Image-Based Work Machine Control for Adaptive Lawn Care

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Solution Overview

Problem

Current autonomous lawn mowing and gardening systems lack efficient control mechanisms to adapt to varying lawn conditions, such as grass density and health, leading to suboptimal mowing and watering practices.

Innovation Solution

A control device that integrates image acquisition, feature recognition, and parameter decision-making to adjust the lawn mower's travel speed, mowing strength, and watering based on real-time image analysis of lawn conditions, utilizing machine learning and deep learning techniques for precise decision-making.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If autonomous lawn mowing and gardening systems operate with fixed control parameters, then device complexity is reduced, but work quality deteriorates due to inability to adapt to varying lawn conditions

Engineering Contradiction:

Improveadaptability to varying lawn conditionsVSAvoidcontrol mechanism complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The control parameters (travel speed, mowing strength, watering amount) are made dynamic rather than fixed. The control device adjusts these parameters in real-time based on image analysis results, allowing the system to adapt to varying lawn conditions such as grass density, height, and health status without requiring complex manual intervention.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements a feedback loop where images of lawn conditions are captured, analyzed by the control device, and used to adjust control parameters for subsequent operations. This closed-loop control enables the system to learn from and respond to actual lawn conditions, improving work quality while maintaining automated operation.

Inventive Principle:

Principle #23Feedback

2Manufacturing precision

If real-time image analysis is implemented to adjust control parameters, then work quality improves, but processing time increases

Engineering Contradiction:

Improvemowing and watering precisionVSAvoidimage processing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The control device performs image analysis and determines optimal control parameters in advance before executing the actual mowing and watering operations. This allows the system to prepare adjustment decisions beforehand, ensuring precise control during execution without significant time delays during the actual work process.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements periodic image capture and analysis at intervals during operation, rather than continuous analysis. This approach maintains adequate processing precision while reducing overall processing time and computational load, allowing the lawn mower to efficiently cover larger areas.

Inventive Principle:

Principle #19Periodic action

3Productivity

If autonomous operation is implemented, then productivity increases, but control precision deteriorates due to lack of real-time adaptation

Engineering Contradiction:

Improvework efficiencyVSAvoidcontrol parameter accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The lawn mower system performs self-diagnosis and self-adjustment by capturing images of its own operating environment and automatically determining optimal control parameters. This autonomous decision-making capability maintains high productivity while improving control precision, as the system adapts to real-time conditions without human intervention.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual control mechanisms with automated image analysis and algorithm-based parameter determination. This substitution enables the autonomous lawn mower to achieve both high productivity through automated operation and high control precision through real-time image-based decision making.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11457559B2Control device, work machine and non-transitory computer readable medium storing program

Publication Date: 2022.10.04 HONDA MOTOR CO LTD

AI summary

A control device includes: an image acquiring section that acquires image data of an image of a work target of the work machine; a feature recognizing section that recognizes a feature about at least one of (i) a type of the work target of the work machine, (ii) a number or density of the work target, (iii) a shape of the work target and (iv) an appearance of the work target after work, based on the image data acquired by the image acquiring section; and a control parameter deciding section that decides at least either (i) a parameter for controlling travel of the work machine or (ii) a parameter for controlling work of the work machine, based on the feature recognized by the feature recognizing section.