Development of a Socially Believable Multi-Robot Solution from Town to Home

Abstract

Technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is that they have to be socially acceptable and believable to the end-users. This paper aimed to present some technological aspects that have been faced to develop the Robot-Era system, a multi-robotic system that is able to act in a socially believable way in the environments daily inhabited by humans, such as urban areas, buildings and homes. In particular, this paper focuses on two services—shopping delivery and garbage collection—showing preliminary results on experiments conducted with 35 elderly people. The analysis adopts an end-user-oriented perspective, considering some of the main attributes of acceptability: usability, attitude, anxiety, trust and quality of life

Enabling personalised medical support for chronic disease management through a hybrid robot-cloud approach

“…This guarantees an efficient service delivery compared with other QoS analyses with real users (Cavallo et al 2014a). This quantitative results further emphasised the high system reliability and efficiency during the experimental phase, confirmed by the higher acceptability and usability results.…”

“…According to the results, older participants with a high educational level felt less anxiety than those with low education ( p = 0.035) and those involved in other robotics experimentation such as DustCart (Ferri et al 2011), Astromobile (Cavallo et al 2014a) were more confident with the hybrid robot-cloud system ( p = 0.0524) because they were more familiar with the robotic systems.…”

“…4. The Total Service Time (TST) -service responsiveness is one of the key features that influences the acceptability and usability of the service's levels to improve the service efficiency (Cavallo et al 2014a). It is computed as the sum of RTT, RPT and ATT.…”

“…Physical Layer The smart environment included two different sensor networks: one for user localisation using the Received Signal Strength (RSS) (Bonaccorsi et al 2015), and one for environmental monitoring and passive localisation of the people (Cavallo et al 2014a). The localisation network included a set of ZigBee Anchors placed in fixed positions in the environment, a ZigBee Coordinator to maintain and manage the entire network, a Data Logger (DL) and a Mobile Node (MN) worn by the user.…”

“…The software used localisation data from the DB, implementing a sensor fusion approach based on a Kalman Filter for estimating the user's position. The KF was implemented exploiting both range-free (Arias et al 2004) and range-based (Cavallo et al 2014a) localisation methods, according to Wang et al (Wang et al 2013). Presence sensors were also used to improve positioning accuracy and perform host detection.…”