Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces
Ryo Suzuki, Adnan Karim, Tian Xia, Hooman Hedayati, Nicolai Marquardt

TL;DR
This survey reviews 460 studies on augmented reality in robotics, categorizing approaches, design strategies, and application domains to guide future research in AR-enhanced human-robot interaction.
Contribution
It provides a comprehensive taxonomy of AR and robotics research, synthesizing diverse approaches and identifying key challenges and opportunities for future work.
Findings
AR improves human-robot interaction effectiveness
Categorization of AR approaches and design strategies
Identification of research gaps and future directions
Abstract
This paper contributes to a taxonomy of augmented reality and robotics based on a survey of 460 research papers. Augmented and mixed reality (AR/MR) have emerged as a new way to enhance human-robot interaction (HRI) and robotic interfaces (e.g., actuated and shape-changing interfaces). Recently, an increasing number of studies in HCI, HRI, and robotics have demonstrated how AR enables better interactions between people and robots. However, often research remains focused on individual explorations and key design strategies, and research questions are rarely analyzed systematically. In this paper, we synthesize and categorize this research field in the following dimensions: 1) approaches to augmenting reality; 2) characteristics of robots; 3) purposes and benefits; 4) classification of presented information; 5) design components and strategies for visual augmentation; 6) interaction…
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