# SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots
## 2 Related Work
### Existing Ontologies for the Cooperation and Coordination of Underwater Robots  
There is an upsurge in using ontologies to enable a formal representation for the robotic field [11]. The IEEE RAS Ontologies for Robotics and Automation Working Group [12] has been developing a standard ontology model to represent the knowledge and reasoning in autonomous robots, such as air, ground, and underwater vehicles. However, this ontology focuses on presenting a very high-level service representation for vehicles themselves, such as sensors, resources, capabilities, platform, tasks, and mission. Context, which is useful to characterize the operational environment of vehicles, is not considered by this ontology. The ontology proposed by [PERSON] et al. [13] also lacks the inclusion of environmental context, though it provides a good representation of planning and control systems for AUVs. The KnowRob [14] knowledge processing framework developed a set of ontologies to abstract robot actions, events, objects, environments, and the robot's hardware as well as inference procedures that operate on this common representation. The KnowRob puts its emphasis on improving the autonomy of individual vehicles instead of enabling the cooperation and coordination of multiple vehicles. In addition, the household robots, rather than underwater robots, are the target modeling domain of the KnowRob ontologies. Similar to KnowRob, the ORO [15] system also leveraged a core robotics ontology to integrate data from diverse sources, such as sensors, domain knowledge, and human input. Nevertheless, the focus of the ORO ontologies is to help robots in interactions with humans. The RobotML [16] ontology, also known as PROTEUS ontology, was developed in the framework of the French research project PROTEUS [17]. The RobotML ontology aimed to enable scientific knowledge transfer between different robotic communities by formalizing the robots, their environments, robot parts, operations, mission, planning, their detailed behaviors, scenarios, etc. However, due to its complexity, the developed RobotML ontology cannot be directly used for exploitation as users must perform the semi-automatic transformation from the ontology to a UML representation. Besides, the RobotML is quite specific to their application; thus, it lacks generality to be reused in the underwater robots field. A reference ontology of collective behavior of autonomous was developed by [PERSON] et al. [18]. This ontology provides model of the system and environment, model of interaction between the system objects and the environment, and model of the behavior of the system objects and the environment. Ontologies were also extensively adopted to provide semantic formalizations for many robotic applications, such as monitoring of the execution of robot plans [19], robots task planning [20], navigation planning [21], urban search and rescue missions with robots [22], space exploration using robots [23], and supervision of underwater environments for robots [24]. All these application specific ontologies for robots are conceived at a too specific and limited level to cover the overall modeling requirements from the cooperation of underwater vehicles. It is also worth noting that a common lack exists in all the aforementioned robotic ontologies, except the KnowRob framework. They assume a deterministic world without considering context uncertainties, let alone properly model them. In the underwater robots field, uncertainty is the norm rather than the exception in context data. Therefore, this paper will present an ontology for the representation of coordination and cooperation of underwater vehicles based on existing relevant robotic ontologies. The proposed SWARMs ontology is general enough to cover necessary context from different domains, such as mission and planning, communication and networking, robotic vehicle, and environment recognition and sensing. In addition, uncertainties, as an inherent characteristic of context data, will be modeled in the presented ontology.