Robot Floor Marker Recognition for Autonomous Cart Lining Up
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Solution Overview
Problem
Conventional cart-robots require user intervention for navigation in spaces with specific constraints, such as checkout counters and moving walks, leading to inefficiencies and increased labor in managing their movement.
Innovation Solution
A cart-robot equipped with a camera sensor and control unit that recognizes markers on the floor, analyzing visual characteristics like color, shape, and flickering patterns to adjust speed and direction, enabling autonomous movement and lining up within designated spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a cart-robot operates autonomously in spaces with movement constraints (checkout counters, moving walks), then user convenience and productivity are improved, but the system requires complex space recognition and navigation capabilities that increase device complexity
Solution Approach 1:
The patent introduces markers as intermediary objects placed in the environment to facilitate communication between the cart-robot and the constrained space. These markers serve as mediators that carry recognition information, enabling the robot to understand space constraints without requiring complex environmental sensing. The marker system acts as an external memory and instruction source that simplifies the robot's navigation task.
Solution Approach 2:
The patent replaces complex mechanical navigation systems with an optical recognition system. Instead of using sophisticated sensors and algorithms to understand space constraints, the cart-robot uses a camera to capture images of markers and a recognition unit to extract navigation information from visual patterns. This substitution of optical recognition for mechanical navigation sensing reduces system complexity.
2Measurement precision
If the cart-robot uses marker recognition with multiple visual characteristics (color, shape, flickering patterns), then navigation precision and speed control are improved, but the image processing complexity and time required for recognition increase
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple visual characteristics (color, shape, flickering patterns) in the marker design before deployment. These characteristics are predetermined and encoded in the marker structure, allowing the recognition system to quickly identify and interpret navigation information without performing complex real-time analysis. The information is prepared in advance in the marker itself.
Solution Approach 2:
The patent utilizes color changes and visual pattern variations as a means of encoding navigation information in markers. Different colors, shapes, and flickering patterns represent different instructions (e.g., move forward, turn left, stop). This visual encoding system allows the robot to rapidly distinguish between different navigation commands through simple image analysis, reducing processing time while maintaining high recognition precision.
3Manufacturing precision
If the cart-robot autonomously adjusts speed and direction based on marker recognition, then movement accuracy in constrained spaces is improved, but the control system complexity increases
Solution Approach 1:
The patent implements feedback by continuously monitoring the cart-robot's position relative to markers and adjusting speed and direction based on recognition results. The control unit receives navigation information from marker recognition and dynamically modifies movement parameters to maintain accurate positioning. This closed-loop feedback system enables precise movement control without requiring overly complex mechanical systems.
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
The cart-robot can move autonomously and adjust its speed and direction based on marker recognition, enhancing user convenience and reducing labor by navigating through spaces without user intervention, particularly in areas with restricted movement patterns.
Implementation Method 1
a camera sensor that images a marker disposed on a traveling floor of the cart-robot or a side of the traveling floor
Data Source
AI summary
Provided are a marker for space recognition, a method of moving and lining up a robot based on space recognition, and a robot, and the robot that lines up and moves based on space recognition includes: a camera sensor that images a marker disposed on a traveling floor of the robot or a side of the traveling floor; and a control unit that analyzes an image captured by the camera sensor, calculates a moving direction or a moving speed of the robot on the basis of the marker, and controls a movement unit.