# US 10,869,432 B2 · Lawn monitoring and maintenance via a robotic vehicle > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,869,432 B2 - Document ID: US10869432B2 - Status: Granted - Kind: B2 - Application number: 15/539,317 - Filed: 2015-11-04 - Published: 2018-08-02 - Granted: 2020-12-22 - Earliest claimed: 2014-12-23 - Assignees: Husqvarna AB - Applicants: Husqvarna AB - Inventors: Tomas Wykman; Fredrik Edholm; Eric Lennings; Pär Christensson; Stefan Grufman; Björn Mannefred; Patrik Jägenstedt; Magnus Öhrlund; Olle Markusson - Web page: https://patentgrep.com/patent/US10869432B2 ## CPC - A01G 20/30: Apparatus for treating the lawn or grass surface (machines for aerating lawns A01B45/02) - A01C 21/007: {Determining fertilization requirements} - A01D 34/008: {for automated or remotely controlled operation} - G05D 1/0261: {using magnetic plots} - G05D 1/0274: {using mapping information stored in a memory device (navigation using map-matching G01C21/30)} - G05D 1/0278: {using satellite positioning signals, e.g. GPS} - H04L 67/125: involving control of end-device applications over a network - H04W 4/021: Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences - A01D 2101/00: Lawn-mowers - G05D 1/027: {comprising intertial navigation means, e.g. azimuth detector (inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165)} - H04W 84/18: Self-organising networks, e.g. ad-hoc networks or sensor networks - Y04S 40/18: Network protocols supporting networked applications, e.g. including control of end-device applications over a network - A01G: HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING (picking of fruits, vegetables, hops or the like A01D46/00; propagating unicellular algae C12N1/12) - A01C: PLANTING; SOWING; FERTILISING (parts, details or accessories of agricultural machines or implements, in general A01B51/00 - A01B75/00) - A01D: HARVESTING; MOWING - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) - Y04S: SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS ## Abstract Some example embodiments may provide a capability for intelligent control or management of a number of assets in connection with yard maintenance with the assistance or inclusion of a management unit having distributed properties. Thus, for example, sensor equipment and task performance equipment operation may be coordinated between local management and remote management entities for efficient monitoring and maintaining of lawn wellness. ## Claims ### Claim 1 A robotic vehicle comprising: one or more functional components configured to execute one or more lawn care functions on a parcel in accordance with a schedule, the one or more lawn care functions comprising grass mowing and the one or more functional components of the robotic vehicle comprising a blade control system comprising a cutting blade for grass mowing; one or more sensors configured to detect conditions proximate to the robotic vehicle; a vegetation analyzer module configured to analyze data received from the one or more sensors to determine lawn wellness information; a positioning module configured to determine a robotic vehicle position; and a mapping module configured to correlate the lawn wellness information with the robotic vehicle position, wherein the lawn wellness information comprises one or more of water stress, nutrient stress, weed infestation, and pest infestation, wherein, via the vegetation analyzer module, the robotic vehicle is configured to adjust the schedule based on the lawn wellness information; wherein the robotic vehicle is further configured to move to a plurality of fixed sensors within the parcel, read data from each of the plurality of fixed sensors, and store the data read from each of the plurality of fixed sensors on a memory device of the robotic vehicle; wherein the vegetation analyzer is further configured to determine the lawn wellness information based on the data received from the one or more sensors indicating conditions detected proximate the robotic vehicle and the data read from each of the plurality of fixed sensors by the robotic vehicle. ### Claim 2 (depends on 1) The robotic vehicle of claim 1, wherein the one or more sensors comprises at least one of an inertial measurement unit (IMU), a real time kinematic (RTK)-GPS receiver, a SIM card, a sprinkler angle sensor, or a grass detector. ### Claim 3 (depends on 2) The robotic vehicle of claim 2, wherein the vegetation analyzer module is configured to receive the lawn wellness information from a grass detector. ### Claim 4 (depends on 3) The robotic vehicle of claim 3, wherein the grass detector comprises a near-infrared (NIR) sensor. ### Claim 5 (depends on 4) The robotic vehicle of claim 4, wherein the NIR sensor provides plant NIR reflectance information and plant visible reflectance