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Capability-oriented robot architecture for maritime autonomy

Insaurralde, Carlos C.; Petillot, Yvan R.


Yvan R. Petillot


© 2014 Elsevier Inc. All rights reserved. Advanced ocean systems are increasing their capabilities and the degree of autonomy more and more in order to perform more sophisticated maritime missions. Remotely operated vehicles are no longer cost-effective since they are limited by economic support costs, and the presence and skills of the human operator. Alternatively, autonomous surface and underwater vehicles have the potential to operate with greatly reduced overhead costs and level of operator intervention. This paper proposes an Intelligent Control Architecture (ICA) to enable multiple collaborating marine vehicles to autonomously carry out underwater intervention missions. The ICA is generic in nature but aimed at a case study where a marine surface craft and an underwater vehicle are required to work cooperatively. They are capable of cooperating autonomously towards the execution of complex activities since they have different but complementary capabilities. The architectural foundation to achieve the ICA lays on the flexibility of service-oriented computing and agent technology. An ontological database captures the operator skills, platform capabilities and, changes in the environment. The information captured, stored as knowledge, enables reasoning agents to plan missions based on the current situation. The ICA implementation is verified and early validated in simulations by means of a team of two above autonomous marine robots. This paper also presents architectural details and evaluation scenarios of the ICA, results of simulations from different maritime operations, and future research directions.


Insaurralde, C. C., & Petillot, Y. R. (2015). Capability-oriented robot architecture for maritime autonomy. Robotics and Autonomous Systems, 67, 87-104.

Journal Article Type Article
Acceptance Date Jan 1, 2014
Online Publication Date Nov 7, 2014
Publication Date May 1, 2015
Deposit Date Mar 10, 2020
Journal Robotics and Autonomous Systems
Print ISSN 0921-8890
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 67
Pages 87-104
Keywords Maritime robotics, Autonomous marine missions, Unmanned water vehicles, Cognitive control architectures, On-board decision-making
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