# SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots
## 6 Conclusions  
To enable heterogeneous underwater robots with a common understanding of information that is necessarily exchanged between themselves is a challenge in the cooperation of underwater robots. The SWARMs project is a European project that targets to tackle this challenge. The approach defined in the SWARMs project has been presented in this paper along with preliminary results. Specifically, a networked ontology, namely the SWARMs ontology, which is defined within the scope of the SWARMs project, has been introduced in this paper. The SWARMs ontology consists of several domain-specific ontologies, which are interrelated by a core ontology. Specifically, information, related to the mission and planning, the robotic vehicles, the environment recognition and sensing, and the communication and network domains, has been abstracted in the SWARMs ontology. In addition, uncertainty, as an inherent characteristic of information obtained in the harsh maritime and underwater environment, has been modeled in the SWARMs ontology by using ontology constructs defined in the PR-OWL ontology. The uncertainty modeling in the SWARMs ontology has followed the MEBN theory. Thus, the SWARMs ontology can provide both a comprehensive representation of information and support for a hybrid context reasoning, including ontological, rule-based, and uncertainty reasoning. Underwater robots and CCS/MMT can exchange information without ambiguous meaning if they comply with the SWARMs ontology. In this way, further cooperation and coordination of a group of vehicles could be potentially achieved. A chemical pollution scenario has been described and it has been used to showcase how the SWARMS ontology can be instantiated, be extended with application enrichments, represent context uncertainty based on the MEBN theory, and provide support for the MEBN reasoning.  
Future work could be focused on the following aspects.  
The SWARMs ontology should be tested with more use cases (e.g., sperm construction, plume tracking) defined in the scope of the SWARMs project in terms of its applicability and extensibility.  
Currently, the SWARMs ontology has been fully implemented. However, it has not been integrated into the ontology model component defined in the SWARMs middleware architecture. To develop it in the middleware architecture and ensure its interactions with other middleware components are also intended as the future work. With the complete implementation, evaluation of the SWARMs ontology can be more convincible.  
Although the SWARMs ontology is designed to provide a common information model for the cooperation of underwater vehicles in the scope of the SWARMs project, the possibility of reusing it or its portions in other underwater robotics projects is worth to be explored.  
The SWARMs ontology has inherited ontology constructs defined in the PR-OWL ontology to annotate context uncertainties based on MEBN theories. In this way, three aspects of context uncertainty, namely, inaccuracy, randomness, and incompleteness, have been resolved. However, other aspects of context uncertainty, such as vagueness and impreciseness, also need to be tackled. Introducing fuzzy logic into the SWARMs ontology to represent the vagueness and impreciseness of information will also be done in the future.  
**Acknowledgments:** The research leading to the presented results has been undertaken within the SWARMs European project (Smart and Networking Underwater Robots in Cooperation Meshes), under Grant Agreement n.662107-SWARMs-ECSEL-2014-1, partially supported by the ECSEL JU, the Spanish Ministry of Economy, Industry and Competitiveness (Ref: PCIN-2014-022-C02-02), the Spanish Ministry of Energy, Tourism and The Digital Agenda, and the Fundacao para a Ciencia e a Tecnologia (FCT; ECSEL/0002/2014; ECSEL/0003/2014).  
**Author Contributions:** All authors equally contributed to the requirement analysis, design, implementation, and writing of the presented work.  
**Conflicts of Interest:** The authors declare no conflict of interest.