Autonomous Mower Cutting-State Monitoring With Image Feedback
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Solution Overview
Problem
Current autonomous work machines, such as lawn mowers, lack efficient mechanisms for real-time monitoring and adjustment of cutting performance and lawn health, leading to suboptimal operation and maintenance schedules.
Innovation Solution
Integration of an image-capturing section and a judging section within the work machine that captures images of the cutting process and analyzes them to assess the cutting performance and lawn health, using machine learning to determine the state of the cutting section and recommend maintenance or adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If autonomous work machines operate without real-time monitoring mechanisms, then device complexity is reduced, but cutting performance and lawn health assessment capability deteriorates
Solution Approach 1:
The patent implements real-time feedback mechanisms where images captured by the image-capturing section are immediately analyzed by the judging section to assess cutting performance and lawn health. This feedback loop enables the autonomous work machine to monitor its operation continuously and make real-time adjustments, resolving the contradiction by providing precise measurement capability through an integrated monitoring system.
Solution Approach 2:
The judging section is designed to perform multiple functions: analyzing cutting performance, assessing lawn health, and determining maintenance needs. This multi-functional approach allows the system to achieve comprehensive monitoring capability without proportionally increasing device complexity, as a single integrated component handles diverse assessment tasks.
2Productivity
If real-time image analysis is implemented to monitor cutting performance, then productivity is improved through optimized operation, but use of energy increases due to continuous image processing
Solution Approach 1:
The judging section performs image analysis selectively based on operational conditions rather than continuously analyzing every image. The system determines when analysis is necessary based on detected changes in cutting performance or lawn conditions, reducing overall energy consumption while maintaining productivity benefits through targeted monitoring at critical moments.
3Reliability
If autonomous optimization based on real-time feedback is implemented, then reliability of cutting operation is improved, but device complexity increases due to additional control mechanisms
Solution Approach 1:
The control device integrates the image-capturing section and judging section into a unified system that combines sensing, analysis, and control functions. By merging these components into a single integrated control architecture, the system achieves reliable autonomous optimization while minimizing the increase in device complexity through consolidated design rather than separate independent systems.
Data Source
AI summary
A work machine having an autonomous travel function may include: a cutting section that cuts a work target of the work machine; an image-capturing section that captures an image of the work target cut by the cutting section; and a judging section that judges a state of the cutting section based on the image captured by the image-capturing section. The judging section may judge whether maintenance of or a check on the cutting section is necessary or not based on a result of judgment about the state of the cutting section.