Autonomous Field Work Vehicle Abnormality Detection and Mapping
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Solution Overview
Problem
Autonomous grass mowers lack the ability to detect field defects such as pits, foreign objects, and other hazards, making them insufficient for comprehensive field maintenance.
Innovation Solution
An autonomous traveling work vehicle equipped with a positioning device, a work device, a determining device, an abnormality detection section, and an abnormality information outputting section, which detects and reports field defects using self-positioning information, determination data, and image capture, integrated with a field management system for map-based abnormality reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous traveling work vehicle performs field maintenance work automatically, then manpower saving and unmanned implementation are achieved, but the managing person cannot detect field defects such as pits, muddy spots, and foreign objects
Solution Approach 1:
The autonomous traveling work vehicle performs self-diagnosis and self-monitoring by detecting its own operational status, traveling conditions, and work device performance. The determining device continuously monitors parameters such as traveling load, work load, tilt, and acceleration to identify abnormalities without human intervention.
Solution Approach 2:
The system establishes a feedback loop where the determining device sends determination data to the abnormality detection section, which then outputs abnormality information with position data to the terminal. This closed-loop feedback enables continuous monitoring and automatic reporting of field defects, compensating for the lack of human visual inspection.
2Measurement precision
If autonomous grass mower recognizes work area borderline using photographing means and ground surface sensor, then work area determination is improved, but the system remains insufficient for detecting field defects such as pits and foreign objects
Solution Approach 1:
The autonomous traveling work vehicle integrates multiple functions into a single system: it performs grass cutting work, recognizes work area borders, detects field defects, and reports abnormalities. The determining device and abnormality detection section enable the vehicle to serve both as a work machine and a monitoring system, enhancing versatility without adding separate dedicated devices.
Solution Approach 2:
The determining device acts as an intermediary between the vehicle's sensors and the abnormality detection section. It processes raw sensor data regarding traveling conditions and work device status, transforming this data into meaningful determination data that the abnormality detection section can analyze to identify field defects.
3Reliability
If autonomous traveling work vehicle is equipped with determination device and abnormality detection section, then field defect detection capability is improved, but device complexity increases
Solution Approach 1:
The patent merges the determination device with the vehicle's existing control system, integrating abnormality detection functions into the current autonomous navigation and work control architecture. This consolidation allows defect detection capabilities to be added without proportionally increasing overall system complexity, as shared hardware and processing resources are utilized.
Data Source
AI summary
An autonomous traveling work vehicle includes a traveling vehicle body, a positioning device mounted on the traveling vehicle body and configured to acquire self-vehicle position information indicative of a self-vehicle position, a work device for effecting a work for a field, a determining device for determining a condition of at least either one of the traveling vehicle body and the work device during traveling of the traveling vehicle body, an abnormality detection section for detecting abnormality in the field based on determination data determined by the determining device, and an abnormality information outputting section for outputting, as abnormality information, the self-position information in the case of detection of abnormality by the abnormality detection section.