Publications       Rudy Negenborn
Full Professor, Head of Section
Team & Themes

Title:Path planning for autonomous inland vessels using A*BG
Authors:L. Chen, R.R. Negenborn, G. Lodewijks

Conference:7th International Conference on Computational Logistics (ICCL 2016)
Address:Lisbon, Portugal
Date:September 2016

Abstract:To meet the transportation demand and maintain sustainable development, many countries are aiming to promote and strengthen the competitive position of inland shipping in the transport system. Autonomy is seen as a possibility for maritime transport to meet today's and tomorrow's challenges. In realizing autonomous navigation, Path planning plays an important role. Being the most widely-used path planning algorithm, A* and its extensions are analyzed in the paper. Since for vessels, the optimal paths generally have heading changes only at the corners of obstacles, a modified A* algorithm (A*BG) for autonomous inland vessels is proposed. Two locations where ship accidents frequently occurred are chosen for simulation experiments. Experiments are carried out to compare the performance of A*, A*PS, Theta* and A*BG. The influence of the size of neighborhood (the range of nodes that algorithms search in a single step) is also investigated. The path length and computation time of each algorithm is calculated and compared.

Reference:Path planning for autonomous inland vessels using A*BG. L. Chen, R.R. Negenborn, G. Lodewijks. In Proceedings of the 7th International Conference on Computational Logistics (ICCL 2016), Lisbon, Portugal, pp. 65-79, September 2016.
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