# An Abstraction Layer Exploiting Voice Assistant Technologies for Effective Human--Robot Interaction
## 1 Introduction  
People with neuromuscular problems tend to lose a significant degree of autonomy in their daily life. To increase their mobility and independence, power wheelchairs may provide a valuable solution. Due to the deterioration in their physical ability, some of them become unable to use power wheelchairs. A potential solution is represented by robotic wheelchairs, which may provide appropriate human-robot interaction to people with severe motor impairments. They may include intelligent assistive navigation systems to help people according to their capabilities. This reflects the trend of the last years, where the employment of robots has changed from common usage within big manufacturing industries to locations such as people's homes, hospitals, schools, hotels, restaurants, where the daily-life is carried out. As already happened several years ago with the diffusion of smartphones, we are assisting nowadays a similar wide spreading of the employment of robots for different tasks that will contribute to the development of new architectures, frameworks, and applications within the robotic domain. This happens because researchin different Information and Communications Technology (ICT) areas has brought about several cutting-edge technologies that have shaped new robotic platforms. These platforms can be improved and extended into several automatic robotic applications to help people in several domains (e.g., health, education, engineering, entertainment). Robots have also been used as socially assistive entities playing an important role for children with autism spectrum disorders [1] and the active aging of older adults [2]. Active aging is a current topic and has an enormous economic and social impact. According to [3], in 2017, the EU-28's total health-care spending was EUR 1.73 trillion. This accounted for around 10% of the EU GDP (Gross Domestic Product) where curative care and rehabilitative care services incurred on more than 50% of healthcare expenditure in the majority of European Union States. The total spending is expected to increase to 30% of GDP by 2060 [4], especially due to the increase in the aging population. In particular, reduced functional independence and loneliness, unavoidable in older people, who lose connection with their friendship networks and for whom it is more complex to start new ones, can further increase isolation and depression leading to a further increase in healthcare costs [5]. Nowadays, it is possible to program robots to the assistance and rehabilitation of people, and this improves the efficiency of the treatments and may alleviate care centers' workloads, leading to a reduction in the costs for both the care centers and the patients [6], reducing public and private long-term care and health-care expenditure. Furthermore, patients might even be treated in their homes, remotely, through telerehabilitation, thus reducing the inconvenience they experience. Moreover, robots are being constantly and widely used in education [7] and STEM (Science, Technology, Engineering and Mathematics) in general [8], for example to allow people to practice languages. One example of a robot used within education is Elias [9], a social robot that helps students learning foreign languages. Another one is the Makeblocks' mBot [10], which is able to teach kids to code. To further engage users, a robot must be equipped with technology that can understand what the user is saying, and identify the hidden psychological traits like emotions, sarcasm and irony [11]. To tackle this issue, the improvement of voice assistant technology has enabled several changes in life today. Google Assistant [12], Apple's Siri [13], Microsoft's Cortana [14], Amazon's Alexa [15], Wit.ai [16] and Snips.ai [17], an open source and privacy oriented solution, are all well-known examples of digital voice assistants available on the market today.