WO2019125807A1 - Autonomous vehicle for the detection and control of plant diseases - Google Patents

Abstract

An autonomous vehicle system for treating turf is provided. The autonomous vehicle may include a controller, a turf sensing unit, a turf treatment unit, and a position detection system. The turf sensing unit may determine whether turf requires treatment. The turf sensing unit may include a sensor mounted to the vehicle and facing the turf. The turf treatment unit may be a UV light source directed at the turf. The controller may activate the UV light source in response to the sensor data. The position detection system may determine a location of the autonomous vehicle and may store the sensor data associated with the location.

Description

AUTONOMOUS VEHICLE FOR THE DETECTION AND CONTROL OF

PLANT DISEASES

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application Number 61/609,311 filed December 21 , 2018, the content of which is hereby incorporated by reference in its entirety.

BACKGROUND

[0002] Maintaining the health and vitality of turfgrasses is important in areas where public access and utility of use of the land is required. In the US alone, an estimated 1.5 million acres of turfgrass is maintained for playing golf. Fungal diseases can have a devastating impact on the health and functional use of golf course turfgrasses. Fungal diseases are also responsible for a significant number of the chemical treatments made annually. Conventional methods for treating fungal diseases (e.g., Dollar Spot ( Sclerotinia homoeocarpa), Brown Patch ( Rhizoctonia solani), Grey Leaf Spot ( Pyricularia grisea), etc.) use chemical fungicides applied by pressurized spray equipment. Often spray applications are made to treat large areas of turf, beyond that in which the disease is located, due to the limitations of conventional spray equipment. Unintentional environmental consequences of these chemical treatments can result chemical treatments moving beyond the targeted application area. Drift of chemical sprays onto areas not intended for treatment and repetitive treatments can also lead to the build-up of chemical residues in the soil and surrounding water containment areas. Another disadvantage to conventional treatment methods is the development of chemical resistance within various fungal and bacterial pathogens. Chemical applications also require people to operate and control the equipment which can put applicators at risk of chemical exposure. BRIEF SUMMARY

[0003] An autonomous vehicle system for treating turf is provided. The autonomous vehicle may include a controller, a turf sensing unit, a UV light source, and a position detection system. The turf sensing unit may determine whether turf requires treatment. The turf sensing unit may include a sensor mounted to the autonomous vehicle and facing the turf. The UV light source may be directed at the turf. The controller may activate the UV light source in response to the sensor data. The position detection system may determine a location of the autonomous vehicle and may store the sensor data and treatment parameters associated with the location.

BRIEF DESCRIPTION OF THE DRAWINGS

[0004] Figure 1 is a schematic view of a system for treating turf.

[0005] Figure 2 is a schematic view of an autonomous vehicle for treating turf.

[0006] Figure 3 is a block diagram of an autonomous vehicle for treating turf.

[0007] Figure 4 is a flowchart illustrating a method for treating turf.

[0008] Figure 5 is a flowchart illustrating a method for monitoring the treatment of turf.

[0009] Figure 6 is a schematic view of a region of a golf course to be treated by the system.

[0010] Figure 7 is a schematic view of scheduling for a region of a golf course to be treated by the system.

[0011] Figure 8 is a schematic view of another scheduling for a region of a golf course to be treated by the system.

[0012] Figure 9 is a schematic view of a vehicle attachment for treating turf.

[0013] Figure 10 is a schematic view of one implementation for controlling distance from a light source to turf. DETAILED DESCRIPTION

[0014] This disclosure provides for both devices and methods of use for the control of fungal diseases in turfgrasses or managed landscapes. The device may include a mechanized unit that is capable of maneuvering over hardened surfaces (e.g. roads, walkways, paths), managed landscapes and turfgrass areas without direct human contact or control of the device. The device may also include sensors with the capability of detecting and controlling the operation of the treatment unit using functions that include, but not limited to, geolocation, direction and speed of movement, identification of volatile compounds associated directly or indirectly with plant disease, optical or photometric analysis for the identification of diseased areas, temperature, humidity, emission of light energy or radiation, chemical spray equipment, application of granular and dust (i.e., dry) type products (e.g. fertilizers and pesticides), and powering on and off different functional pieces of equipment located on or attached to the device. The system may provide processing to reduce power requirements as a portable device. For example, the system may turn off the light treatment in response to the path mapping and the type of turf or the type of infestation anticipated. In some examples, the system may control the speed of motion to minimize the amount of time that the bulb is on or conserve the amount of power used to propel the system possibly by minimizing or maximizing the speed of the device. Other strategies may include optimizing the path to treat the largest consecutive areas at one time.

[0015] The device, in general, may be comprised of an upper and lower surface. The lower surface being characterized as being directed towards and facing the surface of the ground where as the upper surface is characterized as being directed and facing towards the sky. The surfaces of the device that are generally facing perpendicular or not directly in the same plane as the upper and/or lower surfaces may be termed side surfaces. [0016] In some implementations, the device may include sensors and mechanical equipment to enable autonomous mobility and maneuvering of the device to and over the surface of designated turfgrass and managed landscape areas. In some implementations, the device may be used for driver assisted treatment, for example where a UV unit links to a towable unit or directly controls a vehicle whereby the speed of the vehicle may be regulated based on sensor input to ensure duration of the UV application is adequate to control target disease or pest. Communication or the transmission of information pertaining to the space or area in which the device will operate is enabled using either a wired or wireless communication system. The communication system links the device control electronics to a remotely operated software system through which specific control and diagnostic parameters can be sent to and received from the device. The information transmitted to and/or received from the device may include, but is not necessarily limited to: a) geospatial information or boundaries in which the device can operate or traverse; b) temperature and humidity; c) data specific to the area treated; d) device diagnostics; and e) operational data, such as timing and duration of use. Sensors on the device may also detect obstacles or obstructions that could negatively impact the use and operation of the device. This includes, but is not limited to, detection of equipment, tools, golf balls or clubs that in the designated operating path, detection of surface accumulations of water in area otherwise void of water due to rainfall or irrigation, and detection of movement within the operating space of the device. The device may include one or more treatment units. In some implementations, a light source may be attached or formed into the lower surface of the device. The light source may be a source for emitting UV light energy or radiation (e.g., 100 nm to 400 nm) with an emphasis on UVC radiation (e.g., 100 nm to 290 nm). When the device is within the designated area to be treated the light emitting unit(s) may be powered on and UV radiation energy may be transmitted onto plants positioned below the device as the device passes over the designated area. The wavelength of the light energy, frequency and duration (e.g., time) used during the application of the light energy serves to kill or sterilize fungal pathogens residing on and within the plants. Data regarding the area treated and duration in which the light energy was applied may be recorded and subsequently transmitted back to a remote data collection system. This data can be analyzed using programmed data analytics to track treatments and provide data on disease presence, area(s) infected, treatments applied and operational information about the device. In some implementations, users may also provide feedback to the system via a user interface to allow subjective data to impact the scheduling of treatment and type of treatment applied.

