Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Robots in the Wild: Contextually-Adaptive Human-Robot Interactions in Urban Public Environments

Xinyan Yu, Yiyuan Wang, Tram Thi Minh Tran, Yi Zhao, Julie Stephany Berrio Perez, Marius Hoggenmuller, Justine Humphry, Lian Loke, Lynn Masuda, Callum Parker, Martin Tomitsch, Stewart Worrall

TL;DR

The paper argues for expanding HRI research beyond semi-structured settings to urban public environments, addressing the need for contextually-adaptive robots that navigate social group dynamics, weather, and infrastructure uncertainties. It presents a half-day workshop blueprint featuring pre-work, a keynote, a cultural-probe city-walk reflective activity, and open discussions to surface design opportunities and research questions. Key contributions include a structured process to identify tangible design guidelines and to form a cross-disciplinary OzCHI network, with outcomes aimed at guiding future work and publications. The practical impact lies in catalyzing collaborative efforts to develop urban-robot interactions that respect social contexts, inclusivity, and collective dynamics in real-world environments.

Abstract

The increasing transition of human-robot interaction (HRI) context from controlled settings to dynamic, real-world public environments calls for enhanced adaptability in robotic systems. This can go beyond algorithmic navigation or traditional HRI strategies in structured settings, requiring the ability to navigate complex public urban systems containing multifaceted dynamics and various socio-technical needs. Therefore, our proposed workshop seeks to extend the boundaries of adaptive HRI research beyond predictable, semi-structured contexts and highlight opportunities for adaptable robot interactions in urban public environments. This half-day workshop aims to explore design opportunities and challenges in creating contextually-adaptive HRI within these spaces and establish a network of interested parties within the OzCHI research community. By fostering ongoing discussions, sharing of insights, and collaborations, we aim to catalyse future research that empowers robots to navigate the inherent uncertainties and complexities of real-world public interactions.

Robots in the Wild: Contextually-Adaptive Human-Robot Interactions in Urban Public Environments

TL;DR

The paper argues for expanding HRI research beyond semi-structured settings to urban public environments, addressing the need for contextually-adaptive robots that navigate social group dynamics, weather, and infrastructure uncertainties. It presents a half-day workshop blueprint featuring pre-work, a keynote, a cultural-probe city-walk reflective activity, and open discussions to surface design opportunities and research questions. Key contributions include a structured process to identify tangible design guidelines and to form a cross-disciplinary OzCHI network, with outcomes aimed at guiding future work and publications. The practical impact lies in catalyzing collaborative efforts to develop urban-robot interactions that respect social contexts, inclusivity, and collective dynamics in real-world environments.

Abstract

The increasing transition of human-robot interaction (HRI) context from controlled settings to dynamic, real-world public environments calls for enhanced adaptability in robotic systems. This can go beyond algorithmic navigation or traditional HRI strategies in structured settings, requiring the ability to navigate complex public urban systems containing multifaceted dynamics and various socio-technical needs. Therefore, our proposed workshop seeks to extend the boundaries of adaptive HRI research beyond predictable, semi-structured contexts and highlight opportunities for adaptable robot interactions in urban public environments. This half-day workshop aims to explore design opportunities and challenges in creating contextually-adaptive HRI within these spaces and establish a network of interested parties within the OzCHI research community. By fostering ongoing discussions, sharing of insights, and collaborations, we aim to catalyse future research that empowers robots to navigate the inherent uncertainties and complexities of real-world public interactions.

Paper Structure

This paper contains 11 sections, 2 figures, 1 table.

Table of Contents

  1. Introduction
  2. Workshop Objectives
  3. Workshop Overview
  4. Pre-Workshop Plan
  5. Workshop Activities
  6. Invited Keynote Speaker
  7. Urban Context Reflective Activity
  8. Open Discussion
  9. Post-Workshop Plan and Expected Outputs
  10. Call for Participants
  11. Organisers

Figures (2)

  • Figure 1: Example of a contextually-adaptive HRI scenario: Way-finding robots working at the airport adapting to varied demographics and accessibility needs, e.g., aiding a visually impaired person with a guide dog.
  • Figure 2: Example of taking a photo with the probe