Multi-USMV Coverage Path Planning With Hierarchical Map Segmentation
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Solution Overview
Problem
Current coverage path planning methods for unmanned surface mapping vehicles (USMVs) are inefficient and lack robustness in complex water environments, requiring improved algorithms to enhance coverage rate and operation efficiency.
Innovation Solution
The CCIBA* algorithm divides the operating area into submaps and an overall map using the CCIBA* method, which includes collaborative behavior strategies like area segmentation, backtracking transfer, area exchange, and joint obstacle recognition, to optimize path planning for multiple USMVs, ensuring efficient and high-quality scanning paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional coverage path planning methods are used for USMVs, then the system is simpler to implement, but the coverage rate and operation efficiency deteriorate in complex water environments
Solution Approach 1:
The patent divides the overall map into multiple submaps and further segments them into sub-areas using the CCIBA* algorithm. This segmentation allows multiple USMVs to independently plan and execute coverage paths in different sub-areas, improving operation efficiency while maintaining manageable algorithmic complexity through modular processing
Solution Approach 2:
The patent introduces a hierarchical map structure with multiple levels (overall map, submaps, and sub-areas), adding a dimensional layer to the traditional single-map approach. This multi-level hierarchy enables more efficient path planning by allowing vehicles to operate at different spatial scales simultaneously, enhancing productivity without proportionally increasing complexity
2Productivity
If multiple USMVs operate independently without collaborative strategies, then the system is simpler to control, but the coverage rate deteriorates due to redundant paths and gaps
Solution Approach 1:
The patent implements a collaborative behavior strategy determination mechanism where USMVs continuously exchange information about their positions, detected obstacles, and coverage status. This feedback loop enables vehicles to dynamically adjust their paths based on the actions and discoveries of other vehicles, ensuring complete coverage without redundant paths while maintaining coordinated control
Solution Approach 2:
The overall coverage task is segmented into sub-tasks for different sub-areas, with each USMV assigned to specific regions. This task segmentation reduces control complexity by allowing decentralized decision-making within assigned zones while the collaborative strategy coordinates interactions at boundaries, achieving high coverage rate through organized division of labor
3Loss of time
If the path planning algorithm optimizes for shorter paths, then the operation time is reduced, but the coverage completeness may deteriorate in complex environments
Solution Approach 1:
The patent performs preliminary area division and path planning using the CCIBA* algorithm before USMVs begin their coverage operations. By pre-segmenting the environment and calculating optimal paths for each sub-area, the system ensures coverage completeness is built into the plan from the start, while the optimized paths minimize operation time without requiring costly real-time adjustments
Data Source
AI summary
Disclosed is a coverage path planning method for multiple unmanned surface mapping vehicles, comprising: simultaneously creating submaps and an overall map; outputting its own position information and obstacle information, transmitting to BLli and updating BLlm; defining a behavior strategy list (BS); determining the BS with priority for path planning, outputting a to or th state if any criterion is satisfied; when trapped in a local optimum, updating map layers layer-by-layer going upwards, searching for tp in the corresponding layers, performing a BS determination, and outputting a tr instruction; if no target point is found even at the highest layer, checking each CSP<sub2>i</sub2>∈{FNi,UFNi}, and determining a termination. As such, the coverage rate and coverage effect of multiple unmanned surface mapping vehicles in a complex environment can be increased, thus increasing the operational efficiency of the unmanned surface mapping vehicles.