[0017] In some implementations, the light source may be a source for emitting light energy or radiation that is helpful to turf, for example some wavelengths of UV- A or UV-B radiation, visible spectrum, or even infrared. As such, an area may be defined without an infestation or where good turf is present and be scheduled for treatment with light that will aid the growth of the turf. When the device is within the designated area to be treated the light emitting unit(s) may be powered on and light energy may be transmitted onto plants positioned below the device as the device passes over the designated area. The wavelength of the light energy, frequency and duration (e.g., time) used during the application of the light energy may be used to promote growth of turf within the designated area. Data regarding the area treated and duration in which the light energy was applied may be recorded and subsequently transmitted back to a remote data collection system. The use of light energy may be used alternatively to or in combination with the light energy used to kill infestations as described elsewhere throughout the application.

[0018] In some implementations, the device may include spectrophotometric sensors capable of detecting fungal disease in or on plants. The data generated by the spectrophotometric sensors can be used for different control or management solutions. These may include, but are not limited to: a) identification and communication of specific targets within a designated area in which remedial treatment is advised or necessary; b) identification of specific targets (e.g., infected plants) and powering on and off light emitting unit(s) located on the lower surface of the device to control fungal pathogens; c) identification of disruptions or alterations to the general land surface within designated areas not related to disease; d) determine plant density; and e) plant health assessment. Data from these sensors can be stored and transmitted to a remote computer system and used to map disease, plant health, plant status, etc. and be incorporated into tactical plant health maintenance programs and services.

[0019] In some implementations, the device includes sensors capable of detecting spores from specific fungal pathogens collected from within designated areas. The one or more sensors are capable of real-time analysis and identification of specific fungal pathogens (e.g. Dollar Spot). The uses of this data include, but are not limited to: a) identification and communication of specific targets within a designated area in which remedial treatment is advised or necessary; b) identification of specific targets (e.g., infected plants) and powering on and off light emitting unit(s) located on the lower surface of the device to control fungal pathogens; and c) activation of pesticide application equipment located on or associated with the device

[0020] In some implementations, the device may include equipment to spray or apply one or more pesticide (e.g., fungicide, herbicide, insecticide) products onto targeted surface areas or plants. Sensor data from one or more sensors on the device can be used to generate an electronic signal within the operating control unit for the spray equipment and provide the indication of where chemical treatment is required. The data collected by the autonomous turfgrass disease control and resistance management (ATDCRM) device may be transmitted to a separate remotely controlled device that is specifically designed for pesticide application. The separate device can use the data from the ATDCRM device to navigate to the point(s) which require treatment.

[0021] In some implementations, the ATDCRM device can detect and map the location where fungal and bacterial diseases appear and where specific or targeted weeds species are identified. This information can be transmitted to a software system that can alert and/or activate a separate chemical application device, whether ground operated or aerial (e.g. Unmanned Aerial Vehicle (UAV)) that can travel to the location identified by the ATDCRM and remedial or curative treatments applied.

[0022] Another problem with conventional chemical applications methods used to combat turfgrass diseases is the time and labor that is required to make the actual application. To complete chemical applications, in general, requires 1 to 2 persons to apply the chemical controls and, due to the recurring nature of fungal diseases, take several man-hours per week to maintain an effective schedule of applications. This can result in significant expense to maintain healthy turfgrass, both in terms of direct labor costs and indirect costs associated with the time the affected turfgrass area is removed from commercial use.

[0023] Using an autonomous device that can navigate to designated areas or sites, detect and apply curative control treatments to turfgrasses to reduce or eliminate fungal diseases have several advantages. An ATDCRM device can reduce the labor needed to inspect and treat turfgrass areas where fungal diseases have been identified. The use of an ATDCRM device can also significantly reduce the amount of pesticide applied to turfgrass areas and reduce exposures to both applicators and other persons who may interact with or travel through treated areas. In addition to controlling different disease pathogens use of the ATDCRM can reduce or eliminate the build-up of resistance within specific pathogens and/or weed species and increase the effectiveness over time chemical control agents are applied. The use of an ATDCRM device can also reduce the build-up and/or off-site movement of pesticides by reducing or eliminating the need for their use. Interruption in the use of managed turfgrass areas can be dramatically lowered in that devices can operate during off-peak hours when people are not around. The ATDCRM device also increases the efficiency of managing and tracking disease control programs and can be used to rapidly access and remediate any areas in which disease problems persist.

[0024] FIG. 1 is a schematic diagram of a turf treatment system. The turf treatment system 100 may include one or more autonomous vehicles 110. The system may include a first ground autonomous vehicle 112. The ground autonomous vehicle 112 may include one or more wheels and a motor to propel the autonomous vehicle along the turf to be treated. The autonomous vehicle 112 may include a treatment unit, for example a light source such as a UV light source, or a sprayer with a tank of chemicals for spraying on an area to be treated. The ground autonomous vehicle 112 may also include a turf sensing unit to record and analyze attributes of the turf before and/or after treatment. The system may also include a second ground autonomous vehicle 114. The second ground autonomous vehicle 114 may include some or all of the features of the first ground autonomous vehicle 112.

[0025] In some implementations, the first ground autonomous vehicle 112 may include sensors to analyze the turf to determine whether treatment is needed, then treat directly or communicate with one or more of the other autonomous vehicles 110, for example the second ground autonomous vehicle 114, which may be equipped with the appropriate treatment for the turf. Then, the second autonomous vehicle 114 may move to the location identified by the first autonomous vehicle 112 and apply a treatment. In some implementations, different vehicles may be equipped with different treatments. For example, the second ground autonomous vehicle 114 may include a chemical treatment while the first ground autonomous vehicle 112 may include light treatments (e.g. a UV-C light source) and the system may discern between calling an autonomous vehicle with chemical treatments or an autonomous vehicle with light treatments based on the sensing of the first ground autonomous vehicle 112. In some implementations, the autonomous vehicles 110 may include an air autonomous vehicle 116, for example a drone with propellers to travel through the air. The air autonomous vehicle 116 may include turf sensing unit to determine whether the turf needs treatment and/or treatment systems for example, light or chemical treatment unit as described with regard to the ground autonomous vehicles.

[0026] In some implementations, an attachment 118 such as a trailer may include all the functionality of the autonomous vehicles 110 described herein, except for possibly the ability to propel, navigate, and path plan. Instead the attachment could be manually maneuvered (e.g. with a tractor) and feedback on treatment locations, etc. could be provided to the driver through a user interface (e.g. integrated into the tractor, on the attachment, or on a hand held device).

[0027] In some implementations, an attachment 118 such as a trailer may include all of the functionality of the autonomous vehicles 110 described herein, except for possibly the ability to propel, navigate, and path plan. Instead the attachment could be manually maneuvered (e.g. with a tractor) and whereby a control unit located on the trailer regulates the throttle or speed control apparatus of the transporting vehicle thereby controlling the speed by which the treatment apparatus travels over the surface of the ground.

