# Telepresence Social Robotics towards Co-Presence: A Review
## 3 From Telepresence to Co-Presence Design
### User-Adaptive Systems Taxonomy  
Social robots aim to assist people, enable telesurveillance of elderly people, guide people on tours, promote physical and mental exercise, keep company, or entertain [1; 5; 6]. In short, they contribute to the user's well-being, adapting to people, to the environment, and ultimately to the context. Case studies include interaction of a service robot for 1 week in an elderly care center [116]. Several types of user-adaptive mechanisms are described in the robotics literature [2; 8; 9; 31; 189; 190]. Typically, a framework for a user-adaptive system comprises two components (see Figure 5): the _interface_ layer that is used for the exchange of information between the user and the system (It integrates sensors for the system to perceive the user and actuatorsto provide stimuli.) and the _decision-making module_ which, based on perceived information, makes algorithmic decisions and generates response actions to be synthesized by the interface. Robot systems with autonomous and semi-autonomous behaviors can be classified with the following taxonomy [8]:  
1. Adaptive systems with no user model: systems with reactive behavior regarding the user's immediate feedback and with no cache of the user's information (see Figure 6);
2. Adaptive systems based on static user models: systems that rely on pre-loaded knowledge retrieved from the relevant attributes of the user and used to adjust the system's behavior (see Figure 7);
3. Adaptive systems based on dynamic user models: similar to the previous example, these systems explicitly maintain user models. They are task-oriented models, updated with users' information during their interactions (see Figure 8). User-adaptive systems require information about the user which is typically stored in the form of a user model [9; 191]. As reported in an early survey [192], a new field of research emerged concerning with acquisition, organization, and representation of the system's user. Adaptive systems without user modeling can implicitly map the characteristics of a generic user in the architecture of the decision-making module (Figure 6). Nevertheless, it is a reactive adaptation that shapes the system's behavior directly based on the user's feedback. The user's behavior changes are monitored and trigger an immediate switch to a new system's operational state, while no storage or user model update is performed. Table 7 summarizes several works that adopt this type of architecture. Adaptive systems based on static user models assume that the person's profile does not evolve during the interaction. These static models can be built during an initial phase of the interaction (Figure 7), similar to the calibration process, or the user's profile can be pre-supplied using external questionnaires. These types of systems are not able to dynamically learn the characteristics of the user. Examples of related works are listed in Table 8.  
Figure 5: Overview of a generic user-adaptive system, which includes a user interface layer and a decision-making module. _Adaptive systems based on dynamic user models_ perceive, learn, and update the knowledge regarding the context model and the user model. The stored user model is updated during the interaction based on the user's reactions. This category of systems is considered the best performing user-adaptive solution, although its implementation is more complex [191; 193; 194]. Table 9 compiles several references for systems based on dynamic user models. Additionally, one of the described categories, such as adaptive systems based on dynamic user models, can coexist in a telepresence teleoperated robot [1; 3; 172; 173], thus adding adaptiveness functionalities either for the robot's operator (remote user) or for the local user that is with the robot. The general architecture of a teleoperation system with user adaptiveness is depicted in Figure 9.  
Figure 8: General schematic of a user-adaptive system based on dynamic user models.