Lawn Mowing Robot Mapping Correction Trajectory Rewinding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing lawn mowing robots face inefficiencies in mapping due to errors in boundary tracking, requiring manual correction and re-mapping, which reduces operational efficiency.
Innovation Solution
A method and apparatus for lawn mowing robots that involve obtaining an initial correction position, rewinding to the original mapping trajectory, determining an intersection point, and deleting the erroneous trajectory to continue mapping from a target correction position, thereby avoiding the need to return to the starting point for re-mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual tracking of the boundary is performed during initial mapping, then the operation map can be created, but mapping errors occur between the boundary and tracked trajectory requiring restart
Solution Approach 1:
The system continuously monitors the mapping trajectory and automatically detects deviations from the original boundary. When an error is detected, the system provides feedback by identifying the divergence point and automatically corrects the trajectory without requiring manual intervention or restart, thus maintaining high mapping accuracy while improving efficiency.
Solution Approach 2:
The mapping system performs self-correction by automatically detecting trajectory errors, identifying the divergence point, and adjusting the mapping path independently. This self-service capability eliminates the need for manual intervention or complete restarts when mapping errors occur, resolving the contradiction between accuracy and efficiency.
2Reliability
If mapping error occurs during initial mapping, then the tracked boundary becomes incorrect, but restarting the mapping process reduces efficiency
Solution Approach 1:
The mapping process is segmented into independent sections. When an error is detected, only the affected segment after the divergence point needs correction, while the correct segments before the divergence point are preserved. This segmentation allows localized correction without restarting the entire mapping process, reducing time loss while maintaining correctness.
Solution Approach 2:
The system performs preliminary error detection and divergence point identification during the mapping process itself. By detecting errors early and identifying the exact divergence point, the system can make immediate corrections without waiting for complete mapping failure, thus maintaining reliability while minimizing time loss.
3Ease of operation
If the lawn mower automatically returns to initial position for correction, then mapping can be resumed, but the process becomes time-consuming
Solution Approach 1:
Instead of returning to the initial position in time (restarting the process), the system uses spatial information (the identified divergence point on the trajectory) to resume mapping from the correct location. This dimensional change from temporal restart to spatial resumption maintains ease of automatic operation while dramatically improving mapping efficiency.
Data Source
Figure 1A~1B
Figure 1C~2
Figure 3~4
AI summary
The embodiments of the present disclosure disclose a mapping correction method, an apparatus, and a storage medium, which are applied to a lawn mowing robot. The method includes: obtaining an initial correction position; obtaining a rewinding instruction to rewind toward the original mapping trajectory; obtaining an intersection position between the lawn mowing robot and the original mapping trajectory during the rewinding process and determining the intersection position as a target correction position; deleting the mapping trajectory between the target correction position and the initial correction position and continuing to construct a map based on the target correction position. In this way, according to the initial position where the signal is lost, a return path is recommended to the user for selection in real time, so that the mapping can be continued, and the efficiency and correctness of the lawn mowing robot's mapping are improved.