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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

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.

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

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.
Paper Structure (72 sections, 10 figures, 3 tables)

This paper contains 72 sections, 10 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Human Interpretation in Human-Pet and Human-Robot Affective Bonding
  4. Animal–Computer Interaction and More-than-Human Perspectives
  5. Designing Emotionally Expressive Behaviors in Zoomorphic Robots
  6. The Design Features of Animal-inspired Companion Robots
  7. Construction of the Design Resource
  8. Video Analysis of Human–Pet Interaction
  9. Development of the Coding Scheme
  10. Coding Process
  11. Literature Integration
  12. Evaluation and Iteration
  13. Design Reference Cards
  14. MojiKit
  15. Design Reference Cards from Interaction Analysis and Ethology
  16. ...and 57 more sections

Figures (10)

  • Figure 1: Design process of the reference cards: from video-based deductive coding (V1.0), to literature integration on animal behaviors and emotions (V2.0), to refinement via interviews with pet owners, resulting in the finalized Design Reference Cards V3.0.
  • Figure 2: Design Reference Cards comprising three modules (eight cards in total) of human–pet interaction. Example: the “Human Interaction Intentions” card, detailing motives such as human-initiated actions, passive responses, and non-interactive intent.
  • Figure 3: The structure of MomoBot. (a) Exploded view of MomoBot’s internal components with servomotors. (b) Structural cutaway showing the plush exterior and embedded mechanisms. (c) Motion ranges of ears, head, limbs, and tail across pitch, rotation, lifting, flexion, wagging, and curling.
  • Figure 4: Action editing and execution in MomoBot. (a) Motion sequences created in the Behavior Control Studio are (b) sent via Wi-Fi to the ESP32 and relayed as serial commands to the Arduino Mega, (c) which drives 16 servomotors. The Studio supports (d) timeline editing, (e) code editing, and (f) preset actions.
  • Figure 5: Co-design workshop.(a) Participants co-creating with MojiKit during the workshop sessions. (b) Examples of affective interaction patterns co-created by participants, including (i) face-to-face nuzzling, (ii) emotional embracing, (iii) face-cupping gesture, and (iv) resting on the shoulder. Photos are used with informed consent.
  • ...and 5 more figures