[0028] Each of the autonomous vehicles 110 and the attachment 118 may be connected to a network 168 Accordingly, each of autonomous vehicles 110 may communicate with each other as well as a server 150 and one or more hand-held devices 120.

[0029] The handheld devices 120 may include a positioning system. The handheld device 166 may include a user interface that receives entry of a treatment request, the handheld device 166 transmitting the request that activates an autonomous vehicle to treat the turf (e.g. using the UV light source or a chemical treatment). The user may take the handheld device 166 to a location where treatment may be desired and enter information, for example, the type of turf, the type of biological invasion, a location category, and/or the treatment desired based on human observation. The handheld device may display a map including an indicator identifying the treatment location and/or a current location of the handheld device. The hand-held system 166 may then determine the location of the treatment based on the position tracking system (e.g. GPS) in the hand-held system 166. Accordingly, the hand-held system 166 may then communicate with the server 150 or directly with one of the autonomous vehicles 110 to schedule treatment of the turf at the determined location. The treatment parameters may be entered into a user interface on the hand-held device 166 and transmitted to the server 150 and/or may be transmitted directly to any one of the autonomous vehicles 110. The treatment parameters may include the type of treatment (e.g. chemical or UV light), the time of day, and/or exposure parameters for UV light treatment (e.g. distance to turf, intensity of light, duration of exposure, wavelength of light).

[0030] The server 150 may communicate with an external server 174 located in a remote location such as corporate headquarters. The server 174 may receive data from the server 150. The server 150 may push the data to the server 174 and/or, the server 174 may request the data from the server 150. The data may be streamed in real time to the server 174 or accumulated and provided in batches, for example, in the late evening hours. Further, certain data may be provided at different times based on a data priority. For example, alerts that a turf attribute exceeded a certain threshold may generate a message that is immediately transmitted from server 150 to server 174 whereas the actual monitored data may be transmitted at a later time as a different priority. The data that the server 174 may be stored in a data storage unit 176 and may be retrieved by server 174 or other servers for additional data analysis. The server 174 may communicate via a network 178 with various other devices. For example, server 174 may communicate with a billboard display 182 or a handheld device 180 (e.g. cell phone, tablet, etc). The billboard display 182 or handheld device 180 may display the characteristics that are monitored by the sensors located on the autonomous vehicles. In addition, the handheld device 180 and/or the billboard display 182 may display alerts to the greens keepers, course managers, or service providers if a severity is above a certain level or if an unresolvable error occurs, for example, if an autonomous vehicle is stuck an unable to return to the home station. The handheld device 180 and/or the billboard display 182 may display a map with the location of each autonomous vehicle on the course and an indicator to mark the location of autonomous vehicles that are experiencing problems or generating alerts.

[0031] The server 150 and/or server 174 includes communication interfaces 202, system circuitry 204, input/output (I/O) interfaces 206, and display circuitry 208 that generates user interfaces 210 locally or for remote display, e.g., in a web browser running on a local or remote machine through which a project is defined and resources are selected, evaluated, allocated, and connected to a project. The user interfaces 210 and the I/O interfaces 206 may include graphical user interfaces (GUIs), touch sensitive displays, voice or facial recognition inputs, buttons, switches, speakers and other user interface elements. Additional examples of the I/O interfaces 206 include microphones, video and still image cameras, headset and microphone input / output jacks, Universal Serial Bus (USB) connectors, memory card slots, and other types of inputs. The I/O interfaces 206 may further include magnetic or optical media interfaces (e.g., a CDROM or DVD drive), serial and parallel bus interfaces, and keyboard and mouse interfaces.

[0032] The communication interfaces 202 may include wireless transmitters and receivers ("transceivers") 212 and any antennas 214 used by the transmit and receive circuitry of the transceivers 212. The transceivers 212 and antennas 214 may support WiFi network communications, for instance, under any version of IEEE 802.11 , e.g., 802.11 h or 802.11 ac or LoRaWAN protocol. In another embodiment the transceivers 212 and antennas 214 may support cellular communications. The communication interfaces 202 may also include wireline transceivers 216. The wireline transceivers 216 may provide physical layer interfaces for any of a wide range of communication protocols, such as any type of Ethernet, data over cable service interface specification (DOCSIS), digital subscriber line (DSL), Synchronous Optical Network (SONET), or other protocol. [0033] The system circuitry 204 may include any combination of hardware, software, firmware, or other circuitry. The system circuitry 204 may be implemented, for example, with one or more systems on a chip (SoC), application specific integrated circuits (ASIC), microprocessors, discrete analog and digital circuits, and other circuitry. The system circuitry 204 is part of the implementation of any desired functionality in the server 150 and/or server 174. As just one example, the system circuitry 204 may include one or more instruction processors 218 and memories 220. The memory 220 stores, for example, control instructions 222 and an operating system 224. In one implementation, the processor 218 executes the control instructions 222 and the operating system 224 to carry out any desired functionality for the server 150 and/or server 174. The control parameters 226 provide and specify configuration and operating options for the control instructions 222, operating system 224, and other functionality of the server 150 and/or server 174.

[0034] The server 150 and/or server 174 may include a local data repository 232 that includes volume storage devices, e.g., hard disk drives (HDDs) and solid state disk drives (SDDs). The storage devices may define and store databases that the control instructions 222 access, e.g., through a database control system, to perform the functionality implemented in the control instructions 222. In the example shown, the databases include a resource data database 228 and a project data database 230. In other implementations, any of the databases may be part of a single database structure, and, more generally, may be implemented logically or physically in many different ways. Each of the databases defines tables storing records that the control instructions 222 read, write, delete, and modify to perform the processing noted below. The resources descriptors may maintain their own resource descriptor data repositories. The system circuitry 204 may implement the resource analysis circuitry 214, project platform circuitry 216, and the operator control circuitry 218, e.g., as control instructions 222 executed by the processor 218. [0035] FIG. 2 is a schematic view of a ground autonomous vehicle 200. The ground autonomous vehicle may include a body 250 made of a durable frame of metal or polymer. Attached to or enclosed within the body 250 may be control electronics 254. The control electronics 254 may include a processor, a position tracking unit, a communication unit, and power control circuitry. The body 250 may also house a motor 255 for driving one or more wheels 252 of the autonomous vehicle 200. The motor 255 may, in some implementations, be a gas motor used to drive the at least one wheel 252, as well as, generate electricity through an alternator to power the control electronics 254 of the autonomous vehicle 200. A sensor 258 and a turf treatment unit 256 may be housed within or attached to the body 250. Further, the sensor 258 and the turf treatment unit 256 may be positioned such that the sensor 258 and the turf treatment unit 256 are facing the turf, for example being located on the bottom portion of the body 250. The turf treatment unit 256 may be a light treatment unit (e.g. UV light source) or a chemical treatment unit (e.g. chemical sprayer).

