Abstract
The coexistence of robots and humans in shared physical and social spaces is expected to increase. A key enabler of high-quality interaction is a mutual understanding of each other’s actions and intentions. In this paper, we motivate and present a systematic user experience (UX) evaluation framework of action and intention recognition between humans and robots from a UX perspective, because there is an identified lack of this kind of evaluation methodology. The evaluation framework is packaged into a methodological approach called ANEMONE (action and intention recognition in human robot interaction). ANEMONE has its foundation in cultural-historical activity theory (AT) as the theoretical lens, the seven stages of action model, and user experience (UX) evaluation methodology, which together are useful in motivating and framing the work presented in this paper. The proposed methodological approach of ANEMONE provides guidance on how to measure, assess, and evaluate the mutual recognition of actions and intentions between humans and robots for investigators of UX evaluation. The paper ends with a discussion, addresses future work, and some concluding remarks.
Highlights
Several kinds of robots are entering the world we live in and they are expected to be fully integrated in future society
Sensors 2020, 20, 4284 systematic evaluation framework of action and intention recognition between humans and robots from a user experience (UX) perspective, because we have identified a lack of this kind of evaluation methodology
ANEMONE has its foundation in activity theory (AT) [81,82,83,84,85,86] as its theoretical lens, the seven stages of action model [91], and UX evaluation methodology, which together are useful in motivating and framing the work presented in this paper
Summary
Several kinds of robots are entering the world we live in and they are expected to be fully integrated in future society. In order to become a natural part in the daily life of humans in domestic, vocational, as well as public contexts, interaction and coexistence with several kinds of robots has to be experienced positively by humans while being suited to our purposes, with the interaction being smooth and satisfying [2,3,4,5]. This means that humans should experience that a robot delivers according to existing explicit and implicit goals, which means that it performs efficiently, and in a way that makes humans feel trust, safety, and convenience while being together [5]. We present a Sensors 2020, 20, 4284; doi:10.3390/s20154284 www.mdpi.com/journal/sensors
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