Lawn Mower Robot Boundary Mapping with Vision and UWB Tags
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Solution Overview
Problem
Existing lawn mower robots require manual setup of movable areas and rely on wires or beacons for navigation, which is inefficient and costly, as they need pre-defined paths and lack the ability to autonomously generate maps of their working area.
Innovation Solution
A lawn mower robot equipped with tags to receive signals from beacons, a vision sensor to distinguish between lawn and non-lawn areas, and a processor to determine position coordinates and generate a map of the working area, using ultra-wideband signals and triangulation methods for accurate boundary line detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wires or beacons are used for navigation, then the robot can detect the operating area boundary, but the system complexity and installation cost increase
Solution Approach 1:
The patent extracts the boundary detection function from physical infrastructure (wires/beacons) and transfers it to the robot's vision sensor system. The robot independently identifies boundaries by analyzing visual features of the lawn area, eliminating the need for external navigation aids and reducing system complexity.
Solution Approach 2:
The robot performs self-navigation by using its own vision sensor to detect and map the operating area boundaries. The system serves itself by autonomously generating the map without requiring external wire installation or beacon placement, reducing both complexity and installation cost.
2Reliability
If manual setup of movable areas is required, then the robot can operate within defined boundaries, but labor costs and operational efficiency decrease
Solution Approach 1:
The robot performs preliminary area mapping autonomously by detecting boundaries and generating a map before starting the mowing operation. This preliminary action eliminates the need for manual area setup while ensuring reliable operation within the detected boundaries, improving both efficiency and reliability.
Solution Approach 2:
The patent replaces manual mechanical setup of boundaries with an automated vision-based detection system. The robot uses its camera and image processing algorithms to automatically identify and map the operating area, substituting human labor with automated visual recognition technology.
3Ease of operation
If pre-defined paths are used for navigation, then the robot can follow a set route, but the ability to adapt to different lawn areas is reduced
Solution Approach 1:
The patent implements dynamic path generation where the robot adapts its navigation route based on real-time detection of the actual lawn boundaries. Instead of following fixed pre-defined paths, the robot dynamically adjusts its trajectory to match the detected operating area, enhancing adaptability while maintaining operational simplicity through automated mapping.
Solution Approach 2:
The system changes the navigation parameter from fixed pre-defined paths to dynamically generated paths based on detected boundary coordinates. The robot adjusts its movement parameters according to the actual lawn area shape and size, enabling versatility across different areas while keeping operation simple through automated adaptation.
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 autonomous navigation and accurate mapping of the lawn area, reducing labor and operational costs by allowing the robot to autonomously define its working area and detect obstacles, thereby improving user convenience and operational efficiency.
Implementation Method 1
one or more tags configured to receive a signal from one or more beacons
Implementation Method 2
a vision sensor configured to distinguish and recognize a first area and a second area on a travelling path of the mobile robot, and to acquire position information of a boundary line between the first area and the second area
Data Source
AI summary
A mobile robot and a method of controlling the same are provided, and more specifically, a technology of automatically generating a map of a lawn working area by a lawn mower robot. The mobile robot includes one or more tags configured to receive a signal from one or more beacons, a vision sensor configured to distinguish and recognize a first area and a second area on a travelling path of the mobile robot and acquire position information of a boundary line between the first area and the second area, and at least one processor configured to determine position coordinates of the mobile robot based on pre-stored position information of the one or more beacons, determine position coordinates of the boundary line based on the determined position coordinates of the mobile robot and the acquired position information of the boundary line, and generate a map of the first area while travelling along the determined position coordinates of the boundary line.