Automatic Cleaning Device Path Planning to Escape Carpet Traps
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Solution Overview
Problem
Automatic cleaning apparatuses, such as ground sweeping robots, often get trapped by carpets or obstacles while cleaning, as they fail to detect and navigate around these obstacles effectively, leading to inefficient cleaning and potential damage.
Innovation Solution
The method involves scanning the boundary of a second surface medium region, generating a set of obstacle points, and using a path searching map to determine the shortest escape path when an obstacle-free path is not available, allowing the apparatus to escape from trapped situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the automatic cleaning apparatus cleans along the wall or carpet, then the cleaning coverage is improved, but the apparatus gets trapped by carpets or obstacles
Solution Approach 1:
The system performs preliminary scanning to detect boundary lines of surface medium regions (carpets) before cleaning operations. By identifying these boundaries in advance and incorporating them into the path searching map, the apparatus can plan cleaning paths that avoid trapped situations while maintaining comprehensive cleaning coverage.
Solution Approach 2:
The path searching map serves as an intermediary data structure that integrates obstacle information (boundary lines of surface medium regions) with cleaning path planning. This intermediary representation allows the system to navigate around obstacles effectively while maintaining cleaning efficiency.
2Reliability
If the apparatus detects and navigates around obstacles, then the trapping rate is reduced, but the cleaning efficiency decreases
Solution Approach 1:
The system scans and identifies boundary lines of surface medium regions during the cleaning process, building the path searching map in advance. This preliminary detection allows the apparatus to maintain high cleaning efficiency by avoiding obstacles proactively rather than reacting to them during cleaning operations.
Solution Approach 2:
The scanning and path planning operations are integrated into the continuous cleaning process. The apparatus maintains continuous useful action by seamlessly combining obstacle detection with cleaning operations, ensuring that navigation around obstacles does not significantly interrupt the cleaning workflow.
3Measurement precision
If the apparatus uses a path searching map with obstacle points, then the navigation accuracy is improved, but the computational complexity increases
Solution Approach 1:
The path searching map is constructed by segmenting the environment into discrete boundary lines of surface medium regions. This segmentation approach simplifies the representation of obstacles, allowing for accurate navigation planning while reducing computational complexity compared to using continuous or detailed obstacle models.
4Measurement precision
If the apparatus scans and generates surface medium region sets, then the obstacle detection accuracy is improved, but the processing time increases
Solution Approach 1:
The system performs scanning and generates surface medium region sets during the cleaning operation itself, utilizing idle or transitional time periods. This preliminary action approach allows accurate obstacle detection without significantly extending the overall cleaning time, as the scanning occurs concurrently with or between cleaning passes.
Data Source
AI summary
An automatic cleaning device control method, an automatic cleaning device control apparatus, a computer-readable storage medium, and an electronic device, are described relating to the technical field of smart homes. The method comprises: when an automatic cleaning device cleans in a first surface medium area, scanning boundaries of second surface medium areas, and generating a second surface medium area set; using boundary points in the second surface medium area set as obstacle points and storing same in a path search map; if no obstacle-free path to a target point is found on the basis of the obstacle points, determining passing paths to the target point according to the path search map; and determining the shortest path among the passing paths, and controlling the automatic cleaning device to be unstuck along the shortest path.