Laser Obstacle Recognition Using Reference Line Stripe Filtering
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Solution Overview
Problem
Mobile robots face challenges in accurately identifying obstacles with reflective or light-absorbing materials and varying shapes due to environmental conditions, which affect their obstacle avoidance capabilities.
Innovation Solution
The method involves acquiring a laser image, extracting candidate laser stripes, determining a theoretical position of a reference laser line, and screening valid laser stripes based on this position to improve obstacle identification accuracy, using a horizontal line laser to minimize reflection and refraction effects, and employing background subtraction with motion compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional laser detection methods are used to identify obstacles, then the system is simple to implement, but the identification accuracy deteriorates when obstacles have reflective or light-absorbing materials
Solution Approach 1:
The patent transitions from traditional single-line laser detection to line laser technology, adding dimensional complexity to the laser pattern. This dimensional change allows the system to capture more spatial information about obstacles, improving identification accuracy for reflective and light-absorbing materials by providing multiple measurement points across the obstacle surface simultaneously.
Solution Approach 2:
The patent introduces a reference laser line as an intermediary element to establish a theoretical position baseline. By comparing candidate laser stripes against this reference framework, the system can accurately identify valid laser stripes even when obstacles have challenging optical properties like high reflectivity or light absorption, thereby improving measurement precision.
2Reliability
If multiple candidate laser stripes are extracted to improve detection robustness, then the detection reliability improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent extracts only the valid laser stripes from multiple candidate laser stripes by comparing them against a theoretical position derived from reference laser line equations. This extraction process filters out unnecessary data, maintaining detection reliability while reducing processing complexity by focusing computational resources only on relevant candidates.
Solution Approach 2:
The patent employs feedback mechanisms where the theoretical position of the reference laser line is used to validate and screen candidate laser stripes. This feedback loop allows the system to maintain high detection reliability by continuously comparing actual measurements against expected positions, while managing processing complexity through efficient validation criteria.
3Measurement precision
If background subtraction is used to improve signal-to-noise ratio, then the obstacle detection accuracy improves, but the processing time increases due to motion compensation requirements
Solution Approach 1:
The patent performs preliminary background subtraction before final obstacle detection, establishing a clean reference framework in advance. By preparing the background model beforehand and using it to subtract from current laser images, the system improves signal-to-noise ratio while managing processing time through efficient pre-computation of background characteristics.
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
Enhances the accuracy of obstacle identification by filtering out noise and improving the detection of valid laser stripes, allowing for precise obstacle detection and navigation.
Implementation Method 1
acquiring a laser image of a target area; extracting candidate laser stripes from the laser image
Implementation Method 2
emitting a horizontal line laser to the target area; obtaining the laser image of the target area
Data Source
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AI summary
The present disclosure provides an obstacle recognition method, an apparatus, an electronic device, and a storage medium. The method comprises: collecting a laser image of a target area; extracting candidate laser bars in the laser image; obtaining the theoretical position of a reference laser line in the laser image; selecting valid laser bars from among the candidate laser bars on the basis of the theoretical position; and obtaining the position of an obstacle on the basis of the position of the valid laser bars in a world coordinate system.