Ceiling Vision Robot Positioning via Dynamic Road Sign Management
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Solution Overview
Problem
Existing visual robot positioning technologies face challenges due to uneven construction of road signs, leading to low positioning accuracy and high error rates, especially when environmental characteristics are confusing.
Innovation Solution
A positioning method for ceiling vision robots that involves acquiring real-time ceiling images, recognizing existing road sign distribution, determining whether to establish new road signs based on distance and illumination thresholds, and monitoring the effectiveness of existing road signs for accurate positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If road signs are constructed in complex environmental conditions, then the robot can operate in diverse environments, but the positioning accuracy decreases due to confusing environmental characteristics
Solution Approach 1:
The patent applies local quality by making road signs with distinct local characteristics (specific shapes, colors, and patterns) that differ from the surrounding environment. The road signs have unique visual features such as quadrangular shapes with specific color combinations (yellow background with black patterns) that make them locally distinguishable from complex environmental backgrounds, enabling accurate identification even in diverse environments.
Solution Approach 2:
The patent utilizes color changes and specific color combinations in road signs to enhance their distinguishability. The road signs employ high-contrast color schemes (yellow background with black patterns, or blue background with white patterns) that create strong visual differentiation from the environment, allowing the vision system to reliably identify road signs regardless of environmental complexity.
2Ease of manufacture
If visual robot positioning relies on environmental road signs, then positioning can be achieved without additional infrastructure, but positioning error rate increases due to uneven construction and environmental confusion
Solution Approach 1:
The patent applies preliminary action by pre-establishing a systematic framework for road sign construction before deployment. The method includes pre-defining specific construction standards (quadrangular shapes, color combinations, pattern arrangements, spacing requirements) and pre-processing environmental data to identify suitable locations. This preliminary preparation ensures that when road signs are constructed, they meet consistent quality standards that enhance positioning reliability.
Solution Approach 2:
The patent utilizes parameter changes by systematically varying key parameters of road signs including shape (quadrangular configurations), color combinations (yellow-black or blue-white patterns), size parameters, and spatial arrangement. These controlled parameter variations create distinct, recognizable features that improve detection accuracy and reduce positioning errors while maintaining deployment simplicity.
3Measurement precision
If the robot establishes new road signs frequently, then positioning coverage is improved, but the uneven construction leads to lower positioning accuracy
Solution Approach 1:
The patent applies dynamics by implementing adaptive road sign establishment strategies. The system dynamically adjusts road sign construction decisions based on real-time evaluation of environmental conditions, existing road sign distribution, and positioning requirements. The robot continuously monitors and updates road sign locations, optimizing the distribution to achieve uniform coverage while maintaining construction quality standards.
Solution Approach 2:
The patent utilizes feedback mechanisms where the robot continuously monitors positioning accuracy and road sign effectiveness. Based on this feedback, the system adjusts road sign establishment decisions, modifying construction parameters or locations to improve uniformity. The feedback loop ensures that road sign construction maintains consistent quality while achieving adequate positioning coverage.
Data Source
AI summary
A positioning method for a ceiling vision robot are provided. The method includes: during a moving process, a ceiling vision robot acquiring a ceiling image in real time; acquiring existing road sign distribution information according to the ceiling image; determining whether to establish a new road sign, according to the existing road sign distribution information, and if so, establishing a new road sign at a acquisition position of the ceiling image, and if not, not establishing the new road sign at the acquisition position of the ceiling image; and monitoring the positioning effectiveness of an existing road sign according to the existing road sign distribution information, and if the positioning of the existing road sign is effective, performing positioning by using pose information corresponding to the existing road sign, and if the positioning of the existing road sign is ineffective, not performing positioning by using the pose information corresponding to the existing road sign. In the method, a ceiling vision robot is used to avoid a situation in which the environment is complex and road signs are thus easily confused; a new road sign is established according to existing road sign distribution information, thereby realizing the uniformly establishment of road signs; and effectiveness detection is performed on an existing-road sign, thereby improving the precision of positioning based on road signs.