Feedback motion planning of unmanned surface vehicles via random sequential composition

Date

2019-08-01

Author

Ege, Emre
Ankaralı, Mustafa Mert

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper, we propose a new motion planning method that aims to robustly and computationally efficiently solve path planning and navigation problems for unmanned surface vehicles (USVs). Our approach is based on synthesizing two different existing methodologies: sequential composition of dynamic behaviours and rapidly exploring random trees (RRT). The main motivation of this integrated solution is to develop a robust feedback-based and yet computationally feasible motion planning algorithm for USVs. In order to illustrate the main approach and show the feasibility of the method, we performed simulations and tested the overall performance and applicability for future experimental applications. We also tested the robustness of the method under relatively extreme environmental uncertainty. Simulation results indicate that our method can produce robust and computationally feasible solutions for a broad class of USVs.

Subject Keywords

Instrumentation

URI

https://hdl.handle.net/11511/40077

Journal

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL

DOI

https://doi.org/10.1177/0142331218822698

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

E. Ege and M. M. Ankaralı, “Feedback motion planning of unmanned surface vehicles via random sequential composition,” TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, pp. 3321–3330, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40077.