Using Sound to Communicate Robot's Internal State in Human-Robot Interaction: A Study on Sonification for Explicit Feedback
While sonification can effectively convey a robot's internal state and improve its expressiveness in human-robot interaction, careful sound design is crucial, as initial user feedback reveals that the chosen sounds, though useful, were perceived as unpleasant and uninteresting.
Force-Myography Based Human Arm Pose Estimation for Collision Avoidance in Human-Robot Interaction
This research explores the feasibility of using a shoulder-worn force-myography (FMG) device to estimate human arm pose for real-time collision avoidance in human-robot interaction, demonstrating its potential as a robust and calibration-free alternative to vision-based and IMU-based methods.
이타심을 가진 로봇: 강화 학습과 마음 이론을 활용한 로봇 보조 행동 개선
마음 이론 능력을 갖춘 적응형 로봇은 사용자의 작업 수행 능력을 향상시키고 로봇에 대한 신뢰도를 높여 더욱 효과적인 인간-로봇 협업을 가능하게 한다.
Development of a Dual-Arm Robot Platform for Human-Robot Interaction Using ROS and Multimodal AI
This research paper presents the development of a dual-arm robot platform using ROS and multimodal AI, focusing on object recognition, voice control, and system accuracy for improved human-robot interaction.
로봇의 단서가 인간의 결정을 조종할 수 있을까? 인간-로봇 팀워크에서 편향 제어 비선형 의견 역학 및 로봇 시선 상호 작용을 통한 합의 구축 탐구
본 연구는 로봇이 인간의 의사 결정에 영향을 미치고 합의를 유도할 수 있는지에 대한 여부를 실험적으로 탐구하며, 특히 로봇 시선을 통한 편향 제어 비선형 의견 역학 모델을 제시하고, 인간-로봇 팀워크에서의 협력적 의사 결정 과정을 분석합니다.
Wearable High-Density Electromyography for Controlling Assistive Mobile Manipulators: A Feasibility Study
This research demonstrates the feasibility of using a wearable high-density electromyography (HDEMG) system to intuitively control a mobile manipulator for performing assistive tasks in a home setting.
用於人類行為預測的去混淆框架：增強動態環境中機器人系統的性能
為了增強機器人在動態環境中的預測能力，本文提出了一個去混淆框架，用於消除人類行為預測中的混淆因素，並提高多變量時間序列預測的準確性。
A Deconfounding Framework for Human Behavior Prediction Using Wearable Sensor Data to Enhance Robotic Systems in Dynamic Environments
Integrating deconfounding algorithms with multivariate time series prediction models using wearable sensor data significantly improves the accuracy of human behavior prediction, leading to more effective and safer human-robot interaction in dynamic environments.
2D/3Dビジュアルおよび触覚フィードバックに基づく、空中操作用ヒューマンロボットインターフェースの評価
空中操作における、3D MRビジョンと触覚フィードバックは、ユーザーの習熟度向上と効率的な飛行に貢献する。
Evaluation of Mixed Reality and Haptic Feedback on Operator Performance in Aerial Telemanipulation
While operator experience remains the most significant factor in aerial telemanipulation, integrating 3D mixed reality vision and haptic feedback independently enhances operator dexterity and efficiency in aerial manipulation tasks.
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