Inspection Device Lane Line Deviation Correction
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Solution Overview
Problem
Existing inspection devices for road surface monitoring struggle to accurately maintain a preset route, especially when lanes turn, requiring manual steering and affecting detection efficiency due to limited camera views and inability to automatically correct deviations.
Innovation Solution
An inspection device equipped with a control method that collects environment images, identifies lane lines, calculates deviations from a preset route, and adjusts its path to align with the route using cameras and image processing algorithms, allowing for automatic correction and steering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual steering is used to maintain preset route, then route accuracy is improved, but operation complexity and time consumption increase
Solution Approach 1:
The inspection device performs self-steering by automatically identifying lane lines through image processing and adjusting its own trajectory without external manual intervention. The device captures environment images, processes them to identify lane lines, calculates deviations from the preset route, and autonomously corrects its path, enabling the system to serve itself in maintaining route accuracy.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where the inspection device continuously monitors its position relative to the lane lines through image capture and processing, compares the actual position with the desired preset route, and automatically adjusts its trajectory based on the calculated deviation. This feedback loop eliminates the need for manual steering while maintaining high route accuracy.
2Measurement precision
If manual steering is used to navigate lane turns, then route accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The inspection device autonomously handles lane turn navigation by independently identifying lane line geometry, calculating deviation from the preset route, and executing self-steering corrections. The system processes environment images to detect lane line orientations and automatically adjusts its trajectory to follow lane turns without requiring manual intervention, thereby improving ease of operation while maintaining route accuracy.
Solution Approach 2:
The patent replaces manual mechanical steering operations with an automated image processing and control system. Instead of human operators manually controlling the device through lane turns, the system uses computer vision algorithms to identify lane lines, process their geometric features, and automatically generate steering commands, substituting mechanical manual control with an automated electronic control system.
3Device complexity
If camera view is limited to current position, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The image processing system performs preliminary identification and characterization of lane lines before the inspection device reaches the corresponding physical location. By capturing environment images ahead of time and processing them to identify lane line positions, orientations, and curvature, the system prepares navigation data in advance, enabling accurate route following without requiring complex real-time sensing at every moment.
Data Source
AI summary
The present disclosure provides an inspection device, a control method and a control apparatus for the same, and relates to the technical field of inspection patrol. The inspection device can patrol in a lane which has at least one lane line. The control method includes collecting an environment image around the inspection device. The control method includes identifying the lane line from the environment image. The control method includes determining a distance between the inspection device and the lane line. The control method includes determining a deviation between the inspection device and a preset route in the lane according to the distance between the inspection device and the lane line. The control method includes controlling the inspection device to move toward the preset route according to the deviation.


