Automatic Vehicle Marker Detection and Boundary Mapping
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Solution Overview
Problem
Existing automatic operation vehicles require significant user labor to set operation areas and struggle with accurately navigating around visual obstacles during this process.
Innovation Solution
An automatic operation vehicle equipped with a camera, image analysis unit, and survey unit that uses triangulation to acquire and update position information of markers, allowing it to autonomously set and maintain the operation area without physical barriers, while avoiding obstacles by determining optimal moving directions to minimize contact with markers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the automatic operation vehicle uses visual markers for position recognition, then the ease of operation is improved, but the reliability deteriorates when obstacles block the camera view
Solution Approach 1:
The system performs preliminary actions by acquiring position information of multiple markers and determining the operation area boundary before actual operation begins. This allows the vehicle to pre-map the operation area using visible markers, then rely on stored boundary data during operation, reducing real-time camera dependency.
Solution Approach 2:
The control unit acts as an intermediary between the camera/position recognition system and the navigation system. When the camera cannot detect markers due to obstacles, the control unit switches to using pre-stored operation area boundary data to guide the vehicle, ensuring continuous reliable operation without direct camera input.
2Ease of operation
If the automatic operation vehicle guides itself along the boundary to set the operation area, then the ease of operation is improved, but the loss of time increases due to repeated boundary following
Solution Approach 1:
The system performs preliminary boundary mapping by acquiring marker positions and calculating the operation area boundary once during setup. This pre-established boundary information is then stored and reused for navigation, eliminating the need for repeated boundary following operations.
Solution Approach 2:
The system creates a digital copy of the operation area boundary based on marker positions. Instead of physically following the boundary repeatedly, the vehicle uses the stored boundary coordinate data to navigate directly to target positions within the operation area, significantly reducing setup time.
3Measurement precision
If the automatic operation vehicle uses a camera and image analysis for position recognition, then the measurement precision is improved, but the use of energy increases due to continuous image processing
Solution Approach 1:
The system performs preliminary position recognition to acquire marker positions and establish the operation area boundary before operation begins. During actual operation, it uses the pre-calculated boundary data for navigation decisions, minimizing continuous camera operation and image processing.
Solution Approach 2:
The camera and image analysis unit operate periodically or on-demand rather than continuously. The system activates visual recognition only when needed for initial marker detection or when boundary verification is required, rather than maintaining constant image processing during all operation phases.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces user labor in setting operation areas and enhances accuracy in navigating around visual obstacles, enabling the vehicle to autonomously operate within defined boundaries with improved efficiency and reduced power consumption.
Implementation Method 1
a survey unit that acquires position information of a marker by using triangulation
Data Source
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AI summary
An automatic operation vehicle (10) that automatically performs an operation in an operation area is provided. The vehicle includes an image analysis unit (43) configured to extract a marker (71) included in an image captured by a camera (21) provided on the automatic operation vehicle. If a situation in which the marker that was extracted from the image captured by the camera cannot be extracted by the image analysis unit from the image captured by the camera has occurred during a movement of the automatic operation vehicle in a constant direction. The image analysis unit determines whether the marker extracted before an occurrence of the situation and the marker extracted after an elimination of the situation are the same marker.