件。
自动行走设备1上安装有定位设备，以将区域地理位置信息和植被健康状态信息相关联起来，作为生成前述的各类信息，以及执行各类动作的基础。定位设备可以为GPS设备(具体如DGPS设备)，UWB高精度定位设备，图像位置识别设备等。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本发明的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明专利的保护范围应以所附权利要求为准。

Claims (22)

  1. 一种自动行走设备，其特征在于，包括摄像仪、以及摄像加热装置，所述摄像加热装置包括加热模块，所述加热模块给摄像仪的镜头加热以去除镜头上的水雾。
  2. 根据权利要求1所述的自动行走设备，其特征在于：所述摄像加热装置还包括在摄像仪外部设置的透明罩，所述加热模块安装于所述透明罩内部，位于所述摄像仪的侧部并紧邻所述摄像仪。
  3. 根据权利要求2所述的自动行走设备，其特征在于，所述透明罩为玻璃透明罩或塑料透明罩。
  4. 根据权利要求2所述的自动行走设备，其特征在于，所述加热模块包括电阻丝，所述电阻丝与所述自动行走设备中的电池连接。
  5. 根据权利要求4所述的自动行走设备，其特征在于，所述电阻丝外部设置有导热绝缘体。
  6. 根据权利要求4或5所述的自动行走设备，其特征在于，所述摄像仪的镜头上设置上导热片，所述导热片与所述电阻丝连接。
  7. 根据权利要求4所述的自动行走设备，其特征在于，所述电阻丝为连续弯曲状电阻丝。
  8. 根据权利要求7所述的自动行走设备，其特征在于，所述连续弯曲状电阻丝为横竖弯曲状电阻丝。
  9. 根据权利要求1所述的自动行走设备，其特征在于：所述加热模块位于所述摄像仪上或者内部。
  10. 根据权利要求1所述的自动行走设备，其特征在于：还包括雨刮件，所述雨刮件可控地擦除所述镜头上的水雾。
  11. 根据权利要求1所述的自动行走设备，其特征在于：还包括控制器，所述控制器控制所述加热模块加热或停止加热。
  12. 根据权利要求11所述的自动行走设备，其特征在于：还包括检测摄像仪附近环境信息的传感器，所述传感器将检测的环境信息发送给控制器，所述控制器根据环境信息是否满足预设条件，控制所述加热模块加热或停止加热。
  13. 根据权利要求12所述的自动行走设备，其特征在于：所述传感器为温度传感器、湿度传感器、雨淋传感器中的至少一个。
  14. 根据权利要求11所述的自动行走设备，其特征在于：还包括通信模块，所述通信模块接收气候信息并发送给控制器，所述控制器根据气候信息是否满足预设条件，控制所述加热模块加热或停止加热。
  15. 根据权利要求11所述的自动行走设备，其特征在于：还包括时钟模块，所述时钟模块记录时间信息并发送给控制器，所述控制器根据时间信息是否满足预设条件，控制加热模块加热或停止加热。
  16. 根据权利要求1所述的自动行走设备，其特征在于：包括植被健康状况的识别系统，所述植被健康状况识别系统包括：
    获取模块，用于获取植被的图像信息；
    提取模块，用于从图像信息中提取出对应植被的颜色值，所述颜色值为植被的RGB值；
    识别模块，用于将所述植被的RGB值与植被健康生长时的颜色值进行对比识别植被是否健康。
  17. 根据权利要求16所述的自动行走设备，其特征在于：所述获取模块为近红外相机。
  18. 根据权利要求16所述的自动行走设备，其特征在于，还包括植被健康提醒模块，所述植被健康提醒模块将植被是否健康的信息和/或植被养护建议信息发送给用户。
  19. 根据权利要求18所述的自动行走设备，其特征在于，所述植被健康提醒模块包括通信模块，所述通信模块和用户个人智能设备通信，以将前述植被是否健康的信息和/或植被养护建议信息发送到用户个人智能设备上。
  20. 根据权利要求18所述的自动行走设备，其特征在于，所述植被是否健康的信息包括植被所在区域，以及该区域的植被健康水平和/或植被病害类型；所述植被养护建议信息包括建议施肥、浇水、松土、除草、洒药中的至少一种。
  21. 根据权利要求16所述的自动行走设备，其特征在于，还包括植被养护模块，所述植被养护模块对植被不健康的区域执行植被养护动作。
  22. 根据权利要求21所述的自动行走设备，其特征在于，所述植被养护模块包括：施肥模块、浇水模块、松土模块、除草模块、洒药模块中的至少一种。
PCT/CN2016/090127 2015-07-17 2016-07-15 自动行走设备 Ceased WO2017012505A1 (zh)

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