CCIBA*: An Improved BA* Based Collaborative Coverage Path Planning Method for Multiple Unmanned Surface Mapping Vehicles

doi:10.1109/TITS.2022.3170322

CCIBA: An Improved BA Based Collaborative Coverage Path Planning Method for Multiple Unmanned Surface Mapping Vehicles

2022-10-01

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AI

DOI：10.1109/TITS.2022.3170322

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The main emphasis of this work is placed on the problem of collaborative coverage path planning for unmanned surface mapping vehicles (USMVs). As a result, the collaborative coverage improved BA* algorithm (CCIBA*) is proposed. In the algorithm, coverage path planning for a single vehicle is achieved by task decomposition and level map updating. Then a multiple USMV collaborative behavior strategy is designed, which is composed of area division, recall and transfer, area exchange and recognizing obstacles. Moverover, multiple USMV collaborative coverage path planning can be achieved. Consequently, a high-efficiency and high-quality coverage path for USMVs can be implemented. Water area simulation results indicate that our CCIBA* brings about a substantial increase in the performances of path length, number of turning, number of units and coverage rate.

Keywords:

Path planning

Task analysis

Collaboration

Heuristic algorithms

Behavioral sciences

Robots

Potential energy

Multiple USMVs

collaborative coverage

path planning

CCIBA*

task decomposition

CCIBA: An Improved BA Based Collaborative Coverage Path Planning Method for Multiple Unmanned Surface Mapping Vehicles

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