[0036] A brush 270 may be used to cause the blades of turf to lay down (e.g. bend more parallel to the ground) thereby providing a better angle for the light energy to reach a greater surface area of each blade (e.g. on the side of the blade). The brush use will enhance the performance of the UVC light due to the laying down of the blades and the exposure to more direct light. The brush may extend from the autonomous vehicle toward the ground and may be flexible. The brush may include many fibers or bristles that engage the blades of grass causing the turf to lay down.

[0037] The communication electronics may communicate with beacons 262 located proximate regions of the turf to be inspected and treated. For example, in the golf course scenario, one or more beacons 262 may be located along the perimeter of the course and be located along the fairway of each hole. The communication electronics may communicate with the beacons 262 through a blue- tooth, Wi-Fi, or other wireless communication network. Additionally, the communication electronics and/or the positioning system may communicate with satellite devices 260. The communication electronics may connect through either of the beacons 262 or satellite devices 260 to determine location of the autonomous vehicle 200 or to communicate system information such as turf analysis, treatment parameters, autonomous vehicle status parameters.

[0038] FIG. 3 is a block diagram of an autonomous vehicle for turf treatment. The autonomous vehicle 300 includes a controller 310. The controller 310 may include a microprocessor as well as discrete electronic components for sensing inputs of other modules and for controlling actuators in other modules. The controller 310 may be in communication with a motor drive unit 312 to control the speed and direction of the autonomous vehicle 300 to move the autonomous vehicle 300 to a desired location to analyze or treat the turf.

[0039] The controller 310 may be in communication with a position tracking system 330. The position tracking system 330 may include a Global Positioning System (GPS) or other position tracking device. For example, using beacons located along the facility having known positions for each of the beacons. The controller 310 and position tracking system 330 may communicate with a mapping unit 322. The mapping system may include data identifying the type of turf and/or a category for each region within the facility. The mapping unit 332 may receive manually generated data or data adapted from other mapping systems for example, Google Maps, Microsoft Earth, or other mapping systems. Further, the data from other mapping systems may be complemented with specific category information or turf information that may be manually inputted. In addition, mapping data within the mapping unit 332, may be automatically determined by having the autonomous vehicle as it drives to each location and senses the type of turf or category based on turf sensing data or environmental sensors at the location.

[0040] The controller 310 may be in communication with a turf sensing unit 324. The may include a sensor, for example a camera or photo spectral sensor facing the turf to determine information relating to the turf. For example, the sensors in the turf sensing unit 324 may determine a type of turf, plant viability or health, as well as, whether a biological invasion has attacked the turf, a type of biological invasion, a severity of the biological invasion, and/or the severity of the damage to the turf. In some implementations, user input may be provided through a user interface (e.g. a questionaire, a map with a drawing tool, etc.) to provide subjective feedback on the severity or change in severity of the biological invasion or damage to the turf.

[0041] The turf sensing unit 324 may include an optical sensor such as a camera or spectrophotometric sensor. The spectrophotometric sensor may include multiple groups of photo sensor that are sensitive to different wavelengths of light. The turf sensing unit 324 may be used to determine if the turf requires treatment. The turf sensing unit 324 (e.g. including one or more sensors) may be mounted to the vehicle facing the turf. The one or more sensors may generate sensor data, for example image data that may be analyzed, stored, and/or transmitted for external processing. The sensor data may be analyzed to determine if a biological invasion is present in the turf. The turf sensing unit 324 may determine the type and severity of biological invasion based on attributes in the image data for example shape, color (e.g. hue, chroma), intensity, and motion. The turf sensing unit 324 may also use infrared sensing or imaging, for example to detect heat variations. The sensor system may illuminate the area of turf being imaged or use ambient light. Further, the vehicle may shield the area being imaged using a baffle or skirt to remove ambient light. The type of light used to illuminate the area being image may include white light, various wave lengths of visible light, UV light, or infrared light. The sensor system may categorize the type of biological invasion by matching sensed attributes of the imaged turf to known attributes of biological invasions. The turf sensing unit 324 may categorize the invasion into different groups such as a fungus, a bacteria, an insect, or a weed. Further, the turf sensing unit 324 may categorize the invasion into more specific diseases such as Dollar Spot ( Sclerotinia homoeocarpa ), Brown Patch ( Rhizoctonia solani), Grey Leaf Spot ( Pyricularia grisea), etc. The turf sensing unit 324 may store the invasion type or transmit the invasion type to a mapping system. The mapping system may store the invasion type, if no invasion type has been previously identified at the current location. The mapping system may compare the invasion type to any previously identified invasion type at that location, if an invasion was already identified for that location. The mapping system may send an alert to the greens keeper or manager if the currently identified invasion type is newly discovered or recurring.

[0042] In some implementations the turf sensing unit 324 may also classify the type of turf using image attributes such as shape, color (e.g. hue, chroma), intensity. The turf sensing unit 324 may store the turf type or transmit the turf type to a mapping system. The mapping system may store the type of turf, if no turf type has been previously identified. The mapping system may compare the turf type to a previously identified turf type, if a turf type was already identified for that location. The mapping system may send an alert to the greens keeper or manager if the currently identified turf type does not match the expected turf type. The type of turf, type of biological invasion, and the severity of the invasion, may be stored for future use.

[0043] Information from the turf sensing unit 324 may be provided to a treatment planning unit. The treatment planning unit may be located in the controller 310 or may be located at a remote server (e.g. server 150 or server 174) through a communication network. The controller 310 may be configured to direct the autonomous vehicle to the location and activate the UV light source in response to a treatment plan (e.g. including a time, treatment parameters, location). The controller 310 may adjust the exposure parameters of the UV light treatment based on the sensor data acquired at the treatment location. The controller 310 may receive sensor data (e.g. one or more images) and store the sensor data in a database. As described above the sensor data may be indicative of biological invasion.

[0044] The controller 310 may be configured to determine exposure parameters (e.g. distance to turf, intensity of light, duration of exposure, wavelength of light) for the UV light source based on a type of turf type (e.g. as determined by stored location in the mapping system or sensor data) and the biological invasion (e.g. as determined by sensor data or user input). When determining exposure parameters the controller 310 may to determine a type of turf based on the sensor data (e.g. spectral sensor, imaging sensor) or based on the location and a mapping stored in a database. The controller 310 may determine a number of treatments required over a predefined time period and schedule the treatments. The controller 310 may schedule a treatment based on a location category (e.g. green, tee, fairway, rough 1 , rough 2) as determined by the database in response to the location. As such, the controller 310 may request scheduling a treatment at a location that corresponds to a green at a higher priority than other location categories. The controller 310 may also be configured automatically request scheduling a treatment at a location that corresponds to certain locations such as a green or a tee after sunset and before sunrise.