information to the vegetation analyzer module. ### Claim 6 (depends on 5) The robotic vehicle of claim 5, wherein high NIR reflectance and low visible reflectance indicates a healthy plant. ### Claim 7 (depends on 5) The robotic vehicle of claim 5, wherein low NIR reflectance and high visible reflectance indicates an unhealthy plant. ### Claim 8 (depends on 1) The robotic vehicle of claim 1, wherein the one or more sensors further comprises a camera. ### Claim 9 (depends on 8) The robotic vehicle of claim 8, wherein the camera provides images of grass to the vegetation analyzer module for determining the lawn wellness information. ### Claim 10 (depends on 1) The robotic vehicle of claim 1, wherein the mapping module is configured to operate in a map generation mode. ### Claim 11 (depends on 10) The robotic vehicle of claim 10, wherein the mapping module is configured to incorporate input from the one or more sensors to determine a current position of the robotic vehicle and the lawn wellness information at the current position of the robotic vehicle to generate a map of the parcel responsive to traversal of the parcel by the robotic vehicle. ### Claim 12 (depends on 11) The robotic vehicle of claim 11, wherein the mapping module is configured to divide the map into a plurality of zones in which each of the plurality of zones is defined by a corresponding geographic description and corresponding predefined lawn conditions relative to the map data. ### Claim 13 (depends on 12) The robotic vehicle of claim 12, wherein the predefined lawn conditions comprises plant data corresponding to at least one plant growing within a respective one of the plurality of zones, and wherein the plant data defines predefined growth parameters of the at least plant. ### Claim 14 A system comprising: a plurality of fixed sensors disposed on a parcel of land configured to detect conditions on the parcel of land; and a robotic vehicle configured to perform a task in accordance with a schedule on the parcel, the robotic vehicle comprising one or more functional components configured to execute a lawn care functions associated with the task, the lawn care functions comprising grass mowing and the one or more functional components comprising a blade control system comprising a cutting blade for grass mowing; wherein the robotic vehicle is configured to: move to the plurality of fixed sensors within the parcel, read data from each of the plurality of fixed sensors, store the data read from each of the plurality of fixed sensors on a memory device of the robotic vehicle, and execute an adjustment to the schedule based on lawn wellness information, the lawn wellness information being determined based on the data read from each of the plurality of fixed sensors by the robotic vehicle. ### Claim 15 (depends on 14) The robotic vehicle of claim 14, wherein the robotic vehicle is configured to transfer power, via inductive power transmission, from a power source of the robotic vehicle to at least one of the plurality of fixed sensors to power or recharge a battery of the at least one of the plurality of fixed sensors. ### Claim 16 (depends on 14) The robotic vehicle of claim 14, wherein the robotic vehicle is configured to transfer power from a power source of the robotic vehicle to a sprinkler to operate a valve of the sprinkler via a wired or wireless connection between the robotic vehicle and the sprinkler. ### Claim 17 (depends on 14) The robotic vehicle of claim 14, wherein the robotic vehicle further comprises an RFID reader and the robotic vehicle is configured to read an RFID tag of at least one of the plurality of fixed sensors within the parcel and capture a position of the robotic vehicle when the RFID tag is read to determine a location of the at least one of the plurality of fixed sensors. ### Claim 18 (depends on 14) The robotic vehicle of claim 14, robotic vehicle is configured to use low power short range communications to read the data from each of the plurality of fixed sensors. ### Claim 19 (depends on 18) The robotic vehicle of claim 18, wherein the robotic vehicle uses high power communications to transmit the transmit the data read from each of the plurality of fixed sensors to an application manager. ### Claim 20 (depends on 14) The robotic vehicle of claim 14, wherein the robotic vehicle is further configured to: move to and dock with a battery charging station; and transmit the data read from each of the plurality of fixed sensors to an application manager in response docking with the battery charging station. ### Claim 21 (depends on 14) The robotic vehicle of claim 14, wherein the robotic vehicle is configured to use low power short range communications to transmit the data read from each of the plurality of fixed sensors to the battery charging station.