# Ontology-Based Knowledge Representation in Robotic Systems: A Survey Oriented toward Applications
## 3 Analysis of Knowledge Representation Systems
### Ontology Scope
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**KRS** & **Ontologies** & **Concepts/Classes** \\ \hline
**KnowRob** & Inner world, virtual, logical, episodic memories, and DUL & Temporal, spatial, and mathematical things \\ \hline
**OROSU** & CORA, human anatomical, PARTS, and SUMO & Medical sensing and manipulation action \\ \hline
**CARESSES** & Modular structure & Not defined in [70] \\
**PMK** & Meta ontology & Feature, WSobject, WSpace, actor, sensor, context reasoning, action \\ \hline
**SARbot** & Entity, environment, and task & SLAM, object, task, and environment \\ \hline
**IEQ** & IEQ & Occupant, environment, and recommendation \\ \hline
**SmartRules** & Micro, DUL, & Object, person, and robot \\ \hline
**ARBI** & ISRO, user, robot, action, perception, and environment & Person, SocialConcept, object, robot, and event \\ \hline
**Worker-cobot** & Agent, agent administrative & Not defined in [76] \\ \hline
**APRS** & Three & PointType, PartType \\ \hline \hline \end{tabular}
\end{table} 
Table 7: KRSs: ontology scope. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & & \multicolumn{2}{c}{**Know-Rob**} & **OROUS** & **CARE-SSES** & **PMK** & **SARBot** & **IEQ** & **Smart-Rules** & **ARBI** & **Worke-robust** & **APRS** \\ \hline \multirow{4}{*}{Onto-logy Compe-nents} & Object & Definition & D & \({}^{\text{*}}\)D & - & \({}^{\text{*}}\)D & - & - & \({}^{\text{*}}\)D & \({}^{\text{*}}\)D & - & - \\ \cline{2-11}  & & Concept & C & C & C & C & C & \({}^{\text{*}}\)C & C & C & C & C & C & C & C \\ \cline{2-11}  & & Entity & P & P & P & P & P & N & P.V & P & P & P & P \\ \cline{2-11}  & & Type & R,S & H & S & T,G & K & O & M & T.G & S & S \\ \cline{2-11}  & & Definition & -E & -E & -E & -E & -E & -E & -E & -E & -E & -E \\ \cline{2-11}  & & Type & S & - & - & S & S,G & - & - & S & - & - \\ \cline{2-11}  & & Concept & PI & PI & -PI & PI & PI & -PI & PI & PI & -PI & -PI \\ \cline{2-11}  & & Definition & \({}^{\text{*}}\)A & - & -A & - & - & -A & - & - & - & - \\ \cline{2-11}  & & Concept & E & \({}^{\text{*}}\)E & - & \({}^{\text{*}}\)E & \({}^{\text{*}}\)E & -E & \({}^{\text{*}}\)E & \({}^{\text{*}}\)E & \({}^{\text{*}}\)E & \({}^{\text{*}}\)E \\ \hline \multirow{4}{*}{Cogn-itive Capsu-like} & \multirow{4}{*}{Inter-action Based on} & \multirow{4}{*}{*} & \multirow{4}{*}{-} & \multirow{4}{*}{-} & \multirow{4}{*}{-} & \multirow{4}{*}{-} & \multirow{4}{*}{-} & \multirow{4}{*}{-} & \multirow{4}{*}{-} & \multirow{4}{*}{-} & \multirow{4}{*}{-} \\  & & & & & & & & & & & & & \\ \cline{1-1} \cline{  
SARbot [72] divides the ontology into two layers: the conceptual layer for knowledge representation of the disaster rescue domain and the instance layer for the relationship among instances. The conceptual layer is further divided into abstract and specific layers. The abstract layer contains concepts related to the _SLAM_, _object_, and _task_ classes, while the specific layer describes certain environment objects. Three main parts of its ontology are entity ontology, environment ontology, and task ontology. The modules of these three ontologies are combined to make a joint ontology. For efficient task execution, it allows the robot to query and match the ontology at each layer according to the initial state. IEQ [73] represents the IEQ ontology, which focuses on the concepts related to physical environmental parameters of indoor areas, user's features, their perceptions, and preferences about the environment. The IEQ ontology consists of three parts, which concentrate on three main concepts known as occupant, environment, and recommendation. Occupant elements contain the attributes and relationships of the user (i.e., person), features (i.e., age, gender), user perception (i.e., heat), and preferences (i.e., temperature, illuminance level) about the environment to allow the robot to understand the comfortable conditions for the occupants. SmartRules [74] contains domain ontology to create context models for IoRT scenarios.