[0045] The controller 310 may select a distance of the UV light source to the turf based on the sensor data. The light positioner 322 may be mounted to the autonomous vehicle and the UV light source may be mounted on the positioner. The controller 310 may adjust the distance of the UV light source from the turf using the light positioner 322. In some implementations, the distance of the light source may be controlled by selecting between multiple light sources mounted at different distances. The UV light source may include a first light source mounted to a body of the autonomous vehicle at a first distance from the turf and a second light source mounted to a body of the autonomous vehicle at a second distance from the turf. The controller 310 may select between a first light source at the first distance and the second light source at the second distance based on the sensor data. The controller 310 may adjust intensity of the light source based on the sensor data. The controller 310 may adjust intensity by adjusting power provided to the light source to change the intensity based on the sensor data. The controller 310 may activate additional lamps to adjust the intensity of the light source based on the sensor data. In some implementations, the controller may adjust a duration of exposure or wavelength based on the sensor data. Further, the controller may store the exposure parameters associated with the location and a treatment time. Table 1 is one example of a treatment plan for a particular area.

Table 1

[0046] One possible treatment schedule for a particular area incorporating UV treatment may provided in Table 2 below.

Table 2

[0047] The controller 310 may compare the severity of the biological invasion to a stored previously determined severity at the treatment location. In some implementations, the controller 310 may compare a stored image to a current image and adjust the exposure parameters in response to the comparison. The controller may generate a severity rating based on the sensor data, where the controller compares the severity rating to a previously stored severity rating for that treatment location and adjusts the exposure parameters in response to the comparison. The controller 310 may generate an alarm if the severity rating is worse than the previously stored severity rating. The alarm may include the treatment location, location classification, the type of biological invasion, and the severity rating. The controller 310 may schedule treatment in regions adjacent to the treatment location based on comparison, as well as, the treatment location and the severity rating.

[0048] The autonomous vehicle may include a sprayer 350 and a sprayer tank 352. The sprayer tank 352 may be filled with chemical treatment for the turf. As such, the controller 310 may activate either the lighting unit 320 to apply a UV light treatment or the sprayer 350 to apply a chemical treatment according to the treatment plan. Further, UV light and chemical treatments may be used in an alternating manner to reduce the build up of resistance in the biological invasion. The sprayer 350 may also be used as marking device (e.g. with dye in the sprayer tank 352) for marking the turf at the treatment location based on the severity. The controller 310 may compare the severity to a previously stored severity rating for the treatment location and mark the turf at the treatment location in response to the comparison.

[0049] The autonomous vehicle may stop at each location to inspect and apply treatment to the turf. However, the autonomous vehicle may inspect or apply treatment continuously while moving. The sensors may acquire images with a fast shutter speed (electronic or mechanical) to freeze the motion of the turf under the sensor. Further, the controller 310 may control or take into account the speed of the autonomous vehicle to calculate the integrated exposure to UV light that is provided as the UV light source moves across the location. As such, the intensity and or distance between the light source and turf may be adjusted to provide the desired amount of UV radiation.

[0050] The controller 310 may also be in communication with environmental sensors 340. The environmental sensors 340 may measure environmental conditions at the location of the autonomous vehicle 300. The environmental conditions may include a slope of the ground, a moisture of the turf, a moisture in the air, a humidity, a temperature of the turf, a temperature in the air, an amount of sunlight. Each of these parameters may be stored based not only on the location but also the time of day. The parameters may then be tracked such that data may be interpreted to determine a best time of day for treatment and/or turf inspection based on environmental conditions provided for each location. For example, if the temperature of the ground and the temperature of the air are at such conditions that dew may develop or if moisture on the ground is sensed, the system may schedule a UV treatment at a time to avoid dew such that the effects of the light may not be magnified and may not create an overexposure condition. In other instances, it is possible that the system may adjust the treatment for example, reduce the power of the light knowing that dew on the ground may magnify the potency of the treatment at a particular time and location that dew is present. As such, the controller 310 may adjust exposure parameters of the UV light source in response to the sensor data and/or the environmental data.

[0051] The controller 310 may be in communication with a power supply 314 to provide power to the controller electronics as well as other systems including for example, the environmental sensors, the detection unit, the treatment planning unit, the position tracking unit, the mapping unit, and the motor drive unit. The power supply unit 314 may provide electrical power to control these units. The power supply 314 may receive power from a battery 316. The battery 316 may be a rechargeable battery that is located in the body of the autonomous vehicle 300. The battery 316 may be charged via a power source 318. The power source 318 may be an electronic docking station located at a home base for example, a greens keeper shed located on the golf course. However, docketing stations may be located at various positions along the golf course, as such, the mapping system may plot a course for the autonomous vehicle 300 that stops at multiple docking stations to power before returning to the greens keeper shed at the completion of a treatment run or for other maintenance.

[0052] In other implementations, the power source may be a gas generator, solar power cell, or an alternator attached to a gas motor that may be used to drive the autonomous vehicle position through the motor drive unit 312. In some implementations, the controller 310 may communicate with the power supply to control the amount of power provided to a lighting unit 320 that may be used to treat the turf. For example, in some implementations, a UV-C light may be used to treat the turf and eliminate biological invasions through DNA disruption. The power of the light provided by the lighting unit 320 may be controlled through the power supply 314. In addition, the controller 310 may be in communication with a light positioner 322 to control the distance between the light source with the lighting unit 320 and the turf. The light positioner 322 may be a physical displacement unit, for example, a motor (e.g. an electric motor) attached to a drive screw or scissor jack to control the distance of the lighting unit 320 from the turf. In other implementations, lighting positioner 322 may be controlled through the use of multiple lighting sources mounted at various distances and then controlled by switching certain light sources on at certain distances while other light sources at non-desired light distances are turned off.

[0053] Now referring to FIG. 4, a method for treating turf is provided. The method starts in block 408 where the system moves to a location of the turf to be inspected or treated. In block 410, the system acquires sensor data of the turf. In block 412, the system may then determine the type of turf based on the sensor readings. The system may then determine or confirm the location of the inspection or treatment in block 414. In block 416, the system may determine whether treatment is needed and biological invasion characteristics based on the sensor readings. If the system determines that treatment is needed in block 418, the process continues to block 420. In block 420, treatment parameters are determined based on the turf type and the biological invasion characteristics. In block 422, an autonomous vehicle may perform the treatment for example, by applying a UV-C light to the turf or spraying a chemical treatment. In some implementations, the system will schedule future treatments to be performed by the same autonomous vehicle or another autonomous vehicle at a later time. The treatment may be scheduled or performed at the determined location. Further treatments and/or inspections may be scheduled within adjacent regions to the current region when a biological invasion has been identified. The system may then move to the next scheduled region. The method may, then repeat, by continuing along line 424 to the next region at block 410. If the system determines that treatment is not needed at the current region in block 418, the method may proceed along 424 and the autonomous vehicle may move to the next scheduled region at block 410.

[0054] FIG. 5 is a method for monitoring turf treatment. The method starts in block 510 where the autonomous vehicle is moved to a treatment location. The system acquires sensor data of the turf at the treatment location as is denoted in block 512. In block 514, the system may retrieve stored sensor data from previous inspections and/or treatments and compare the currently acquired sensor data to the previously stored sensor data at the treatment location. This may also consider prior chemical treatments which may be applied by spraying autonomous units or entered by users through a user interface. In block 516, the system determines if the severity of the biological invasion is worse now than previously.

