Abstract
A traditional A-Star (A*) algorithm generates an optimal path by minimizing the path cost. For a vessel, factors of path length, obstacle collision risk, traffic separation rule and manoeuvrability restriction should be all taken into account for path planning. Meanwhile, the water current also plays an important role in voyaging and berthing for vessels. In consideration of these defects of the traditional A-Star algorithm when it is used for vessel path planning, an improved A-Star algorithm has been proposed. To be specific, the risk models of obstacles (bridge pier, moored or anchored ship, port, shore, etc.) considering currents, traffic separation, berthing, manoeuvrability restriction have been built firstly. Then, the normal path generation and the berthing path generation with the proposed improved A-Star algorithm have been represented, respectively. Moreover, the problem of combining the normal path and the berthing path has been also solved. To verify the effectiveness of the proposed A-Star path planning methods, four cases have been studied in simulation and real scenarios. The results of experiments show that the proposed A-Star path planning methods can deal with the problems denoted in this article well, and realize the trade-off between the path length and the navigation safety.
Highlights
The autonomous surface vessel (ASV) technologies have grown rapidly and obtained more attention than ever both in military and commercial applications [1]
This study presents an improved A-Star based global path planning method to satisfy the requirements of the economy, the obstacle avoidance, the traffic separation rule, the berthing and the manoeuvrability restriction considering the water current effects at the same time
Please note that the traffic separation rule is not considered for the berthing path generation, i.e., rs = 0 at any time, because a vessel in the berthing process always finds the path that is against the current ignoring the traffic separation rule temporarily
Summary
The autonomous surface vessel (ASV) technologies have grown rapidly and obtained more attention than ever both in military and commercial applications [1]. Ma et al proposed a dynamic augmented multi-objective particle swarm optimization (PSO) algorithm to obtain a path considering the path length, smoothness, economical efficiency and safety for unmanned surface vehicles [8] Though this algorithm can get good performance of path planning, the PSO based method usually has the possibility of trapping in a local optima and the berthing requirements were not taken into account. This study presents an improved A-Star based global path planning method to satisfy the requirements of the economy (path length), the obstacle avoidance, the traffic separation rule, the berthing and the manoeuvrability restriction considering the water current effects at the same time.
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