Adhering to current HRI paradigms, all of the sensors, visualisation and legibility of actions and motions are borne by the robot or its working cell. This necessarily makes robots more complex or confines them into specialised, structured environments. We propose leveraging the state of the art of wearable technologies, such as augmented reality head mounted displays, smart watches, sensor tags and radio-frequency ranging, to "adapt" the human and reduce the requirements and complexity of robots.
HiSync: Spatio-Temporally Aligning Hand Motion from Wearable IMU and On-Robot Camera for Command Source Identification in Long-Range HRI
Department of Computer Science；Technology, BNRist Tsinghua University Beijing China；Technology, BNRist, College of AI Tsinghua University Beijing China；Technology Tsinghua University Beijing China；Beijing University of Posts；Academy of Arts \& Design Tsinghua University Beijing China；Qinghai University Xining China；Tsinghua University；Technology, BNRist, College of AI；Technology Tsinghua University；Academy of Arts \& Design Tsinghua University；Qinghai University
Purdue University（普渡大学）；University of California, Santa Cruz（加州大学圣克鲁兹分校）
Wearable biosensors can enable continuous human data capture, facilitating development of real-world Human-Robot Interaction (HRI) systems. However, a lack of standardized libraries and implementations adds extraneous complexity to HRI system designs, and precludes collaboration across disciplines and institutions. Here, we introduce a novel wearable biosensor package for the Robot Operating System 2 (ROS 2) system. The ROS2 officially supports real-time computing and multi-robot systems, and thus provides easy-to-use and reliable streaming data from multiple nodes. The package standardizes bi…
École Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）
Human-Robot Interfaces (HRIs) represent a crucial component in telerobotic systems. Body-Machine Interfaces (BoMIs) based on body motion can feel more intuitive than standard HRIs for naive users as they leverage humans' natural control capability over their movements. Among the different methods used to map human gestures into robot commands, data-driven approaches select a set of body segments and transform their motion into commands for the robot based on the users' spontaneous motion patterns. Despite being a versatile and generic method, there is no scientific evidence that implementing a…
Positioning Modular Co-Design in Future HRI Design Research
Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington（信息学、计算与工程学院，印第安纳大学布卢明顿分校）；Human-Computer Interaction Institute, Carnegie Mellon University（人机交互研究所，卡内基梅隆大学）
Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University（迪肯大学智能系统研究与创新研究所（IISRI））
Exoskeletons and orthoses are wearable mobile systems providing mechanical benefits to the users. Despite significant improvements in the last decades, the technology is not fully mature to be adopted for strenuous and non-programmed tasks. To accommodate this insufficiency, different aspects of this technology need to be analysed and improved. Numerous studies have tried to address some aspects of exoskeletons, e.g. mechanism design, intent prediction, and control scheme. However, most works have focused on a specific element of design or application without providing a comprehensive review f…
Uppsala University（乌普萨拉大学）；University of Potsdam（波茨坦大学）
Over the past years, extensive research has been dedicated to developing robust platforms and data-driven dialog models to support long-term human-robot interactions. However, little is known about how people's perception of robots and engagement with them develop over time and how these can be accurately assessed through implicit and continuous measurement techniques. In this paper, we explore this by involving participants in three interaction sessions with multiple days of zero exposure in between. Each session consists of a joint task with a robot as well as two short social chats with it …
Personalised Explanations in Long-term Human-Robot Interactions
PAL robotics (Barcelona, Spain)（PAL机器人公司（巴塞罗那，西班牙））；Institut de Robòtica i Informàtica Industrial (IRI-CSIC)（机器人与信息技术研究所（IRI-CSIC））；Universitat Politècnica de Catalunya - BarcelonaTech (UPC)（巴塞罗那技术大学（UPC））；University of Hamburg（汉堡大学）；Artificial Intelligence Research Institute (IIIA-CSIC)（人工智能研究所（IIIA-CSIC））
US CCDC Army Research Laboratory（美国CCDC陆军研究实验室）；Oak Ridge Associated Universities（橡树岭联合大学）；Defence Science and Technology（国防科学技术集团）；Swinburne University of Technology（斯威本科技大学）
Human-robot teaming offers great potential because of the opportunities to combine strengths of heterogeneous agents. However, one of the critical challenges in realizing an effective human-robot team is efficient information exchange - both from the human to the robot as well as from the robot to the human. In this work, we present and analyze an augmented reality-enabled, gesture-based system that supports intuitive human-robot teaming through improved information exchange. Our proposed system requires no external instrumentation aside from human-wearable devices and shows promise of real-wo…
We propose a set of communicative gestures and develop a gesture recognition system with the aim of facilitating more intuitive Human-Robot Interaction (HRI) through gestures. First, we propose a set of commands commonly used for human-robot interaction. Next, an online user study with 190 participants was performed to investigate if there was an agreed set of gestures that people intuitively use to communicate the given commands to robots when no guidance or training were given. As we found large variations among the gestures exist between participants, we then proposed a set of gestures for …
Are We Generalizing from the Exception? An In-the-Wild Study on Group-Sensitive Conversation Design in Human-Agent Interactions
Cologne Cobots Lab, TH Köln - University of Applied Sciences（科隆机器人实验室，TH Köln应用科学大学）；KI Park e.V. & FAU - Friedrich-Alexander University of Erlangen-Nuremberg（KI Park协会与弗赖堡-艾森纳赫大学）
Italian Institute of Technology (IIT)（意大利理工学院）；University of Genova（热那亚大学）；University of Hertfordshire（赫特福德大学）
In our everyday lives we are accustomed to partake in complex, personalized, adaptive interactions with our peers. For a social robot to be able to recreate this same kind of rich, human-like interaction, it should be aware of our needs and affective states and be capable of continuously adapting its behavior to them. One proposed solution to this problem would involve the robot to learn how to select the behaviors that would maximize the pleasantness of the interaction for its peers, guided by an internal motivation system that would provide autonomy to its decision-making process. We are int…
XR-DT: Extended Reality-Enhanced Digital Twin for Safe Motion Planning via Human-Aware Model Predictive Path Integral Control
Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin（德克萨斯大学奥斯汀分校土木、建筑与环境工程系）；School of Architecture, The University of Texas at Austin（德克萨斯大学奥斯汀分校建筑学院）；School of Civil and Construction Engineering, Purdue University（普渡大学土木与建设工程学院）；Department of Civil and Environmental Engineering, University of Wisconsin-Madison（威斯康星大学麦迪逊分校土木与环境工程系）