[0055] If the biological invasion is not worse, the method follows line 518 to block 520. In block 520, the system determines whether treatment is needed and invasion characteristics. If treatment is needed in block 522, the system determines treatment parameters. Then the method proceeds to block 524 where treatment is performed, if needed. [0056] In block 516, if the severity is worse, the method proceeds to block 526. For example, the severity may be worse because of a change in the perimeter, increased size, or color characteristics indicating the strength of the biological invasion has increased. In block 526, the system generates an alert to the greens keeper, manager, or system service provider. The alert may take the form of a text message, email, or other indicator. The method then proceeds to block 526. In block 526, the treatment parameters are adjusted. For example, the amount of power of a UV-C light treatment may be increased. In some implementations, one or more of the duration, distance between the light source and turf, or speed of movement of the autonomous vehicle may be adjusted to increase the amount of power of UV-C light provide to the turf. If the severity is above a threshold severity, the system may be configured to provide a UV-C power treatment power or duration above the amount that would kill the turf to prevent the spread of the biological invasion beyond the area currently affected. The method may then proceed to block 530 where adjacent regions may be scheduled for inspection and/or treatment to prevent further spreading of the biological invasion beyond the current region.

[0057] The system may then proceed to block 524 where the treatment may be performed by the system for example, by activating a UV-C light source that is directed toward the turf. The system may then store treatment data as denoted by block 532. The system may then proceed to move to the next treatment location where the method may be repeated as denoted by block 510.

[0058] FIG. 6 is a schematic view of the region of a golf course to be treated by the turf treatment system. The region is depicted as a hole on a golf course. The system for treating turf on a golf course may categorize locations on the golf course differently based on their use, cut, and turf type. The region includes a tee box 612 and a green 610. The tee box 612 is where each golfer starts the hole and the green 610 includes a cup inserted into the ground where each golfer finishes the hole. The greens 610 are typically the most important area of turf on the golf course. Greens 610 are finely manicured since the ball typically rolls along the surface of the turf into the cup. The greens 610, however, are also one of the most susceptible areas to biological invasion. Greens 610 are susceptible because of the very short cut of the turf, the type of turf used, and the amount of traffic that the green 610 receives. For example, each golfer walks a somewhat different path from the tee 612 to the green 610. As such, any biological invasion that is encountered along each golfer’s path may be brought to the green 610 when finishing the hole.

[0059] While each golfer starts on a tee box 612, often times each hole may have multiple tee boxes 612 that may be used depending on the golfer’s skill level. Accordingly, the greens 610 are the highest priority area on the golf course for both inspection and treatment. The tee boxes 612 are the second most important areas for inspection and treatment. The perimeter of each area (e.g. green 610 or tee box 612) may be stored and tracked in the mapping unit (e.g. 332 of FIG. 3) to guide autonomous vehicles as described elsewhere in this application. While the tees 612 and greens 610 have the highest two priorities, other areas on the golf course are also important. The fairway 614 is a region between the tee 612 and the green 610 that is also cut short for easy playability by the golfer. Ideally, the golfer will hit the ball along the fairway 614 when the green 610 cannot be reached directly during that shot. As such, the fairway 614 may have a third priority for scheduling.

[0060] To increase the difficulty of play, areas around the fairway 614 are provided with an increased length of turf called the rough. Often, these areas are more rugged and durable but are ideally less traveled by the golfer. Typically, a first rough 616 surrounds the fairway 614 and a second cut of rough 618 may fill the rest of the whole region. The first rough 616 may have a longer cut than the fairway 614, but a shorter cut than the second rough 618. Often to protect the turf, a paved or dirt path called a cart path 620 will be provided for golfers to use ridable carts or drag manually pulled carts from the tee box 612 to the green 610. While the cart path 620 is typically not of particular concern to the greens keeper, it may be helpful to have the autonomous vehicle inspect the cart path 620 for cracks or weeds growing in the cart path 620. Weeds may be treated by the autonomous vehicle with chemicals or a UV treatment to kill any weeds along the path. Further, any cracks can be noted and alerts may be sent to greens keepers regarding possible maintenance required.

[0061] In addition, the golf course may include hazards that make the golf ball more difficult or impossible to play at certain locations. For example, sand traps 622 may be an area typically around the green that is filled with sand. Often the sand trap 622 is dug out of the ground and includes walls or lips around its edges that make the area around the sand trap 622 difficult for an autonomous vehicle to traverse. As such, the perimeter of the sand traps and other hazards are also important to track and store in the mapping system to avoid stranding or damaging the autonomous vehicle.

[0062] A water hazard 624 may also be positioned in the area of the golf course. Often water hazards 624 may run adjacent to the fairway 614, however, sometimes the hazards may be integrated into the fairway 614 and/or run across the fairway 614 depending on the design of the hole. Again, the perimeter of the hazards are important to provide to the mapping system such that the mapping system may determine a route for the autonomous vehicle that does not traverse through or too close to any of the hazards such as the sand trap 622 or the water hazard 624.

[0063] The golf course may also include many trees, bushes or other obstacles such as benches, trash cans or outhouses. These other obstacles may also be provided to the mapping system and stored for generating a path between inspection regions for an autonomous vehicle. Additionally, the autonomous vehicle may include sensors to detect when an obstacle is in front of or to the side of an autonomous vehicle. As such, the autonomous vehicle may provide obstacle data to the mapping system which may be stored for future use when planning the path of the autonomous vehicles throughout the region.

[0064] FIG. 7 is a schematic view of scheduling for a region of a golf course to be treated by the system. In certain instances, a location on the golf course is scheduled for inspection or treatment either by an autonomous vehicle or by a human, for example using a handheld device. Treatment location 710 is an area that is identified for treatment. If the area 710 is identified as having a biological invasion, then adjacent regions may also be automatically scheduled for inspection and treatment. As such, a processor in the autonomous vehicle or on a remote server may schedule inspection and/or treatment in regions that share a border with region 710 for example, region 712, 714, 716, and 718. In addition, depending on the type of biological invasion and severity of the biological invasion, the system may schedule cross-cornered regions for example, region 720, 722, 724, and 726. Further, it is understood that if inspection of the adjacent regions indicate a biological invasion the bordering or cross-cornering regions to the additionally scheduled region may also be scheduled. Accordingly, the system may automatically determine the size and the shape of the biological invasion even if the biological invasion spans multiple treatment locations as the number of connected inspection regions increases and the system stores the perimeter of the biological invasion such that treatment progress can be tracked based on the size and shape of the biological invasion.

[0065] FIG. 8 is a schematic view of another scheduling for a region of a golf course to be treated by the system. The region includes multiple locations that may require treatment by an autonomous vehicle. The path of the autonomous vehicle for the treatment may be determined based on the power characteristics of the vehicle, the location of each treatment location, and the priority category of each treatment location. For example, treatment locations on the green 610 would have the highest priority classification, treatment locations on the tee box 612 would have the second highest priority classification, and treatment locations on the fairway 614 would have the third highest priority classification. The green 610 having the highest priority, treatment location 812 located on the green 610 may be loaded into the autonomous vehicle path first. Any other treatment locations located on the green 610 would then be added. Tee boxes 612 having the second highest priority, treatment location 810 may be added to the autonomous vehicle path next.

