Autonomous Work Machine Control When Boundary Markers Are Lost
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Solution Overview
Problem
Existing autonomous work machines face difficulties in continuing operations when some or all markers defining the work area are lost, as they rely on these markers for navigation and boundary recognition.
Innovation Solution
An autonomous work machine equipped with a storage system for past captured images, a mechanism to specify similar images, and a control system that uses these images to maintain operation even if markers are missing, by setting virtual lines and controlling the machine based on past image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If markers are used to define the work area for autonomous navigation, then position recognition accuracy is improved, but system reliability deteriorates when markers are lost
Solution Approach 1:
The system performs preliminary actions by capturing and storing images of the work area and markers before actual autonomous work begins. These pre-captured images serve as reference data that the autonomous work machine can use to identify its position and continue work even when physical markers are lost or damaged during operation.
Solution Approach 2:
The system creates a copy of the work area environment by storing images captured during setup. Instead of relying solely on physical markers, the system uses these image copies as virtual references for position recognition, allowing the machine to identify its location by comparing current camera input against the stored image database.
2Measurement precision
If multiple markers are arranged to define the work area, then navigation accuracy is improved, but loss of markers causes work interruption
Solution Approach 1:
The system captures images of the work area and markers in advance before autonomous work begins. These pre-captured images store the spatial relationships and marker positions, creating a reference database that enables the machine to continue navigation and work even if physical markers are lost during operation.
Solution Approach 2:
The system creates digital copies of the work area environment through stored images. These image copies serve as virtual markers that replace physical markers for position identification, allowing the autonomous machine to maintain navigation accuracy without being dependent on the physical presence of all original markers.
3Speed
If the system relies on current captured images for control, then real-time responsiveness is improved, but ability to continue work when markers are lost deteriorates
Solution Approach 1:
The system performs preliminary image capture and storage before autonomous work begins. By pre-caching the work area environment in stored images, the system ensures that reference data is available immediately when needed, maintaining real-time control responsiveness while providing a backup when current marker recognition fails.
Solution Approach 2:
The stored images act as an intermediary between the physical markers and the control system. When physical markers are lost or cannot be recognized, the control system uses the stored image data as a mediator to maintain position identification and continue work without interruption.
Data Source
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Figure 3
Figure 4A
AI summary
An autonomous work machine that works in a work area, the autonomous work machine comprising: a storage means that stores past captured images including one or more markers arranged to define the work area; a specifying means that specifies a past captured image stored in the storage means and similar to a current captured image captured by an image capturing means; and a control means that controls the autonomous work machine based on the past captured image specified by the specifying means.