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

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.