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20th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2025

作者： Park, Cheonshu Cho, Miyoung Shin, Minjung Ryu, Jeh-Kwang Jang, Minsu Social Robotics Research Lab Daejeon Korea Republic of Seoul National University Interdisciplinary Program in Cognitive Science Seoul Korea Republic of Dongguk University Department of Physical Education Seoul Korea Republic of

ISBN: (纸本)9798350378931

This study presents an adaptive human-robot interaction (HRI) system that evaluates older adult participants' satisfaction with personalized health care programs. By integrating the CLOi robot with a large language model (LLM), the system conducts satisfaction surveys that adapt in real-time to participant responses. The system was applied to evaluate healthcare programs that include physical health measurements, exercise assessments, and virtual reality (VR) experiences. The system utilizes the CLOi robot and Claude API to analyze response clarity in real-time, automatically generating contextually appropriate follow-up questions when responses are deemed ambiguous. This adaptive questioning strategy ensures comprehensive response quality before proceeding to subsequent survey items. We conducted a preliminary feasibility study with five older adult participants to evaluate our approach. The system leverages LLM prompts to analyze gaps between question intent and participant responses, generating targeted follow-up questions as needed. Results demonstrate that our LLM-enhanced robotic interview system effectively reduced response ambiguity through dynamic follow-up questioning, achieving an 85% response resolution rate. This adaptive approach improved the clarity and specificity of healthcare satisfaction assessments for older adults. © 2025 IEEE.

关键词： Industrial robots

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RNR-Nav: A Real-World Visual Navigation System Using Renderable Neural Radiance Maps

RNR-Nav: A Real-World Visual Navigation System Using Rendera...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Minsoo Kim Obin Kwon Howoong Jun Songhwai Oh Interdisciplinary Program in Artificial Intelligence (IPAI) and ASRI Seoul Republic of Korea Department of Electrical and Computer Enginnering (ECE) and ASRI Seoul National University Seoul Republic of Korea Sequor Robotics Inc. Seoul Republic of Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We propose a novel visual localization and navigation framework for real-world environments directly integrating observed visual information into the bird-eye-view map. While the renderable neural radiance map (RNR-Map) [1] shows considerable promise in simulated settings, its deployment in real-world scenarios poses undiscovered challenges. RNR-Map utilizes projections of multiple vectors into a single latent code, resulting in information loss under suboptimal conditions. To address such issues, our enhanced RNR-Map for real-world robots, RNR-Map++, incorporates strategies to mitigate information loss, such as a weighted map and positional encoding. For robust real-time localization, we integrate a particle filter into the correlation-based localization framework using RNR-Map++ without a rendering procedure. Consequently, we establish a real-world robot system for visual navigation utilizing RNR-Map++, which we call "RNR-Nav." Experimental results demonstrate that the proposed methods significantly enhance rendering quality and localization robustness compared to previous approaches. In real-world navigation tasks, RNR-Nav achieves a success rate of 84.4%, marking a 68.8% enhancement over the methods of the original RNR-Map paper.

关键词： Location awareness Visualization Navigation Rendering (computer graphics) Particle filters Encoding Vectors Robustness Real-time systems Intelligent robots

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Adaptive Robot-Mediated Assessment using LLM for Enhanced Survey Quality in Older Adults Care programs 25

Adaptive Robot-Mediated Assessment using LLM for Enhanced Su...

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ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Cheonshu Park Miyoung Cho Minjung Shin Jeh-Kwang Ryu Minsu Jang Social Robotics Research Lab Electronics and Telecommunications Research Institute (ETRI) Daejeon Republic of Korea Interdisciplinary Program in Cognitive Science Seoul National University Seoul Republic of Korea Department of Physical Education Dongguk University Seoul Republic of Korea

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

关键词： Surveys Large language models Human-robot interaction Medical services Virtual reality Particle measurements Real-time systems Question generation Older adults Robots

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Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning

Renderable Street View Map-Based Localization: Leveraging 3D...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Howoong Jun Hyeonwoo Yu Songhwai Oh Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of Department of Intelligent Robotics & Mechanical Engineering Sungkyunkwan University (SKKU) Suwon-si Korea Republic of Department of Electrical and Computer Engineering (ECE) & Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a new method that first utilizes 3D Gaussian splatting in street-level localization problem. Robust localization with street-level real-world images such as street view is a major issue for autonomous vehicle, augmented reality (AR) navigation, and outdoor mobile robots. The objective is to determine the position and orientation of a query image that matches a street view database composed of RGB images. However, given the limited information available in the street view images, accurately determining the location solely based on this data presents a significant challenge. To address this challenge, we propose a novel method called renderable street view map-based localization (RSM-Loc). This approach enhances the localization process by augmenting 2D street view images into a renderable 3D map using 3D Gaussian splatting, to resolve street-level localization problems. Upon receiving a query RGB image without geometry information, the proposed method renders 2D images from a pre-made renderable map and compares image pose similarities between the rendered images and the query image. Through iterations of this process, the proposed method eventually estimates the pose of the given query image. The experimental results demonstrate that RSM-Loc outperforms the baselines with neural-field-based localization. Additionally, we conduct deep analysis on the proposed method to show that our method can serve as a new concept for the street-level localization problem.

