Robotic Lawnmower Mapping of Grass Conditions for Adaptive Mowing
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Solution Overview
Problem
Existing robotic lawnmowers lack the ability to autonomously assess and adapt to varying vegetation characteristics and weather conditions, leading to inefficient mowing operations and potential damage to lawns.
Innovation Solution
Equipping robotic lawnmowers with vegetation characteristic sensors to detect moisture content, grass height, and color, and integrating a system that adjusts mowing schedules based on real-time data and weather forecasts, while also providing users with recommendations for lawn care through a remote interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If robotic lawnmowers operate autonomously without vegetation sensing, then device complexity is reduced, but lawn care effectiveness and adaptability deteriorate
Solution Approach 1:
The patent replaces manual lawn care decision-making with automated sensor-based detection and analysis systems. Vegetation characteristic sensors (optical, capacitive, impedance) automatically detect grass health parameters, eliminating the need for manual inspection while providing adaptive mowing recommendations based on real-time vegetation data.
Solution Approach 2:
The patent introduces a remote device as an intermediary between the robotic lawnmower and the user. The remote device receives vegetation data from sensors, processes it to generate health assessments and mowing recommendations, and presents this information to the user in an actionable format, bridging the gap between complex sensor data and simple decision-making.
2Productivity
If robotic lawnmowers use basic mowing schedules, then ease of operation is improved, but productivity and lawn health optimization deteriorate
Solution Approach 1:
The patent implements a feedback loop where vegetation characteristic sensors continuously monitor grass health parameters (color, moisture, electrical properties), the system analyzes this data to assess lawn conditions, and automatically adjusts mowing recommendations based on the assessed health status. This closed-loop feedback enables dynamic optimization of mowing schedules without requiring user intervention.
Solution Approach 2:
The patent transforms static, pre-programmed mowing schedules into dynamic, adaptive schedules that automatically adjust based on real-time vegetation conditions. The system modifies mowing frequency and timing dynamically in response to detected grass health changes, weather conditions, and growth rates, optimizing productivity while maintaining simple user interaction through the remote device.
3Measurement precision
If robotic lawnmowers lack vegetation detection capability, then manufacturing cost and device complexity are reduced, but measurement precision and lawn care quality deteriorate
Solution Approach 1:
The patent employs multi-functional sensor systems that detect multiple vegetation characteristics simultaneously using a single integrated sensing platform. The sensors measure optical properties (color), electrical properties (impedance, capacitance), and physical properties (moisture) to comprehensively assess grass health, enabling precise multi-parameter detection while consolidating hardware complexity into a unified sensing system.
Data Source
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AI summary
A method of mowing with an autonomous robot lawnmower includes traversing a mowable area with the autonomous robot lawnmower carrying a cutter and a vegetation characteristic sensor. The vegetation characteristic sensor is configured to generate sensor data in response to detecting a vegetation characteristic of the mowable area. The vegetation characteristic is selected from the group consisting of a moisture content, a grass height, and a color. The method includes storing position-referenced data representing the vegetation characteristic detected across the mowable area. The position-referenced data is based at least in part on the sensor data and position data. The method includes sending data to a remote device to cause the remote device to display a map including information based on the position-referenced data.