Autonomous Mobile Robot Map Re-Exploration to Reduce Navigation Errors
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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in dynamic settings where frequent changes occur, leading to inefficiencies and errors in navigation due to outdated maps and the time-consuming process of exploratory trips.
Innovation Solution
The method involves an autonomous mobile robot re-exploring and updating its map by using sensors to record changes in the environment, updating orientation and meta information, and storing the updated map for future missions, allowing for adaptive navigation and efficient task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the robot carries out an exploratory trip to cover the entire area with sensors of limited range, then the map coverage is improved, but the time required for exploration increases significantly
Solution Approach 1:
The robot performs preliminary exploration actions by using previously collected map data to identify and prioritize unexplored areas, allowing it to focus sensor coverage on regions that need mapping rather than systematically covering the entire area
Solution Approach 2:
The robot changes exploration parameters dynamically by adjusting sensor range and resolution based on the importance and accessibility of different areas, using multi-resolution mapping to balance coverage completeness with exploration speed
2Manufacturing precision
If the robot restarts the exploration trip after getting stuck, then the map accuracy is improved, but the total exploration time increases and previously explored areas are forgotten
Solution Approach 1:
The robot performs preliminary actions by maintaining and storing map data from previously explored areas in memory, so when exploration is interrupted, it can resume without forgetting previously collected information
Solution Approach 2:
The robot uses feedback from its navigation system to track which areas have been explored and which remain, allowing it to resume exploration efficiently after interruptions by focusing only on unexplored or problematic regions
3Reliability
If the robot enters temporary obstacles on the map, then the navigation safety is improved, but the robot's functionality is severely limited
Solution Approach 1:
The robot applies dynamics by implementing time-stamped obstacle data that allows obstacle information to expire automatically, transforming static map obstacles into dynamic, time-dependent navigation constraints that can be updated or removed based on current exploration results
Solution Approach 2:
The robot changes the parameter of obstacle permanence by introducing temporal validity to obstacle entries, allowing obstacles to be marked as temporary with expiration times, thus balancing navigation safety with functional adaptability
Data Source
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AI summary
One embodiment relates to a method for an autonomous mobile robot. According to one example, navigating an autonomous mobile robot through a specific area using a map includes: determining an initial measurement representing the actual traversable area within that area; determining a measure of the traversability of the area based on the initial measurement and a stored reference value; and notifying a user based on the determined measure.