# An Abstraction Layer Exploiting Voice Assistant Technologies for Effective Human--Robot Interaction
## 6 Conclusions and Future Works  
In this paper, we introduced an abstraction layer for HRI that includes voice assistant technologies and that can be plugged into any robotic platform. Among its advantages, it allows reduction in the workload on the robot by using external tools and cloud platforms for running resource-intensive tasks. It also allows the development of applications of different kinds that can augment the interaction between the robot and the user. Moreover, the employment of voice assistant technologies is leveraged for the management of some applications built on top and for the conversation between the robotic platform and the user in the open domain. The scheme provided by the abstraction layer can be instantiated by choosing the robotic platform and technology for each component. One example of such instances is represented by the use case we proposed which uses the NAO robotic platform, the Choregraphe suite, and Google Assistant as voice assistant technology. Moreover, we employed the Google Assistant SDK and the associated developing tools. One example application leveraging Google Assistant and its SDK was developed and included in our proposed use case. Similarly, in our proposed use case, we employed Google's voice services. Furthermore, we evaluated the proposed use case testing possible scenarios with several stakeholders who identified potential weaknesses that we are taking into account for the next release of our architecture. For simplicity, we also evaluated the user experience of the proposed use case through questionnaires we gave to 10 different users. The entire source code for the use case we developed can be freely downloaded ([[https://github.com/conema/ZAGA](https://github.com/conema/ZAGA)]([https://github.com/conema/ZAGA](https://github.com/conema/ZAGA)) (accessed on 30 June 2021)). The presented abstraction layer is general; therefore, if the intention is to use services with more privacy-aware policies, different use cases based on our proposed abstraction layer can be instantiated by adopting solutions such as Snips.ai. A video related to the proposed use case that summarizes the different applications we built on top of NAO is freely available here ([[https://www.youtube.com/watch?v=tCEIrj6](https://www.youtube.com/watch?v=tCEIrj6) dg_w&feature=youtu.be]([https://www.youtube.com/watch?v=tCEIrj6](https://www.youtube.com/watch?v=tCEIrj6) dg_w&feature=youtu.be) (accessed on 30 June 2021)). The reader should note that the proposed use case can be applied to any robotic platform including robotic wheelchairs. For the Object Detection Application, the robotic wheelchair must be provided with a camera, whereas for the Mr. Chess Application it should have a screen. Finally, the Robot Action Command should be reset according to the physical movements and positions the robot can assume. There are several directions that we would like to head in parallel. One of them, the most challenging, and at architecture-level, is related to the development of a smart engine so that each application built on top can be triggered automatically depending on certain events to enrich the HRI between the user with the voice assistant technology by employing certain behavior (e.g., sentiment analysis, object detection) and have the robotic platform performing related actions depending on its sensors, body parts, etc. The idea is to turn any robotic platform closer towards the behavior of a human. One more direction at the use case level is related to the development of a further use case employing ROS ([[https://www.ros.org/](https://www.ros.org/)]([https://www.ros.org/](https://www.ros.org/)) (accessed on 30 June 2021)), already widespread among a certain number of robotic platforms. Conceptualization, D.R.R. ; methodology, E.C. and R.A.; software, E.C. ; validation, R.A. and E.C. ; writing, D.R.R. ; supervision, D.R.R. ; funding acquisition, D.R.R. and R.A. All authors have read and agreed to the published version of the manuscript.