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arXiv · 2603.11632

From Pets to Robots: MojiKit as a Data-Informed Toolkit for Affective HRI Design

Liwen He·Pingting Chen·Ziheng Tang·Yixiao Liu·Jihong Jeung·Teng Han·Xin Tong
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Abstract

Designing affective behaviors for animal-inspired social robots often relies on intuition and personal experience, leading to fragmented outcomes. To provide more systematic guidance, we first coded and analyzed human-pet interaction videos, validated insights through literature and interviews, and created structured reference cards that map the design space of pet-inspired affective interactions. Building on this, we developed MojiKit, a toolkit combining reference cards, a zoomorphic robot prototype (MomoBot), and a behavior control studio. We evaluated MojiKit in co-creation workshops with 18 participants, finding that MojiKit helped them design 35 affective interaction patterns beyond their own pet experiences, while the code-free studio lowered the technical barrier and enhanced creative agency. Our contributions include the data-informed structured resource for pet-inspired affective HRI design, an integrated toolkit that bridges reference materials with hands-on prototyping, and empirical evidence showing how MojiKit empowers users to systematically create richer, more diverse affective robot behaviors.

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Liwen He, Pingting Chen, Ziheng Tang, Yixiao Liu, Jihong Jeung, Teng Han, Xin Tong. 2026-03-12. From Pets to Robots: MojiKit as a Data-Informed Toolkit for Affective HRI Design. https://doi.org/10.1145/3772318.3790830

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