Autonomous Robot Map Re-Exploration for Dynamic Area Updates
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Solution Overview
Problem
Autonomous mobile robots face challenges in creating and maintaining stable, efficient maps of their operational environments, particularly in dynamic settings like households, where frequent changes and obstacles hinder navigation and require extensive re-exploration, leading to inefficiencies and potential map errors.
Innovation Solution
The method involves an autonomous mobile robot re-exploring and updating its map by using sensors to detect changes in the environment, updating orientation and meta information, and storing the updated map for future navigation, allowing it to adapt to changes while maintaining meta information and avoiding the need for complete map re-creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot performs a complete reconnaissance mission to create an updated map, then the map covers as much detail as possible, but the exploration run becomes very long and time-consuming
Solution Approach 1:
The patent divides the exploration process into two distinct modes: a first mode for initial comprehensive mapping and a second mode for targeted re-exploration of specific areas. This segmentation allows the robot to perform quick updates on demand rather than requiring complete re-mapping, significantly reducing the time required for map updates while maintaining necessary detail levels.
Solution Approach 2:
The patent implements partial re-exploration where the robot re-explores only specific portions of the environment that have changed or need updating, rather than performing complete reconnaissance missions. This partial action approach maintains map detail where necessary while avoiding the time cost of exhaustive re-mapping of entire areas.
2Reliability
If the robot restarts the exploration run after getting stuck, then map errors are avoided, but the robot forgets the area it has already explored and loses time
Solution Approach 1:
The patent performs preliminary actions by saving progress information during exploration runs, including detected structures and mapped areas. When the robot gets stuck or an interruption occurs, this preliminary saved information allows the robot to resume exploration from the point of interruption rather than restarting completely, preventing both map errors and time loss.
Solution Approach 2:
The patent implements feedback mechanisms where the robot continuously monitors exploration progress and detects interruptions. When an interruption is detected, the system uses feedback from previously saved exploration data to determine the appropriate resumption point, ensuring map accuracy is maintained while avoiding redundant re-exploration of already-mapped areas.
3Adaptability or versatility
If changes are entered into the permanently stored map, then the map adapts to the changing environment, but the robot can no longer access areas behind temporarily closed doors, severely limiting functionality
Solution Approach 1:
The patent makes the map dynamic by allowing it to be updated with detected changes in the environment. The system continuously monitors for changes such as closed doors or moved objects and updates the map accordingly, enabling the robot to adapt to new conditions while maintaining access to previously mapped areas through proper path planning around obstacles.
Solution Approach 2:
The patent changes map parameters selectively based on detected environmental changes. Rather than permanently blocking areas, the system updates specific parameters (such as accessibility flags or obstacle markers) for affected regions, allowing the robot to adapt to changes like closed doors while still maintaining the ability to access those areas when conditions permit.
4Device complexity
If the robot uses sensors with limited range, then the device complexity is reduced, but the exploration run must cover the entire area making it very long
Solution Approach 1:
The patent ensures continuity of useful action by implementing a systematic exploration strategy where the robot methodically covers the entire area using its sensor suite. The continuous scanning and mapping process, combined with efficient path planning and the ability to resume from interruption points, maximizes the utility of limited-range sensors while minimizing total exploration time through optimized coverage patterns.
Data Source
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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.