ATRU: A Stage-based Framework for Designing Ethology-Inspired Social Robots
Xiaoqing Sun, Yanheng Li, Zhen Yin, Xinyan Zhao, Xipei Ren
Abstract
Animal behavior (ethology) has emerged as a promising source of inspiration for social robot design. However, existing efforts have commonly resulted in isolated design instances. Our high-level understanding of the design processes for integrating ethological insights into social robot design and evaluation remains limited. To address this gap, we conducted a two-step investigation. First, we developed a stage-based framework through a systematic review, identifying six core design stages along with their descriptive dimensions. Using this framework as an analytic lens, we then analyzed design cases drawn from academic, commercial, and public contexts, deriving stage-specific considerations and actionable strategies to support designers in navigating the process. Our findings provide a conceptual scaffold for operationalizing ethology as a design resource, enabling more systematic, reflective, and transferable practices, while also surfacing new opportunities for future social robot interaction design.
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