Joint attention is the shared focus multiple people can have on the same object and it is subconsciously used by humans every day. The simple act of verbally or non-verbally pointing out an object to one another, is a form of joint attention. Its use facilitates human cooperation, such as when someone needs to hand over an object to another person. When robots display those same joint attention behaviours, it could be useful in improving human-robot interactions and perhaps variably so in various levels of jointness.
This research investigates the effects of these levels of jointness on the interactions between a human and a robot. This is done by investigating the effect on the person's task performance, the effect on their mental model of the robot, and the effect on their perception of the robot as its own entity with its own mind. To this end, this research defines four levels of joint attention and designs an experiment that makes use of these four levels of joint attention. To perform this experiment, a system capable of establishing joint attention has been developed. The system is divided into two parts; hardware and software tools & applications which have not been developed in this project but are used as is, and software which has been actively developed in this research.
In this experiment, participants played three guessing games with a robot. Task performance was measured by the amount of time and hints needed, as well as the accuracy of a participant. The participant's mental model and perception of the robot as its own entity with its own mind were measured using a questionnaire.
This research found no significant effect on the mental model towards the robot and the perception of whether the robot is its own entity with its own mind, although it is not concluded that such an effect cannot be found.
This research did find a significant effect on task performance; higher levels of joint attention lead to faster task completion with less hints needed. But interestingly, this did not necessarily lead to a higher accuracy.
The system introduced by this research was originally intended to help children with autism spectrum disorder learn joint attention skills, but due to ethical and time constraints, the system was tested with and the experiment was performed with adults instead. Due to ethical constraints, the participants in this research were not asked to disclose whether they had an autism spectrum disorder diagnosis or not. However, future research could replicate this study with the intended target group.

Interactive Robotics aims to familiarize children with robotics, which they try to do with their RoboTutor. Towards this goal they developed a platform for controlling the robots but this platform only worked for the Nao robot and not for the Pepper robot.
So for our bachelor end project we have been asked to build a connection tunnel between the server and the Nao and Pepper robots so that it is possible to also use the Pepper robot.

As our research progressed however, it became more clear to us that in order to make a generic solution for both the robots the existing platform would not suffice. So instead of only creating the tunnel we also worked on a new server side solution.
the solution we came up with, virtualization, was sure to solve the problems that caused the Pepper robot to be incompatible with the current platform. By running the server side processes for each robot inside their own environment using Docker containers we where able to create a generic solution for both robots. And with some custom code on the robots themselves, we could ensure that the robots would always connect to the server if they where connected to the Internet.