[0066] Since no other treatment locations are on the tee box 612, the scheduling unit may look to the next lowest priority region (e.g. the fairway 614) and find the inspection location that is closest to the path between the already scheduled treatment locations. In this instance, treatment location 816 may be closest to the path between inspection location 810 and inspection location 812. As such, inspection location 816 may be added to the autonomous vehicle path. Then the next closest inspection location to the path of the scheduled route is added to the path. For example, in this case, inspection location 814 may be added to the path. Further, the scheduling unit may take into account obstacles that may lie directly between the inspection locations. For example, even though inspection location 814 is closer to the direct line between 816 and 812, the scheduling unit may include 814 because the path between 812 and 816 may not be able to be a straight line due to the closeness of a straight line path to the sand trap 622. As such, the path may need to move to the left to avoid the sand trap 622 thereby making the adjusted path even closer to location 814. Next, additional inspection locations are added within the current priority area (e.g. the fairway 614) such as, inspection location 818. Then additional inspection areas are added in lower priority regions for example, inspection region 820 in the first cut of the rough 616 and the inspection location 822 in the second cut of the rough 618.

[0067] Further, it is understood that the scheduling unit may recalculate the path on the fly as the autonomous vehicle is inspecting or treating a particular inspection location. For example, the autonomous vehicle may stop at location 812 and, based on the severity of the biological invasion found at location 812, schedule adjacent locations to the current path as discussed earlier with regard to FIG. 7. As such, the schedule unit may need to drop other inspection locations such as lower priority locations 822 or 820 based on power characteristics of the autonomous vehicle, such as a low battery level. In addition, the scheduling unit may incorporate stops at recharging stations for example, recharging station 830. Accordingly, when the vehicle is below a certain power level the scheduling unit may include a stop to the closest recharging station and adjust the scheduling on the fly based on the location of the autonomous vehicle at the charging station 830.

[0068] FIG. 9 is a schematic view of a vehicle attachment for treating turf. The vehicle attachment 912 may include any of the functionality and features described elsewhere in this application with regard to autonomous vehicles (e.g. with regard to Figure 3). However, the attachment 912 may mechanically connect to a user operated vehicle such as a tractor 910. Ideally, the attachment 912 may also have an electrical communication link to the tractor 910. However, this is not necessarily required. The attachment 912 may receive power from the tractor 910 however, the attachment 912 may include batteries, solar panels and/or a gas powered generator to create and maintain its own power independent from the tractor 910. Further, it may be beneficial for the attachment 912 to control the speed of the vehicle 910 allowing adjustment to the amount of time that the turf is exposed to the light provided from a light source on the attachment 912. However, the attachment 912 may include sensors that determine the distance from the light source to the turf and the speed of the vehicle 910 and/or attachment 912. The speed of the attachment 912 may be measured, for example by measuring the relative speed of the ground moving underneath the attachment 912 or the rotation of the wheels located on the attachment 912. If the speed of the vehicle is not controlled, then the power of the UV light provided to the turf may be controlled via other means for example, increasing or decreasing the power output of the light source and/or the distance of the light source to the turf.

[0069] The attachment 912 may include control electronics 954. The control electronics 954 may include a processor, a position tracking unit, a communication unit, and power control circuitry. A sensor 958 and a treatment unit 956 may be housed within or fixed to the attachment 912. Further, the sensor 958 and the treatment unit 956 may be positioned such that the sensor 958 and the treatment unit 956 are facing the turf, for example being located on the bottom portion of the attachment 912.

[0070] The communication electronics may communicate with beacons located proximate regions of the turf to be inspected and treated. For example, in the golf course scenario, one or more beacons may be located along the perimeter of the course and be located along the fairway of each hole. The communication electronics may communicate with the beacons through a blue-tooth, Wi-Fi, or other wireless communication network. Additionally, the communication electronics and/or the positioning system may communicate with satellite devices. The communication electronics may connect through either of the beacons or satellite devices to determine location of the attachment 912 or to communicate system information such as turf analysis, treatment parameters, autonomous vehicle status parameters.

[0071] Figure 10 is a schematic view of one implementation for a light positioning system to control a distance from UV light source to the turf. As described elsewhere in this application, a screw drive or a geared system may be used to create a physical displacement of the lighting unit to change the distance between a lighting source and the turf. However, the distance between the lighting source and the turf may be controlled logically using multiple sources as depicted in FIG. 10. In this implementation, multiple light sources may be mounted at different heights from the turf. Light sources 1010, 1020 and 1030 may be mounted at a first distance from the turf and form a first set 1040 of light sources. Light sources 1012, 1022 and 1032 may be mounted at a second distance from the turf and may form a second set 1050 of light sources. Finally, light sources 1014, 1024, and 1034 may be mounted at a third distance from the turf and may form a third set 1060 of light sources. The distance controller may determine which of the first, second, or third set of light sources (1040, 1050, or 1060) are mounted closest to the desired distance as determined by the controller. In this scenario, the controller may just select one set of the light sources to activate and deactivate the other two sets light sources. However, the light positioner may interpolate between the two sets of light sources by activating both of the two of the sets of light sources but varying the power of one light source relative to the other light source or the exposure time of one light source relative to the other light source to create an effective distance that is between the distance of each of the distinct set of light sources.

[0072] The use of UVC light to control disease within a spray (chemical) program is a significant reduction of labor value. This value may be calculated to be $60,000-80,000 annually. The use of this product (UV light) may also reduce disease level in golf course turf. Through course mapping an historical chemical use, special pricing may be offered to the customer that allows competitive offers to be made based on greens, fairways and competitive chemistry.

[0073] Further, in some implementations variation may be introduced into the treatment parameters. As discussed previously, one issue can be that certain types of biological invasions may grow immune to certain chemical treatments. Accordingly, introducing variation into the treatment plan for each treatment location may reduce the ability of biological invasions to form resistances to certain types of treatments. As such, various parameters of the UV treatment may be varied either through sequential variation of the treatment or randomization of the treatment. Accordingly, in one implementation, each set of light sources may have a different wavelength of output than each of the other sets of light sources. Accordingly, the wavelength of the UV light applied to the location may be varied from one treatment to the next treatment at a particular location. Further, the exposure time, power output, and distance to the turf of the UV light sources may be varied from one treatment at a location to another treatment at the same location. In addition, one type of treatment may be interspersed with another type of treatment. For example, treatments of UV light may be interspersed with treatments that apply chemical sprays to eliminate the biological invasion and reduce the ability of the biological invasion to build a resistance to the treatment. [0074] The methods, devices, processors, modules, engines, and logic described above may be implemented in many different ways and in many different combinations of hardware and software. For example, all or parts of the implementations may be circuitry that includes an instruction processor, such as a Central Processing Unit (CPU), microcontroller, or a microprocessor; an Application Specific Integrated Circuit (ASIC), Programmable Logic Device (PLD), or Field Programmable Gate Array (FPGA); or circuitry that includes discrete logic or other circuit components, including analog circuit components, digital circuit components or both; or any combination thereof. The circuitry may include discrete interconnected hardware components and/or may be combined on a single integrated circuit die, distributed among multiple integrated circuit dies, or implemented in a Multiple Chip Module (MCM) of multiple integrated circuit dies in a common package, as examples.

