Contributo in atti di convegno, 2018, ENG, 10.1016/j.ifacol.2018.09.458

A Two Layered Optimal Approach towards Cooperative Motion Planning of Unmanned Surface Vehicles in a Constrained Maritime Environment

Bibuli, Marco; Singh, Yogang; Sharma, Sanjay; Sutton, Robert; Hatton, Daniel; Khan, Asiya

CNR; Univ Plymouth

Efficient motion planning of multiple unmanned surface vehicles (USVs) in a dynamic maritime environment is an important requirement for increasing mission efficiency and achieving motion goals. The current study integrates two approaches of intelligent path planning and virtual target path following guidance for multi-agent USV framework to perform a coordinated and cooperative navigation of USVs in a constrained maritime environment. In the current study, a safety distance constrained A* approach produces an optimal, computationally efficient and collision free path which is later smoothed using a spline to provide an optimal trajectory as input for virtual target based multi-agent guidance framework to navigate multiple USVs. The virtual target approach provides a robust methodology of global and local collision avoidance based on known positions of vehicles. The combined approach is evaluated with the different number of USVs and in different environmental scenarios to understand the effectiveness of approach from the perspective of practicality, safety and robustness. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles (CAMS), pp. 378–383, Opatija (Croatia), 10-12 September 2018

Keywords

Path Planning, Multi-Vehicle Systems, Path Following, Unmanned Surface Vehicles

CNR authors

Bibuli Marco

CNR institutes

ISSIA – Istituto di studi sui sistemi intelligenti per l'automazione

ID: 442560

Year: 2018

Type: Contributo in atti di convegno

Creation: 2021-01-21 10:38:44.000

Last update: 2023-04-19 15:03:54.000

CNR authors

External links

OAI-PMH: Dublin Core

OAI-PMH: Mods

OAI-PMH: RDF

DOI: 10.1016/j.ifacol.2018.09.458

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:442560

DOI: 10.1016/j.ifacol.2018.09.458

ISI Web of Science (WOS): 000447025400064