Autonomous Robot Map Updating for Stable Re-Exploration
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Solution Overview
Problem
Autonomous mobile robots face challenges in maintaining a stable and efficient map of their deployment area due to changes in the environment, such as temporary obstacles and limited sensor range, which can lead to inaccurate navigation and increased user effort in updating maps.
Innovation Solution
The method involves an autonomous mobile robot periodically re-exploring and updating its map by detecting changes in the environment using sensors, updating orientation data and metadata, and adapting the map to reflect changes while maintaining a stable navigation framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the robot enters every change into the map to take account of environmental changes, then the map adaptability is improved, but the map stability deteriorates and functionality is limited
Solution Approach 1:
The patent implements a dynamic map management system that automatically adjusts map updates based on change detection. The robot performs selective re-exploration only in areas where environmental changes are detected, rather than updating the entire map. This dynamic approach maintains map stability for unchanged areas while adapting to changes where needed, resolving the contradiction between map adaptability and stability.
Solution Approach 2:
The patent applies local quality by implementing region-specific map updates. When environmental changes are detected, only the affected local areas are marked for re-exploration and updated, while the rest of the map remains stable. This localized approach allows the map to adapt to changes without compromising overall stability, enabling the robot to maintain functionality in unchanged areas while adapting to new conditions.
2Manufacturing precision
If the robot performs a complete exploration run to compile an accurate map, then the map detail completeness is improved, but the time consumption increases
Solution Approach 1:
The patent implements partial exploration by performing selective re-exploration only in areas where environmental changes are detected. Instead of conducting complete exploration runs to ensure map accuracy, the robot uses change detection to identify and re-explore only the necessary regions. This partial action approach maintains map detail completeness in changed areas while significantly reducing time consumption compared to complete re-exploration.
Solution Approach 2:
The patent applies preliminary action by performing change detection before initiating re-exploration. The robot uses sensors to detect environmental changes and identifies specific areas that require updated mapping. This preliminary detection step allows the robot to plan targeted re-exploration routes, ensuring map accuracy in changed areas while avoiding unnecessary exploration of unchanged regions, thus reducing overall time consumption.
3Manufacturing precision
If the robot restarts the exploration run due to map accuracy issues, then the map accuracy is improved, but the time loss increases
Solution Approach 1:
The patent implements feedback by continuously monitoring environmental changes and using this information to trigger selective re-exploration. When sensors detect changes in the environment, the system feeds this information back to the navigation module, which then initiates targeted re-exploration only in affected areas. This feedback mechanism ensures map accuracy is maintained in changed regions without requiring complete restarts of exploration runs, thereby minimizing time loss while improving map accuracy where needed.
Data Source
AI summary
An exemplary embodiment relates to a method for an autonomous mobile robot for the new exploration of an area already listed in a map of the robot. According to one example, the method comprises storing a map of a deployment area of an autonomous mobile robot, wherein the map contains orientation information, which represents the structure of the surroundings in the deployment area, and also meta information. The method further comprises receiving a command via a communication unit of the robot, which causes the robot to start a new exploration of at least a part of the deployment area. The robot then explores again the at least one part of the deployment area, wherein the robot detects information regarding the structure of its surroundings in the deployment area by means of a sensor. The method further comprises updating the map of the deployment area and storing the updated map for use in the robot navigation during a plurality of future robot interventions. The aforementioned update comprises determining changes in the deployment area based on the information recorded during the exploration about the structure of the surroundings and the orientation information already stored in the map, and updating the orientation information and the meta information based on the determined changes.