关键词： Location awareness Visualization Matched filters Three-dimensional displays Image resolution Navigation Noise measurement Mobile robots Intelligent robots Image reconstruction

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A Portable Multiscopic Camera for Novel View and Time Synthesis in Dynamic Scenes

arXiv

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arXiv 2022年

作者： Zhang, Tianjia Lau, Yuen-Fui Chen, Qifeng The Hong Kong University of Science and Technology Hong Kong The Individualized Interdisciplinary Program The Robotics Institute Hong Kong The Department of Mathematics Hong Kong The Department of Computer Science and Engineering The Department of Electronic and Computer Engineering Hong Kong

We present a portable multiscopic camera system with a dedicated model for novel view and time synthesis in dynamic scenes. Our goal is to render high-quality images for a dynamic scene from any viewpoint at any time using our portable multiscopic camera. To achieve such novel view and time synthesis, we develop a physical multiscopic camera equipped with five cameras to train a neural radiance field (NeRF) in both time and spatial domains for dynamic scenes. Our model maps a 6D coordinate (3D spatial position, 1D temporal coordinate, and 2D viewing direction) to view-dependent and time-varying emitted radiance and volume density. Volume rendering is applied to render a photo-realistic image at a specified camera pose and time. To improve the robustness of our physical camera, we propose a camera parameter optimization module and a temporal frame interpolation module to promote information propagation across time. We conduct experiments on both real-world and synthetic datasets to evaluate our system, and the results show that our approach outperforms alternative solutions qualitatively and quantitatively. Our code and dataset are available at https://***/. Copyright © 2022, The Authors. All rights reserved.

关键词： Cameras

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M2FN: Multi-step modality fusion for advertisement image assessment

arXiv

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arXiv 2021年

作者： Park, Kyung-Wha Ha, Jung-Woo Lee, JungHoon Kwon, Sunyoung Kim, Kyung-Min Zhang, Byoung-Tak Interdisciplinary Program in Neuroscience Seoul National University Korea Republic of NAVER AI LAB NAVER CLOVA Statistics and Actuarial Science Soongsil University Korea Republic of School of Biomedical Convergence Engineering Pusan National University Korea Republic of Department of Computer Science and Engineering Seoul National University Korea Republic of Surromind Robotics

Assessing advertisements, specifically on the basis of user preferences and ad quality, is crucial to the marketing industry. Although recent studies have attempted to use deep neural networks for this purpose, these studies have not utilized image-related auxiliary attributes, which include embedded text frequently found in ad images. We, therefore, investigated the influence of these attributes on ad image preferences. First, we analyzed large-scale real-world ad log data and, based on our findings, proposed a novel multi-step modality fusion network (M2FN) that determines advertising images likely to appeal to user preferences. Our method utilizes auxiliary attributes through multiple steps in the network, which include conditional batch normalization-based low-level fusion and attention-based high-level fusion. We verified M2FN on the AVA dataset, which is widely used for aesthetic image assessment, and then demonstrated that M2FN can achieve state-of-the-art performance in preference prediction using a real-world ad dataset with rich auxiliary attributes. © 2021, CC BY-NC-SA.

关键词： Marketing

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Which ads to show? Advertisement image assessment with auxiliary information via multi-step modality fusion

arXiv

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arXiv 2019年

作者： Park, Kyung-Wha Lee, JungHoon Kwon, Sunyoung Ha, Jung-Woo Kim, Kyung-Min Zhang, Byoung-Tak Interdisciplinary Program in Neuroscience Seoul National University Statistics and Actuarial Science Soongsil University Clova AI Research NAVER Corp Department of Computer Science and Engineering Seoul National University Surromind Robotics

Assessing aesthetic preference is a fundamental task related to human cognition. It can also contribute to various practical applications such as image creation for online advertisements. Despite crucial influences of image quality, auxiliary information of ad images such as tags and target subjects can also determine image preference. Existing studies mainly focus on images and thus are less useful for advertisement scenarios where rich auxiliary data are available. Here we propose a modality fusion-based neural network that evaluates the aesthetic preference of images with auxiliary information. Our method fully utilizes auxiliary data by introducing multi-step modality fusion using both conditional batch normalization-based low-level and attention-based high-level fusion mechanisms, inspired by the findings from statistical analyses on real advertisement data. Our approach achieved state-of-the-art performance on the AVA dataset, a widely used dataset for aesthetic assessment. Besides, the proposed method is evaluated on large-scale real-world advertisement image data with rich auxiliary attributes, providing promising preference prediction results. Through extensive experiments, we investigate how image and auxiliary information together influence click-through rate. Copyright © 2019, The Authors. All rights reserved.

