Robots that Evolve with Us: Modular Co-Design for Personalization, Adaptability, and Sustainability

Paper Title

Robots that Evolve with Us: Modular Co-Design for Personalization, Adaptability, and Sustainability

Publication Info

• Topic area: Modular robot design for lifespan-oriented human–robot interaction.
• Keywords: Modular robotics, lifespan design, personalization, adaptability, sustainability, human–robot interaction, co-design, repairability, emotional attachment, ecological responsibility.

Background and Problem

• Problem / challenge: Current robot designs often prioritize efficiency and one-size-fits-all solutions, neglecting personalization, adaptability, and sustainability. Existing research treats these dimensions in isolation, failing to address how robots can remain relevant and meaningful across a human lifespan.
• Significance: Designing robots that evolve with users can enhance long-term utility, emotional connection, and ecological sustainability, addressing challenges like obsolescence and lack of user engagement.
• Motivation and related work: Prior research has explored personalization (short-term customization), adaptability (technical self-reconfiguration), and sustainability (ecological efficiency). However, these studies rarely integrate these dimensions or consider their interplay in lifespan-oriented robot design. The Sustainability, Adaptability, and Modularity (SAM) framework offers a speculative system-level theory but lacks empirical grounding or user-centered perspectives.

Solution

• Proposed approach: The Personalization, Adaptability, and Sustainability (PAS) framework, derived from empirical co-design workshops, integrates modularity as a socio-technical mechanism to support lifespan-oriented human–robot interaction.
• Novelty:
  1. Introduces the PAS framework as a human-centered complement to the SAM framework, emphasizing experiential dimensions of long-term human–robot relationships.
  2. Provides empirical evidence of how users envision modular robots evolving across life stages, addressing gaps in HRI research.
  3. Proposes actionable design principles for sustainable HCI, leveraging modularity as both a technical and philosophical foundation.
• Procedure and key techniques:
  1. Conducted two co-design workshops with 23 participants (15 younger adults aged 21–32 and 8 older adults aged 66–81).
  2. Participants used modular robot components (heads, arms, torsos, bases) to design robots for three life stages: childhood, adulthood, and older adulthood.
  3. Data collection included audio recordings, annotated sketches, and participant reflections, analyzed using thematic analysis to identify patterns in personalization, adaptability, and sustainability.

Results

• Concrete findings:
  • Participants produced 65 modular robot designs, demonstrating how modularity enables personalization, adaptability, and sustainability.
  • Personalization: Robots were tailored to individual values and life-stage needs, with participants customizing modules, omitting parts, or inventing new ones.
  • Adaptability: Robots flexibly transformed within and across life stages, addressing evolving user needs and roles.
  • Sustainability: Modularity supported repair, reuse, and evolution of robots, fostering material longevity and emotional attachment.
• Advantage over baselines: Unlike traditional robots, modular robots were envisioned as dynamic, long-term companions that adapt to users’ changing needs and reduce waste through repair and reuse. The PAS framework integrates personalization, adaptability, and sustainability, addressing gaps in existing research.
• Experiments / evaluation: Conducted two 90-minute co-design workshops with younger and older adults. Participants designed robots for three life stages, using a modular set of components as a design probe. The study combined speculative and experiential perspectives to explore lifespan-oriented modular robotics.
• Limitations and future work:
  • The study focused on adults, with childhood designs based on adult projections rather than children’s input. Future research should involve children directly.
  • Aesthetic and cultural dimensions of modular design were not deeply explored. Future work should investigate how specific module designs align with users’ aesthetic and cultural expectations.
  • The study used conceptual and graphical probes rather than physical prototypes. Future research should include material prototyping to test feasibility and refine design principles.

Summary

This paper introduces the PAS framework, which integrates personalization, adaptability, and sustainability into modular robot design for lifespan-oriented human–robot interaction. Through co-design workshops with younger and older adults, participants envisioned modular robots evolving across life stages, demonstrating how modularity supports repair, reuse, emotional attachment, and long-term adaptability. The study highlights modularity as both a technical mechanism and a design philosophy, enabling robots to become enduring companions rather than disposable tools. Future work should expand the framework to include children’s perspectives, explore aesthetic dimensions, and develop tangible prototypes to validate the findings.