arXiv subjects

Selma Šabanović

Publications and source records attributed to Selma Šabanović.

4 recordsLinked to original sources

arXiv2026

Positioning Modular Co-Design in Future HRI Design Research

Design-oriented HRI is increasingly interested in robots as long-term companions, yet many designs still assume a fixed form and a stable set of functions. We present an ongoing design research program that treats modularity as a designerly medium - a way to make long-term human-robot relationships discussable and material through co-design. Across a series of lifespan-oriented co-design activities, participants repeatedly reconfigured the same robot for different life stages, using modular parts to express changing needs, values, and roles. From these outcomes, we articulate PAS (Personalization-Adaptability-Sustainability) as a human-centered lens on how people enact modularity in practice: configuring for self-expression, adapting across transitions, and sustaining robots through repair, reuse, and continuity. We then sketch next steps toward a fabrication-aware, community-extensible modular platform and propose evaluation criteria for designerly HRI work that prioritize expressive adequacy, lifespan plausibility, repairability-in-use, and responsible stewardship - not only usability or performance.

cs.HC↗

arXiv2026

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

Many current robot designs prioritize efficiency and one-size-fits-all solutions, oftentimes overlooking personalization, adaptability, and sustainability. To explore alternatives, we conducted two co-design workshops with 23 participants, who engaged with a modular robot co-design framework. Using components we provided as building blocks, participants combined, removed, and invented modules to envision how modular robots could accompany them from childhood through adulthood and into older adulthood. The participants' designs illustrate how modularity (a) enables personalization through open-ended configuration, (b) adaptability across shifting life-stage needs, and (c) sustainability through repair, reuse, and continuity. We therefore derive design principles that establish modularity as a foundation for lifespan-oriented human-robot interaction. This work reframes modular robotics as a flexible and expressive co-design approach, supporting robots that evolve with people, rather than static products optimized for single moments or contexts of use.

cs.HC↗

arXiv2026

Adding More Value Than Work: Practical Guidelines for Integrating Robots into Intercultural Competence Learning

While social robots have demonstrated effectiveness in supporting students' intercultural competence development, it is unclear how they can effectively be adopted for integrated use in K-12 schools. We conducted two phases of design workshops with teachers, where they co-designed robot-mediated intercultural activities while considering student needs and school integration concerns. Using thematic analysis, we identify appropriate scenarios and roles for classroom robots, explore how robots could complement rather than replace teachers, and consider how to address ethical and compliance considerations. Our findings provide practical design guidelines for the HRI community to develop social robots that can effectively support intercultural education in K-12 schools.

cs.HC↗

arXiv2014

Designing a minimalist socially aware robotic agent for the home

We present a minimalist social robot that relies on long timeseries of low resolution data such as mechanical vibration, temperature, lighting, sounds and collisions. Our goal is to develop an experimental system for growing socially situated robotic agents whose behavioral repertoire is subsumed by the social order of the space. To get there we are designing robots that use their simple sensors and motion feedback routines to recognize different classes of human activity and then associate to each class a range of appropriate behaviors. We use the Katie Family of robots, built on the iRobot Create platform, an Arduino Uno, and a Raspberry Pi. We describe its sensor abilities and exploratory tests that allow us to develop hypotheses about what objects (sensor data) correspond to something known and observable by a human subject. We use machine learning methods to classify three social scenarios from over a hundred experiments, demonstrating that it is possible to detect social situations with high accuracy, using the low-resolution sensors from our minimalist robot.

cs.RO↗