关键词： Image fusion

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On-body non-invasive glucose monitoring sensor based on high figure of merit (FoM) surface plasmonic microwave resonator

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Scientific reports 2023年第1期13卷 17527页

作者： Farzad Soltanian Mehdi Nosrati Saleh Mobayen Chuan-Chun Li Telung Pan Ming-Ta Ke Paweł Skruch Department of Electrical Engineering University of Alberta Edmonton Canada. Department of Electrical Engineering Manhattan College New York USA. Department of Electrical Engineering University of Zanjan Zanjan Iran. mobayens@yuntech.edu.tw. Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliou 640301 Yunlin Taiwan. mobayens@yuntech.edu.tw. National Taiwan University Hospital Yunlin Branch Yunlin Taiwan. a***@***. Bachelor Program in Interdisciplinary Studies College of Future National Yunlin University of Science and Technology Yunlin 64002 Taiwan. Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliou 640301 Yunlin Taiwan. Department of Automatic Control and Robotics AGH University of Science and Technology 30-059 Kraków Poland.

High-figure of merit (FoM) plasmonic microwave resonator is researched as a non-invasive on-body sensor to monitor the human body's blood glucose variation rate in adults for biomedical applications, e.g., diabetic patients. The resonance frequencies of the proposed sensor are measured to be around [Formula: see text] GHz and [Formula: see text] GHz over the frequency band of DC to 6GHz which are suitable for monitoring interstitial fluid (ISF) changing rate. The [Formula: see text] sensor is experimentally wrapped on the human body arm to monitor the blood glucose changing rate via amplitude and frequency variations of the sensor. Amplitude variation and frequency shift are measured to be around 7 dB and 30 MHz, respectively. The measured results demonstrate the high precision of the proposed approach to depict a valid diagram for glucose changing rate due to good impedance matching of the designed microwave sensor and human body. The sensor is shown to enhance the sensitivity by a factor of 5 compared to the conventional ones.

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A study for estimating reaction force of robot arm by using PDSPO

A study for estimating reaction force of robot arm by using ...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Hyun Hee Kim Sun Oh Park Jin Ho Kyung Hyun Min Do Min Cheol Lee Interdisciplinary Program in Robotics Pusan National University Busan Korea School of Mechanical Engineering Pusan National University Busan Korea Department of Robotics and Mechatronics Korea Institute of Machinery and Materials Daejeon Korea

In the industrial field, assembling parts using robot arm requires force information. Some robot arms with torque sensors are commercially available, but they are difficult to use for industrial applications due to durability problems. In addition, mounting a torque sensor on the robot arm increases manufacturing costs and complicates the structure. In this study, we apply Sliding Perturbation Observer (SPO) to 7-axis robot manipulator and estimate reaction force without using torque sensor in simulation. From the estimated perturbation, it can be determined whether the end effector of the robot manipulator will crash part of the assembly.

关键词： Manipulators Service robots Robot sensing systems Collision avoidance Observers Force

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A study on robust control method of underwater vehicle using SMCSPO

A study on robust control method of underwater vehicle using...

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Asian Control Conference

作者： Hyun Hee Kim Jong Seob Won Hyeon Jin Cho Jun Ho Hwang Min Cheol Lee Interdisciplinary Program in Robotics Pusan National University Geumjeong-gu Busan Korea Department of Mechanical and Automotive Engineering Jeonju University Wansan-gu Jeonju-si Jeollabuk-do Korea Agency for Defense Development Korea School of Mechanical Engineering Pusan National University Geumjeong-gu Busan Korea

ISBN: (纸本)9781509015740;9781509015733

The application of robust control method is required for the design of the automatic control system of the unmanned underwater vehicle which is operated in underwater environment under great disturbance. Sliding Perturbation Observer (SPO) was developed to overcome the chattering phenomenon which is a weak point of the sliding mode control. This control method can be applied to the control of underwater vehicle operating in strong environmental disturbances because it has the advantage of estimating and compensating for nonlinear components, modeling uncertainties and environmental disturbances of the system. In this study, the sliding mode control with sliding perturbation observer (SMCSPO) is simulated in an underwater vehicle to evaluate the disturbance compensation performance and compare it with a PID controller.

关键词： Underwater vehicles Perturbation methods Vehicle dynamics Observers Mathematical model Sliding mode control PI control

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