Transferability of HRI Research: Potential and Challenges
Wafa Johal
TL;DR
The paper addresses the transferability gap in HRI research, arguing that traditional user-centered approaches often fail to bridge to industrial deployment. It classifies HRI contributions into Practice, Evaluation, and Theory and Methods, and analyzes how each can produce outcomes and societal benefits, from patentable artefacts to open datasets and formal guidelines. It highlights practical, industry-driven, and standardisation challenges, proposing channels for translation, open science, and industry-academic collaboration to improve adoption. This work underscores the need for translational pathways and workforce alignment to maximize the economic and social impact of HRI research.
Abstract
With advancement of robotics and artificial intelligence, applications for robotics are flourishing. Human-robot interaction (HRI) is an important area of robotics as it allows robots to work closer to humans (with them or for them). One crucial factor for the success of HRI research is transferability, which refers to the ability of research outputs to be adopted by industry and provide benefits to society. In this paper, we explore the potentials and challenges of transferability in HRI research. Firstly, we examine the current state of HRI research and identify various types of contributions that could lead to successful outcomes. Secondly, we discuss the potential benefits for each type of contribution and identify factors that could facilitate industry adoption of HRI research. However, we also recognize that there are several challenges associated with transferability, such as the diversity of well-defined job/skill-sets required from HRI practitioners, the lack of industry-led research, and the lack of standardization in HRI research methods. We discuss these challenges and propose potential solutions to bridge the gap between industry expectations and academic research in HRI.