Autonomous Mobile Path Planning Across Overlapping Work Areas
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Solution Overview
Problem
Existing path planning methods for autonomous mobile devices are inefficient and result in suboptimal performance when navigating between multiple overlapping work areas, failing to achieve a globally shortest path due to treating each area independently.
Innovation Solution
The method involves acquiring boundary maps of multiple work areas, merging them into an operational map, and determining a movement path based on this integrated map, incorporating boundary-following and non-boundary-following paths to optimize navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple boundary maps are merged into a single operational map, then path planning efficiency is improved and global optimality is achieved, but device complexity increases
Solution Approach 1:
The patent merges multiple boundary maps corresponding to different work areas into a single operational map that encompasses all work areas. This unified map allows the autonomous mobile device to perform path planning across the entire operational area without needing to switch between multiple independent maps, thereby improving path planning efficiency and achieving global path optimality while avoiding the complexity of managing multiple separate mapping systems
Solution Approach 2:
The operational map serves as a universal data structure that can represent multiple work areas, boundary regions, and operational zones within a single unified framework. This multi-functional map structure eliminates the need for separate boundary map management systems while maintaining the ability to perform various path planning operations across different areas
2Device complexity
If each work area is treated as an independent map, then device complexity is reduced, but path planning accuracy deteriorates due to inability to find globally optimal paths
Solution Approach 1:
The patent combines multiple independent work area maps into one integrated operational map that preserves the boundary information of each work area while enabling global path optimization. The merged map includes boundary contours of all work areas, allowing the path planning algorithm to calculate globally optimal paths that may cross between work areas while maintaining awareness of individual area boundaries
3Reliability
If multiple rounds of searching and path combination are performed, then path completeness is improved, but time consumption increases resulting in suboptimal performance
Solution Approach 1:
The patent performs preliminary actions by pre-establishing the unified operational map that includes all work areas and their boundaries before path planning is needed. This pre-processing of the map structure eliminates the need for multiple rounds of searching and path combination during actual path planning operations, as the global path can be directly calculated on the pre-integrated map, significantly reducing computation time while maintaining path completeness
Data Source
AI summary
Embodiments of the present disclosure provide a path planning method, autonomous mobile device, and storage medium. The method comprises: acquiring boundary maps corresponding to a plurality of work areas of the autonomous mobile device; merging the boundary maps to obtain a operational map; determining a movement path from a first position to a second position based on the first position and the second position in the operational map. the disclosure can improve path planning performance in scenarios where mobile devices are present in plurality of work areas with partial overlap.