AUTHOR=Zhang Yifei , Doyle Thomas TITLE=Integrating intention-based systems in human-robot interaction: a scoping review of sensors, algorithms, and trust JOURNAL=Frontiers in Robotics and AI VOLUME=Volume 10 - 2023 YEAR=2023 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2023.1233328 DOI=10.3389/frobt.2023.1233328 ISSN=2296-9144 ABSTRACT=The increasing adoption of robot systems in industrial settings and teaming with humans have led to a growing interest in human-robot interaction (HRI) research. While many robots use sensors to avoid harming humans, they cannot elaborate on human actions or intentions, making them passive reactors rather than interactive collaborators. Intention-based systems can determine human motives and predict future movements, but their closer interaction with humans raises concerns about trust . This scoping review provides an overview of sensors, algorithms, and examines the trust aspect of intention-based systems in HRI scenarios . We searched MEDLINE, Embase, and IEEE Xplore databases to identify studies related to the forementioned topics of intention-based systems in HRI. Results from each study were summarized and categorized according to different intention types, representing various designs. The literature shows a range of sensors and algorithms used to identify intentions, each with their own advantages and disadvantages in different scenarios. However, trust of intention-based systems is not well studied. Although some research in AI and robotics can be applied to intention-based systems, their unique characteristics warrant further study to maximize collaboration performance. This review highlights the need for more research on the trust aspects of intention-based systems to better understand and optimize their role in human-robot interactions, at the same time establishes a foundation for future research in sensor and algorithm designs for intention-based systems.