Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces

• URL: http://arxiv.org/abs/2203.03254v1
• Date: Mon, 7 Mar 2022 10:22:59 GMT
• Title: Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces
• Authors: Ryo Suzuki, Adnan Karim, Tian Xia, Hooman Hedayati, Nicolai Marquardt
• Abstract summary: Augmented and mixed reality (AR/MR) have emerged as a new way to enhance human-robot interaction. This paper contributes to a taxonomy of augmented reality and robotics based on a survey of 460 research papers.
• Score: 21.72715373737208
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 techniques and modalities; 7) application domains; and 8) evaluation strategies. We formulate key challenges and opportunities to guide and inform future research in AR and robotics.

Related papers

• A Survey of Embodied Learning for Object-Centric Robotic Manipulation [27.569063968870868]
  Embodied learning for object-centric robotic manipulation is a rapidly developing and challenging area in AI. Unlike data-driven machine learning methods, embodied learning focuses on robot learning through physical interaction with the environment.
  arXiv  Detail & Related papers  (2024-08-21T11:32:09Z)
• Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI [129.08019405056262]
  Embodied Artificial Intelligence (Embodied AI) is crucial for achieving Artificial Intelligence (AGI) MLMs andWMs have attracted significant attention due to their remarkable perception, interaction, and reasoning capabilities. In this survey, we give a comprehensive exploration of the latest advancements in Embodied AI.
  arXiv  Detail & Related papers  (2024-07-09T14:14:47Z)
• AI for Science: An Emerging Agenda [30.260160661295682]
  This report documents the programme and the outcomes of Dagstuhl Seminar 22382 "Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling" The transformative potential of AI stems from its widespread applicability across disciplines, and will only be achieved through integration across research domains. Alongside technical advances, the next wave of progress in the field will come from building a community of machine learning researchers, domain experts, citizen scientists, and engineers.
  arXiv  Detail & Related papers  (2023-03-07T20:21:43Z)
• The Road to a Successful HRI: AI, Trust and ethicS-TRAITS [64.77385130665128]
  The aim of this workshop is to foster the exchange of insights on past and ongoing research towards effective and long-lasting collaborations between humans and robots. We particularly focus on AI techniques required to implement autonomous and proactive interactions.
  arXiv  Detail & Related papers  (2022-06-07T11:12:45Z)
• Human-Robot Collaboration and Machine Learning: A Systematic Review of Recent Research [69.48907856390834]
  Human-robot collaboration (HRC) is the approach that explores the interaction between a human and a robot. This paper proposes a thorough literature review of the use of machine learning techniques in the context of HRC.
  arXiv  Detail & Related papers  (2021-10-14T15:14:33Z)
• A Survey on Human-aware Robot Navigation [22.926878248788558]
  This paper is concerned with the navigation aspect of a socially-compliant robot. It provides a survey of existing solutions for the relevant areas of research as well as an outlook on possible future directions.
  arXiv  Detail & Related papers  (2021-06-22T10:09:25Z)
• The Road to a Successful HRI: AI, Trust and ethicS-TRAITS [65.60507052509406]
  The aim of this workshop is to give researchers from academia and industry the possibility to discuss the inter-and multi-disciplinary nature of the relationships between people and robots.
  arXiv  Detail & Related papers  (2021-03-23T16:52:12Z)
• Semantics for Robotic Mapping, Perception and Interaction: A Survey [93.93587844202534]
  Study of understanding dictates what does the world "mean" to a robot. With humans and robots increasingly operating in the same world, the prospects of human-robot interaction also bring semantics into the picture. Driven by need, as well as by enablers like increasing availability of training data and computational resources, semantics is a rapidly growing research area in robotics.
  arXiv  Detail & Related papers  (2021-01-02T12:34:39Z)
• SAPIEN: A SimulAted Part-based Interactive ENvironment [77.4739790629284]
  SAPIEN is a realistic and physics-rich simulated environment that hosts a large-scale set for articulated objects. We evaluate state-of-the-art vision algorithms for part detection and motion attribute recognition as well as demonstrate robotic interaction tasks.
  arXiv  Detail & Related papers  (2020-03-19T00:11:34Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.