A Rule-Based Reasoner for Underwater Robots Using OWL and SWRL

Zhai, Zhaoyu; Ortega, José-Fernán Martínez; Martínez, Néstor Lucas; Castillejo, Pedro

doi:10.3390/s18103481

Cited by 18 publications

(15 citation statements)

References 56 publications

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“…The objective is to maintain functionality rather than use certain techniques. In this field, Zhai et al [ 33 ] presents a reasoner based on the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL) to manage knowledge with underwater heterogeneous robot during cooperative missions.…”

Section: State Of the Artmentioning

confidence: 99%

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Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy

Aguado

Milosevic

Hernández

et al. 2021

Sensors

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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.

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Section: State Of the Artmentioning

confidence: 99%

“…However, TOMASys takes a further step. Zhai et al [ 33 ] uses the reasoner to define an information model through semantic queries. In our implementation, the information model is used as a diagnostic tool to trigger the adaptation and reconfiguration of the robot.…”

Section: State Of the Artmentioning

confidence: 99%

Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy

Aguado

Milosevic

Hernández

et al. 2021

Sensors

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“…Therefore, the RTPO should meet a set of requirements to ensure an appropriate outcome. Generally, the paper takes into consideration that the great ontology in robotics should cover the following characteristics [35]:…”

Section: Requirements Of Robot Task Planning Ontology (Rtpo)mentioning

confidence: 99%

RTPO: A Domain Knowledge Base for Robot Task Planning

Sun

Chen

2019

Electronics

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Knowledge can enhance the intelligence of robots’ high-level decision-making. However, there is no specific domain knowledge base for robot task planning in this field. Aiming to represent the knowledge in robot task planning, the Robot Task Planning Ontology (RTPO) is first designed and implemented in this work, so that robots can understand and know how to carry out task planning to reach the goal state. In this paper, the RTPO is divided into three parts: task ontology, environment ontology, and robot ontology, followed by a detailed description of these three types of knowledge, respectively. The OWL (Web Ontology Language) is adopted to represent the knowledge in robot task planning. Then, the paper proposes a method to evaluate the scalability and responsiveness of RTPO. Finally, the corresponding task planning algorithm is designed based on RTPO, and then the paper conducts experiments on the basis of the real robot TurtleBot3 to verify the usability of RTPO. The experimental results demonstrate that RTPO has good performance in scalability and responsiveness, and the robot can achieve given high-level tasks based on RTPO.

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“…In particular, underwater autonomous robots are a very good testbed for this kind of systems, since their working environment is difficult and hazardous for humans, and hence the need for autonomy and resilience is much more compelling. Zhai et al [18], developed a OWL and SRWL-based ontology to provide users of underwater robots with query services to know the status of the robotic systems and the underwater environment. We use the same technologies, but to implement automatic diagnosis and reconfiguration of an autonomous underwater robot.…”

Section: Related Workmentioning

confidence: 99%

Meta-control and Self-Awareness for the UX-1 Autonomous Underwater Robot

Corbato

Milosevic

Olivares

et al. 2019

Advances in Intelligent Systems and Computing

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Autonomous underwater robots, such as the UX-1 developed in the UNEXMIN project, need to maintain reliable autonomous operation in hazardous and unknown environments. Because of the lack of any kind of real-time communications with a human operated command and control station, the control architecture needs to be enhanced with mission-level self-diagnosis and self-adaptation properties an additional provided by some kind of supervisory or "metacontrol" component to ensure its reliability. In this paper, we propose an ontological implementation of such component based on Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). The solution is based on an ontology of the functional architecture of autonomous robots, which allows inferring the effects of the performance of its constituents components in the functions required during the robot mission, and generate the reconfigurations needed to maintain operation reliably. The concept solution has been validated using a hypothetical set of scenarios implemented in an OWL ontology and an OWLAPI-based reasoner, which we aim at validating by integrating the metacontrol reasoning with a realistic simulation of the underwater robot.

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A Rule-Based Reasoner for Underwater Robots Using OWL and SWRL

Cited by 18 publications

References 56 publications

Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy

Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy

RTPO: A Domain Knowledge Base for Robot Task Planning

Meta-control and Self-Awareness for the UX-1 Autonomous Underwater Robot

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