Lawn Mower Robot Boundary Mapping With Vision and UWB Beacons
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Solution Overview
Problem
Current lawn mower robots require manual setup of movable areas and struggle to accurately define lawn boundaries for autonomous operation, leading to inefficiencies and increased costs.
Innovation Solution
A lawn mower robot equipped with a vision sensor and beacons that use ultra-wideband signals to determine position coordinates and distinguish between lawn and non-lawn areas, automatically generating a map of the working area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If wire is buried to set movable area or beacon is installed to define work area, then the lawnmower robot can detect boundaries and operate autonomously, but the device complexity and installation cost increase
Solution Approach 1:
The vision sensor enables the lawnmower robot to automatically identify lawn boundaries and generate working area maps without requiring manual wire burial or beacon installation. The system performs self-service by autonomously detecting environmental features and creating navigation data structures, eliminating the need for complex pre-installation infrastructure.
Solution Approach 2:
The patent replaces mechanical boundary definition methods (buried wires, physical beacons) with optical detection using a vision sensor. The camera-based system captures images of boundary markers or natural features, and the processor converts these visual inputs into digital map data, substituting mechanical infrastructure with optical-electronic sensing.
2Ease of operation
If manual lawn mowing is performed by user, then direct control is possible, but user labor and time consumption increase
Solution Approach 1:
The lawnmower robot performs lawn mowing autonomously without requiring user operation. The vision sensor captures boundary information, the processor generates working area maps, and the robot executes mowing tasks automatically, enabling the system to serve itself and eliminating the need for user labor in lawn maintenance.
Solution Approach 2:
The system performs preliminary actions by automatically capturing boundary images and generating working area maps before mowing operations begin. This pre-processing of environmental data enables subsequent autonomous navigation and mowing execution without real-time user intervention, saving user time and effort.
3Extent of automation
If vision sensor is used to detect boundary line, then automatic map generation is enabled, but measurement precision requirements increase
Solution Approach 1:
The vision sensor continuously captures images of boundary markers during robot movement, and the processor processes these visual inputs to refine position estimates and update the working area map. This feedback loop allows the system to correct detection errors and improve boundary definition accuracy through iterative processing of visual data.
Solution Approach 2:
The patent introduces boundary markers as intermediary objects that enhance the detectability of lawn edges. These markers serve as visual intermediaries between the natural lawn boundary and the vision sensor, making precision measurement easier by providing high-contrast, easily detectable reference points that the camera can reliably identify and track.
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 lawn area mapping, reduces user intervention, and optimizes mowing work planning by automatically defining boundaries and predicting battery needs.
Implementation Method 1
a tag receiving a signal from a beacon, wherein the beacon transmits a signal using an ultra-wideband signal
Data Source
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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.