## 4 Adaptation
### Use Cases
#### 4.1.1 KIDE4 Guide: Guide/Logistics Robot  
The first use case consists on interaction with a guide robot: Teknibot (Figure 3). This robot, which has been presented in previous works [18], presents similar characteristics to logistics robots, and has the capability of moving from one point to another: given a user command, it is able to guide its target users to their destination of choice in a given environment and, additionally, is able to give information about specific objects or spaces. The target language of the use case is Spanish.  
In this case, KIDE4I has been adapted to this use case so as the guide robot is able to guide around the research center Tekniker, providing guidance to its different laboratories, workshops, people, etc. and to give information about them.  
The first two steps of the adaptation process can be observed in detail in [18], in which the key elements to detect and the Foma rules to obtain them were defined. In a nutshell, the relevant information to extract from commands for this use case are **actions** and **destinations** (which consist of a **target**, **preposition** and the target that depends on the preposition--the **complement**). Example (1) shows an instance of the previously mentioned key elements.  
1. [label=(0)]
2. Quiero \(\mathbf{ir}_{action}\) a una \(\mathbf{[sala}_{target}\ \mathbf{con}_{preposition}\ \mathbf{PC}_{complement}]\)_destination_
3. I want to \(\mathbf{go}_{action}\) to a \(\mathbf{[meeting\ room}_{target}\ \mathbf{with}_{preposition}\ \mathbf{PC}_{complement}]\)_destination_  
For the domain-related part of the modelling and instantiation phase, the corresponding classes for the spaces, objects and people from Tekniker were modelled in TODODW. For this, terms from the GEO [36] and FOAF [37] ontologies were reused. Then, the instances of those classes were extracted from existing databases and instantiated automatically through ODBA mapping rules, and the relations between them modelled. The actions that could be performed by the system were also modelled and, for the frame-related information (frames, frame heads and related lexical units), the population strategy in [34] (which will be referred as _the population strategy_ from now on), which makes use of multilingual existing language resources, was used. As for the machine-readable information for each element in the domain, it was modelled considering the requirements of the robot and its components. Finally, the different lexical units corresponding to the different domain  
Figure 3: Teknibot is a guide robot that is able to guide its users to a given destination.  
elements that could not be obtained through the automatic methods mentioned above were obtained combining thesauri and expert knowledge.  
On the other hand, the dialogue management information was modelled considering the expected outcomes of an interaction with a guide robot of these characteristics.  
Tables 1 and 2 include information on the modelling and instantiation of the ontology for this use case, respectively. As it can be observed, more than 90% of the classes have been reused, and more than 70% of the instances have been obtained automatically.  
In this case, this guide robot was used as the base use case to design KIDE4I and, thus, TODO, which is based on an initial conceptualization of KIDE4 Guide. However, to preserve Table 1's consistency, TODO has been considered as reused for this use case, as new modifications in ontology modelling were needed in further development stages of KIDE4 Guide. On another side, and considering this, other adaptations may make use of the rest of the work developed for this scenario (e.g., Foma rules or ontology instances).