Abstract
As the field of social robotics is growing, a consensus has been made on the design and implementation of robotic systems that are capable of adapting based on the user actions. These actions may be based on their emotions, personality or memory of past interactions. Therefore, we believe it is significant to report a review of the past research on the use of adaptive robots that have been utilised in various social environments. In this paper, we present a systematic review on the reported adaptive interactions across a number of domain areas during Human-Robot Interaction and also give future directions that can guide the design of future adaptive social robots. We conjecture that this will help towards achieving long-term applicability of robots in various social domains.
Highlights
The significance of designing adaptive user interfaces can be witnessed in the field ofHuman-Computer Interaction (HCI) [1,2]
Our research aims are to design, implement and evaluate an Adaptive Social Robot (ASR) in a real life setting to challenge the issue of saturation during Human-robot interaction (HRI)
The purpose of the study was to measure the degree of comfort, enjoyment and easiness to make the request to the robot
Summary
The significance of designing adaptive user interfaces can be witnessed in the field ofHuman-Computer Interaction (HCI) [1,2]. The applications of AUIs can be found in HCI where interfaces adapt themselves based on context [3], personalised learning [1], and user activity within the interface [4]. Human-robot interaction (HRI) and Social Robotics (SR) are sub-branches of HCI that revolve around designing, implementing and evaluating robotic systems in both controlled environments and real world social settings. A robot can be categorised autonomous based on its level of automation as presented by [7], an ASR is an autonomous or semi-autonomous robot where speech is controlled by a human operator through a Wizard of Oz (WoZ) setup that can be termed as decision-making engine capable of perceiving the user information from the environment. The user information may include their profile, emotions, personality and past interactions Based on this information, it makes decisions [8]. An ASR has been described to have one or more of the following adaptation capabilities in HRI: understand and show emotions, communication with high-level dialogue, learn/adapt according to user responses, establishing a social relationship, react according to different social situations and have varying social characteristics and roles [9]
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