Next Article in Journal
Calculating the Effect of Ribs on the Focus Quality of a Therapeutic Spherical Random Phased Array
Next Article in Special Issue
Towards the Design and Implementation of an Image-Based Navigation System of an Autonomous Underwater Vehicle Combining a Color Recognition Technique and a Fuzzy Logic Controller
Previous Article in Journal
Natural Frequencies Identification by FEM Applied to a 2-DOF Planar Robot and Its Validation Using MUSIC Algorithm
Previous Article in Special Issue
Online 3-Dimensional Path Planning with Kinematic Constraints in Unknown Environments Using Hybrid A* with Tree Pruning

Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy

Centre for Automation and Robotics UPM-CSIC, Universidad Politécnica de Madrid, 28006 Madrid, Spain
Resources Computing International Ltd, Matlock DE4 5JA, UK
Cognitive Robotics, Delft University of Technology, 2628 CD Delft, The Netherlands
Author to whom correspondence should be addressed.
Academic Editor: Enrico Meli
Sensors 2021, 21(4), 1210;
Received: 31 December 2020 / Revised: 3 February 2021 / Accepted: 5 February 2021 / Published: 9 February 2021
(This article belongs to the Special Issue Intelligence and Autonomy for Underwater Robotic Vehicles)
Autonomous systems are expected to maintain a dependable operation without human intervention. They are intended to fulfill the mission for which they were deployed, properly handling the disturbances that may affect them. Underwater robots, such as the UX-1 mine explorer developed in the UNEXMIN project, are paradigmatic examples of this need. Underwater robots are affected by both external and internal disturbances that hamper their capability for autonomous operation. Long-term autonomy requires not only the capability of perceiving and properly acting in open environments but also a sufficient degree of robustness and resilience so as to maintain and recover the operational functionality of the system when disturbed by unexpected events. In this article, we analyze the operational conditions for autonomous underwater robots with a special emphasis on the UX-1 miner explorer. We then describe a knowledge-based self-awareness and metacontrol subsystem that enables the autonomous reconfiguration of the robot subsystems to keep mission-oriented capability. This resilience augmenting solution is based on the deep modeling of the functional architecture of the autonomous robot in combination with ontological reasoning to allow self-diagnosis and reconfiguration during operation. This mechanism can transparently use robot functional redundancy to ensure mission satisfaction, even in the presence of faults. View Full-Text
Keywords: autonomy; resilience; self-awareness; metacontrol; rendundancy; ontology autonomy; resilience; self-awareness; metacontrol; rendundancy; ontology
Show Figures

Figure 1

MDPI and ACS Style

Aguado, E.; Milosevic, Z.; Hernández, C.; Sanz, R.; Garzon, M.; Bozhinoski, D.; Rossi, C. Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy. Sensors 2021, 21, 1210.

AMA Style

Aguado E, Milosevic Z, Hernández C, Sanz R, Garzon M, Bozhinoski D, Rossi C. Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy. Sensors. 2021; 21(4):1210.

Chicago/Turabian Style

Aguado, Esther, Zorana Milosevic, Carlos Hernández, Ricardo Sanz, Mario Garzon, Darko Bozhinoski, and Claudio Rossi. 2021. "Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy" Sensors 21, no. 4: 1210.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop