Robot Floor Dot-Code Localization for Position and Direction Recovery
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Solution Overview
Problem
Current robot localization methods are ineffective when unexpected movements occur, requiring expensive sensors like LiDAR and being limited to open spaces with distinguishable structures, making it difficult for robots to recognize their location and direction.
Innovation Solution
The use of dot codes with reference dots arranged on the floor, identified by an optical sensor, allows the robot to determine its location and direction, enabling effective recognition and correction without relying on surrounding structures, even in abnormal driving states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDAR sensors and complex matching algorithms are used for robot localization, then measurement precision and reliability are improved, but device cost and complexity increase significantly
Solution Approach 1:
The patent uses a camera to capture an optical image of the environment and matches it with a pre-stored reference image, creating a visual copy-based localization system. This replaces expensive LiDAR sensors with a standard camera, achieving accurate localization through image pattern matching while significantly reducing device cost and complexity
Solution Approach 2:
The patent substitutes the mechanical/optical measurement system (LiDAR) with an electronic image processing system (camera + algorithm). By replacing physical distance measurement with visual pattern recognition, the system achieves comparable localization accuracy using simpler, more cost-effective components
2Measurement precision
If LiDAR sensors and structure-based matching algorithms are used for robot localization, then measurement precision is improved, but adaptability to different environments deteriorates
Solution Approach 1:
The patent creates a universal localization method that works across diverse environments by using general visual features rather than environment-specific structures. The system can adapt to open spaces, corridors, rooms, and outdoor areas by matching any distinguishable visual pattern, making the localization algorithm universally applicable without requiring environment-specific calibration
Solution Approach 2:
The patent changes the localization parameter from physical distance measurements (LiDAR) to visual pattern characteristics (image features). This parameter transformation allows the system to adapt to various environments by detecting and matching visual landmarks, enabling flexible operation in spaces with different structural characteristics
3Productivity
If map-based localization methods are used for robots, then productivity is improved during normal operation, but reliability deteriorates when unexpected movements occur
Solution Approach 1:
The patent implements a feedback mechanism where the robot continuously captures real-time environmental images, compares them with the pre-stored reference map, and corrects its position based on the matching results. This closed-loop feedback system maintains high reliability during unexpected movements by constantly verifying position against visual landmarks, while preserving operational efficiency through automated correction
Solution Approach 2:
The patent performs preliminary actions by pre-storing reference images of the environment and preparing the matching algorithm before the robot needs localization. When unexpected movements occur, the system can immediately perform visual matching without waiting for complex sensor data collection, enabling rapid position correction while maintaining normal operational productivity
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
Enables quick and cost-effective localization and direction recognition for robots, allowing them to execute operations based on identified patterns, improving their ability to correct their position and orientation in various environments.
Implementation Method 1
an optical sensor configured to identify a dot code disposed at a bottom of the space
Data Source
AI summary
A robot and a method for localizing a robot are disclosed. A method for location recognition of a robot includes moving in space; identifying a dot code disposed at a bottom of the space; and determining a location and direction of the robot based on the identified dot code. The dot code includes at least two reference dots arranged to indicate a reference direction. Embodiments of the present disclosure may be implemented by executing artificial intelligence algorithms and/or machine learning algorithms in a 5G environment connected for the Internet of Things.