[0075] The circuitry may further include or access instructions for execution by the circuitry. The instructions may be stored in a tangible storage medium that is other than a transitory signal, such as a flash memory, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM); or on a magnetic or optical disc, such as a Compact Disc Read Only Memory (CDROM), Hard Disk Drive (HDD), or other magnetic or optical disk; or in or on another machine-readable medium. A product, such as a computer program product, may include a storage medium and instructions stored in or on the medium, and the instructions when executed by the circuitry in a device may cause the device to implement any of the processing described above or illustrated in the drawings.

[0076] The implementations may be distributed as circuitry among multiple system components, such as among multiple processors and memories, optionally including multiple distributed processing systems. Parameters, databases, and other data structures may be separately stored and managed, may be incorporated into a single memory or database, may be logically and physically organized in many different ways, and may be implemented in many different ways, including as data structures such as linked lists, hash tables, arrays, records, objects, or implicit storage mechanisms. Programs may be parts (e.g., subroutines) of a single program, separate programs, distributed across several memories and processors, or implemented in many different ways, such as in a library, such as a shared library (e.g., a Dynamic Link Library (DLL)). The DLL, for example, may store instructions that perform any of the processing described above or illustrated in the drawings, when executed by the circuitry.

[0077] As a person skilled in the art will readily appreciate, the above description is meant as an illustration of implementation of the principles this disclosure. This description is not intended to limit the scope or application of this system in that the system is susceptible to modification, variation and change, without departing from the spirit of this disclosure, as defined in the following claims.

Claims

1. An autonomous vehicle system for treating turf, the system comprising:

A turf sensing unit for determining whether turf requires treatment, the turf sensing unit comprising a sensor mounted to the vehicle and facing the turf, the sensor generating sensor data;

A turf treatment unit directed at the turf,

A controller being configured to activate the turf treatment unit in response to the sensor data; and

A position detection system configured to determine a location of the autonomous vehicle.

2. The system according to claim 1 , where the turf sensing unit is configured to determine if a biological invasion is present in the turf.

3. The system according to claim 2, wherein the turf sensing unit comprises a sensor capable of detecting a compound that that is comprised of volatiles indicative of biological invasion that cause stress or damage to plants, such as turf or volatiles expressed by plants in response to fungal disease or other biological invasion.

4. The system according to claim 2, wherein the turf sensing unit comprises a spectrophotometric sensor.

5. The system according to claim 2, wherein the turf sensing unit comprises an imaging sensor.

6. The system according to claim 2, where the controller is configured to determine exposure parameters of the light based on a type of grass and the biological invasion.

7. The system according to claim 1 , wherein the controller is configured to determine a type of turf based on the sensor data.

8. The system according to claim 1 , wherein the controller is configured to determine a type of turf based on the location and a mapping stored in a database.

9. The system according to claim 1 , wherein the controller is configured to determine a number of treatments required over a predefined time period.

10. The system according to claim 1 , wherein the controller is configured schedule a treatment based on a location category as determined by the database in response to the location.

11. The system according to claim 10, wherein the controller is configured schedule a treatment at a location that corresponds to a green at a higher priority than other location categories.

12. The system according to claim 1 , wherein the controller is configured automatically schedule a treatment at a location that corresponds to a green or a tee after sunset and before sunrise.

13. An autonomous vehicle system for tracking progress of treatment for turf, the system comprising:

a UV light source directed at the turf to treat the turf according to exposure parameters;

a position detection system configured to determine a treatment location of the autonomous vehicle;

a turf sensing unit configured to determine a severity of a biological invasion of the turf, the turf sensing unit comprising a sensor mounted to the vehicle and facing the turf, the sensor generating sensor data related to the severity of the biological invasion; and

a controller configured to compare the severity of the biological invasion to a stored previously determined severity at the treatment location.

14. The system according to claim 13, wherein the sensor data is an image and the controller is configured to compare a stored image to a current image and adjust the exposure parameters in response to the comparison.

15. The system according to claim 13, wherein the controller is configured to generate a severity rating based on the sensor data, the controller being configured to compare the severity rating to a previously stored severity rating for the treatment location and adjust the exposure parameters in response to the comparison.

16. The system according to claim 15, wherein the controller is configured to generate an alarm if the severity rating is worse than the previously stored severity rating.

17. The system according to claim 16, wherein the alarm includes the treatment location.

18. The system according to claim 13, wherein the controller is configured to schedule treatment in regions adjacent to the treatment location based on the treatment location and the severity rating.

19. An autonomous vehicle system for treating turf, the system comprising:

a UV light source directed at the turf;

a controller in communication with the UV light source to control activation of the UV light source; a turf sensing unit for determining whether the turf requires treatment, the turf sensing unit comprising a sensor mounted to the vehicle and facing the turf, the sensor generating sensor data; and

a position detection system to determine a treatment location.

20. The system according to claim 19, wherein the controller is configured to direct the autonomous vehicle to the location and activate the UV light source in response to a treatment plan.

21. The system according to claim 19, wherein the controller receives sensor data and stores the sensor data in a database, the sensor data being indicative of biological invasion.

22. The system according to claim 19, wherein the sensor data includes an image of the turf.

23. The system according to claim 19, where in the controller is configured to select a distance of the UV light source to the turf based on the sensor data.

24. The system according to claim 23, further comprising a positioner, the UV light source being mounted on the positioner and the controller being configured to adjust the distance of the UV light source from the turf using the positioner.

25. The system according to claim 23, wherein the UV light source includes a first light source mounted to a body of the autonomous vehicle at a first distance from the turf and a second light source mounted to the body of the autonomous vehicle at a second distance from the turf, the controller being configured to select between the first light source at the first distance and the second light source at the second distance based on the sensor data.

26. The system according to claim 19, wherein the controller is configured to adjust intensity of the light source based on the sensor data.

27. The system according to claim 26, wherein the controller is configured adjust power provided to the light source to change the intensity based on the sensor data.

28. The system according to claim 26, wherein the controller is configured activate additional lamps to adjust the intensity of the light source based on the sensor data.

29. The system according to claim 19, wherein the controller is configured to adjust a duration of exposure based on the sensor data.

30. The system according to claim 29, where in the controller is configured to select a wavelength of the UV light source based on the sensor data.

31. The system according to claim 29, wherein the controller is configured to store exposure parameters associated with the location and a treatment time.