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Path Planning for Autonomous Inland Vessels Using A*BG

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Computational Logistics (ICCL 2016)

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To meet the transportation demand and maintain sustainable development, many countries are aiming to promote the competitive position of inland waterway shipping in the transport system. Autonomous transport 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 for robotics and land-based vehicles, in this paper we analyze A* and its extensions for waterborne applications. We hereby exploit the fact that for vessels optimal paths typically have heading changes only at the corners of obstacles to propose a more efficient modified A* algorithm, A*BG, for autonomous inland vessels. Two locations where ship accidents frequently occur are considered in simulation experiments, in which the performance of A*, A*PS, Theta* and A*BG are compared.

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This research is supported by the China Scholarship Council under Grant 201426950041.

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Correspondence to Linying Chen .

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Chen, L., Negenborn, R.R., Lodewijks, G. (2016). Path Planning for Autonomous Inland Vessels Using A*BG. In: Paias, A., Ruthmair, M., Voß, S. (eds) Computational Logistics. ICCL 2016. Lecture Notes in Computer Science(), vol 9855. Springer, Cham.

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  • Print ISBN: 978-3-319-44895-4

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