Floor Treatment Machine Route Segmentation for Low-Storage Navigation
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Solution Overview
Problem
Existing automatic floor treatment machines face inefficiencies in navigating and cleaning dynamic floor surfaces with movable obstacles, requiring extensive mapping and data storage, which limits their use in professional and variable environments.
Innovation Solution
A method involving determining a treatment direction with forwards and backwards orientation, providing driving lines perpendicular to the treatment direction, following route segments, and adjusting directions when encountering obstacles, with storage of starting and end points and treatment states to enable efficient contour-following movements and minimal data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the floor surface is mapped as accurately as possible and an advantageous route is determined using grids for storing map data and cleaned areas, then the cleaning route optimization is improved, but the data storage capacity and processing effort increase significantly
Solution Approach 1:
The floor surface is divided into driving lines that are spaced apart from one another and perpendicular to the treatment direction. The controller stores only the starting and end points of route segments on each driving line, rather than mapping the entire floor surface with fine grids. This segmentation approach reduces data storage requirements while maintaining effective route planning.
Solution Approach 2:
The invention extracts only the essential information needed for route planning - the starting and end points of route segments on driving lines - and stores this minimal data in route segment storage. This extraction of critical data points eliminates the need for storing complete grid-based maps, significantly reducing data storage capacity requirements.
2Quantity of substance
If the floor surface is traversed at random without creating a map and cleaning route plan, then the storage capacity required is small, but the processing movement effort and cleaning time increase significantly
Solution Approach 1:
The controller preliminarily determines driving lines spaced apart from one another and perpendicular to the treatment direction, along with route segments having starting and end points. This preliminary structuring of the cleaning path enables efficient navigation without requiring complete floor mapping, achieving a balance between minimal storage and reduced cleaning time.
Solution Approach 2:
The system dynamically adjusts the cleaning route by storing route segments that can be modified based on obstacles detected during cleaning. The controller follows route segments from starting points to end points and determines opposite driving directions on adjacent driving lines, enabling adaptive path planning with minimal data storage.
3Measurement precision
If targets with barcodes are mounted on room boundaries for position detection, then the position detection accuracy is improved, but the device complexity and setup effort increase
Solution Approach 1:
The floor treatment machine determines its position and orientation by detecting positioning areas on the floor surface itself using a scan sensor, without requiring external targets or markers to be mounted on room boundaries. The machine uses distance measurements from the scan sensor combined with drive information to autonomously determine position, eliminating the need for target mounting and barcode scanning systems.
4Measurement precision
If a grid map with high resolution is used to accurately represent room boundaries and obstacles, then the mapping precision is improved, but the data processing complexity and storage requirements increase
Solution Approach 1:
Instead of creating a continuous high-resolution grid map, the invention segments the floor surface into discrete driving lines with route segments defined by starting and end points. This segmentation maintains sufficient mapping precision for navigation while dramatically reducing data processing complexity and storage requirements compared to fine grid-based approaches.
Data Source
AI summary
A floor treatment machine is disclosed for treating floor surfaces and includes a housing, two drive wheels, at least one support wheel, a drive device, a controller, at least one scan sensor configured to ensure that distance measurements can be carried out in a substantially horizontal plane via a predetermined angular area, and a floor treatment device configured to ensure that the floor can be treated. In at least one embodiment, the controller encompasses a treatment mode, which guarantees a simple and reliable selection of a successful route by way of few driving and storing steps. The boundary of the floor surface is treated as an obstacle. To record the treated surface, starting and end points of route segments, which have been followed, and one of the states “completely treated” or “incompletely treated” for the end points as well as direction information is stored.