Method and apparatus for updating working map of mobile robot, and storage medium
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Solution Overview
Problem
Mobile robots, especially home service robots, face challenges with low localization accuracy and reliability due to the use of consumer-level sensors and lack of external auxiliary localization devices, resulting in incomplete and inaccurate environment maps that affect path planning and task execution.
Innovation Solution
A method for updating the working map of a mobile robot by merging multiple detected environment maps to create a more comprehensive environment layout map, which involves filtering and weighting processing to enhance map accuracy and reflect detailed object distribution, allowing for better task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the mobile robot re-constructs an environment layout map each time it starts to execute a task, then the path planning can be performed based on the newly constructed map, but the map is not comprehensive enough and cannot reflect a detailed object layout in a workplace
Solution Approach 1:
The system performs preliminary detection and mapping actions before the actual task execution. The mobile robot detects the environment and constructs an initial environment layout map in advance, which serves as a foundation for subsequent task executions without needing complete reconstruction each time.
Solution Approach 2:
The system uses feedback from multiple detected environment maps to continuously improve and update the environment layout map. By merging M detected environment maps and performing weighting processing, the system refines the map accuracy and completeness based on accumulated detection data from previous operations.
2Device complexity
If the mobile robot uses consumer-level sensors without external auxiliary localization devices, then the device complexity is reduced, but the localization accuracy and reliability are not high
Solution Approach 1:
The system merges multiple detected environment maps into a unified environment layout map. By combining information from M detected maps through merging and weighting operations, the system achieves more accurate and reliable localization and mapping results using only consumer-level sensors, without requiring external auxiliary devices.
3Reliability
If the mobile robot does not store an environment layout map to reduce impact of single localization anomaly, then the system reliability is improved against anomalies, but the map completeness and detail accuracy deteriorate
Solution Approach 1:
The system implements a feedback mechanism where the environment layout map is continuously updated by merging multiple detected environment maps. This iterative refinement process ensures that the stored map becomes progressively more complete and accurate, capturing detailed object layouts while maintaining robustness through the merging of multiple detection results.
Data Source
AI summary
This application provides a method and an apparatus for updating a working map of a mobile robot, and a storage medium in the field of intelligent control technologies. The method includes: determining a plurality of detected environment maps based on object distribution information detected by the mobile robot in a moving process; merging the plurality of detected environment maps to obtain a merged environment map; and then performing weighting processing on the merged environment map and an environment layout map currently stored in the mobile robot, to obtain an updated environment layout map. The environment layout map stored in the mobile robot is updated by using the plurality of detected maps obtained by the mobile robot during working, so that the updated environment layout map can reflect a more detailed environment layout. This helps the mobile robot subsequently better execute a working task.