Laser Map Working Area Expansion to Avoid Room Fragmentation
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Solution Overview
Problem
Existing methods for expanding indoor working areas using laser maps often result in large free areas being divided into multiple small areas, reducing robot efficiency and making it difficult for robots to navigate along the edge of the working area effectively.
Innovation Solution
A method that sets pending boundary lines along coordinate axes in real-time laser maps, selects the closest boundary line to frame an initial rectangular working area, and expands it by deleting perpendicular boundary lines based on priority conditions, stopping expansion when the diagonal length increment is less than a preset overlap size error value to maintain a reasonable working area size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot uses obstacle positions to define working area boundaries, then the working area can be established, but large free areas are divided into multiple small areas reducing robot efficiency
Solution Approach 1:
The patent segments the working area definition process into two stages: first establishing initial boundaries using obstacle positions, then merging adjacent small areas through iterative expansion. This segmentation allows the system to handle complex environments systematically while avoiding the creation of inefficiently small divided areas.
Solution Approach 2:
The patent merges multiple small working areas into larger contiguous areas by expanding boundaries based on robot navigation capabilities. Adjacent small areas that would otherwise be separated by minor obstacles are combined into unified working zones, improving robot efficiency by reducing the number of separate area transitions required.
2Productivity
If the robot navigates along edge contours to search for targets, then coverage is improved, but the working area must be properly framed to enable effective edge-following navigation
Solution Approach 1:
The patent performs preliminary framing of the working area before navigation begins. By pre-establishing proper boundary contours that are suitable for edge-following algorithms, the system prepares the navigation environment in advance, making the actual navigation process simpler and more effective without requiring complex real-time adjustments.
3Area of stationary object
If the working area is expanded without constraints, then coverage area increases, but the area becomes unreasonably large reducing navigation efficiency
Solution Approach 1:
The patent implements dynamic working area expansion where boundaries are adjusted iteratively based on robot position and environmental feedback. The area expands when beneficial for coverage but contracts or stabilizes when becoming excessively large, creating a dynamic balance between coverage and navigation efficiency that adapts to the specific environmental context.
Data Source
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AI summary
The present disclosure provides a method for expanding a working area based on a laser map, a chip and a robot, and the method for expanding the working area includes using map pixel point information obtained by laser scanning to position pending boundary lines, deciding a next expansion of a rectangular working area according to an increment of a diagonal length of the rectangular working area framed by the pending boundary lines in a current expansion process, stopping expanding the rectangular working area of the robot when the increment of the diagonal length before expanding and after expanding reaches an overlap condition, which avoids a large connected area being dividing into a plurality of small areas in a process of dividing room areas, thus reducing working efficiency of the robot in indoor working areas. It is possible to save operation resources of the robot framing the working area, avoid using software resources to process framing and separating of corner areas of these isolated rooms, and there is no need to ensure that contour boundary positions of the working area framed on an indoor ground are all walls, thereby improving efficiency of the robot navigation along an edge.