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Dynamics Modeling and Parameter Identification for a Coupled-Drive Dual-Arm Nursing Robot

Chinese Journal of Mechanical Engineering 2024年第4期37卷 243-257页

作者： Hao Lu Zhiqiang Yang Deliang Zhu Fei Deng Shijie Guo College of Electronic Information and Automation Tianjin University of Science and TechnologyTianjin 300222China Academy for Engineering&Technology Fudan UniversityShanghai 200433China Shanghai Engineering Research Center of AI&Robotics Shanghai 200433China School of Mechanical Engineering Hebei University of TechnologyTianjin 300130China

A dual-arm nursing robot can gently lift patients and transfer them between a bed and a *** its lightweight design,high load-bearing capacity,and smooth surface,the coupled-drive joint is particularly well suited for these ***,the coupled nature of the joint disrupts the direct linear relationship between the input and output torques,posing challenges for dynamic modeling and practical *** study investigated the transmission mechanism of this joint and employed the Lagrangian method to construct a dynamic model of its internal *** on this foundation,the Newton-Euler method was used to develop a dynamic model for the entire robotic arm.A continuously differentiable friction model was incorporated to reduce the vibrations caused by speed transitions to *** experimental method was designed to compensate for gravity,inertia,and modeling errors to identify the parameters of the friction *** method establishes a mapping relationship between the friction force and motor *** addition,a Fourier series-based excitation trajectory was developed to facilitate the identification of the dynamic model parameters of the robotic *** tracking experiments were conducted during the experimental validation phase,demonstrating the high accuracy of the dynamic model and the parameter identification method for the robotic *** study presents a dynamic modeling and parameter identification method for coupled-drive joint robotic arms,thereby establishing a foundation for motion control in humanoid nursing robots.

关键词： Nursing-care robot Coupled-drive joint Dynamic modeling Parameter identification

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Nonlinear Dynamic Inversion-based Motion Planning of a Floating Satellite Platform

Nonlinear Dynamic Inversion-based Motion Planning of a Float...

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aiAA science and technology Forum and Exposition, aiAA SciTech Forum 2025

作者： Banerjee, Avijit Tevetzidis, Ilias Satpute, Sumeet Gajanan Nikolakopoulos, George Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents a nonlinear dynamic inversion-based motion plan for a levitating robotic satellite emulation platform. The frictionless motion of such a levitating platform has dynamic equivalency with a satellite’s realistic movement in space, thus evolving as an efficient demonstration tool as a hardware-in-loop satellite motion simulator. A brief design description of the emulation platform unified with various sensor and actuator units is presented, and an associated nonlinear mathematical model representing its coupled dynamic motion is described. The proposed control design architecture manipulates the associated nonlinear dynamics, which appear due to the coupling of translational and rotational movement of the robotic platform, thereby establishing an efficient trajectory tracking capability for various operating regions without the additional requirement of gain scheduling. In order to realize the control requirement through a set of ON-OFF thruster-based actuation units, which closely resembles the reaction control system of realistic satellite design, an optimal thrust allocation logic is proposed that accounts for various physical limitations of thrusters such as thrusters as its magnitude constraint and minimum on time. The efficacy of the proposed modelling and control scheme is experimentally validated in different realistic motion planning scenarios, such as point-to-point manoeuvres with terminal objectives and a superior path-following capability. The experimental studies are supported with related results. © 2025, American Institute of Aeronautics and Astronautics Inc, aiAA. All rights reserved.

关键词： Motion planning

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Enhancing doctor-patient communication in surgical explanations: Designing effective facial expressions and gestures for animated physician characters

Enhancing doctor-patient communication in surgical explanati...

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作者： Kim, Hwang Youn Ali, Ghazanfar Hwang, Jae-In AI-Robotics University of Science and Technology Daejeon Korea Republic of Center for Artificial Intelligence Korea Institute of Science and Technology Seoul Korea Republic of

Paying close attention to facial expressions, gestures, and communication techniques is essential when creating animated physician characters that are realistic and captivating when describing surgical procedures. This paper emphasizes the integration of appropriate emotions, co-speech gestures when medical experts explain the medical procedure, and designing animated characters. We can achieve healthy doctor-patient relationships and improvement of patients' understanding by depicting these components truthfully. We suggest two critical approaches to developing virtual medical experts by incorporating these elements. First, doctors can generate the contents of the surgical procedure with a virtual doctor. Second, patients can listen to the surgical procedure described by the virtual doctor and ask if they have any questions. Our system helps patients by considering their psychology and adding medical professionals' opinions. These improvements ensure the animated virtual agent is comforting, reassuring, and emotionally supportive. Through a user study, we evaluated our hypothesis and gained insight into improvements. © 2024 The Authors. Computer Animation and Virtual Worlds published by John Wiley & Sons Ltd.

关键词： Design

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Quadtree-based Free-space Cell-decomposition for Pathplanning with RRT* Implementation

Quadtree-based Free-space Cell-decomposition for Pathplannin...

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aiAA science and technology Forum and Exposition, aiAA SciTech Forum 2025

作者： Otte, Noah Satpute, Sumeet Gajanan Banerjee, Avijit Nikolakopoulos, George Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper introduces a novel, computationally efficient, random-search based path-planning algorithm specifically designed to enhance the dexterous accessibility of autonomous lunar rovers operating on highly cluttered obstacle-dense planetary surfaces. The proposed pathplanning framework employs a Quadtree-based cell decomposition to enhance the performance of sampling-based path-planning algorithms, specifically those in the category of Rapidlyexploring Random Trees (RRT) and its optimized variant, RRT*. In the process of generating the path through an occupancy grid map, the obstacle-free cells are utilized as discrete sampling points for the RRT* algorithm. A unique non-uniform sampling approach is employed to favour larger cells with a higher degree of safety, thereby enabling seamless navigation through the obstacle-dense map. Additionally, the non-uniform sampling approach enhances the overall computational efficiency of the framework, making it suitable for fast, lightweight onboard implementation. The efficacy of the proposed planning framework is demonstrated through numerous simulation scenarios. © 2025, American Institute of Aeronautics and Astronautics Inc, aiAA. All rights reserved.

关键词： Decision trees

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Navigating Label Ambiguity for Facial Expression Recognition in the Wild 39

Navigating Label Ambiguity for Facial Expression Recognition...

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39th Annual AAai Conference on Artificial Intelligence, AAai 2025

作者： Lee, JunGyu Choi, Yeji Kim, Haksub Kim, Ig-Jae Nam, Gi Pyo Korea Institute of Science and Technology Seoul Korea Republic of AI-Robotics KIST School University of Science and Technology Daejeon Korea Republic of Yonsei University Seoul Korea Republic of

ISBN: (纸本)157735897X

Facial expression recognition (FER) remains a challenging task due to label ambiguity caused by the subjective nature of facial expressions and noisy samples. Additionally, class imbalance, which is common in real-world datasets, further complicates FER. Although many studies have shown impressive improvements, they typically address only one of these issues, leading to suboptimal results. To tackle both challenges simultaneously, we propose a novel framework called Navigating Label Ambiguity (NLA), which is robust under real-world conditions. The motivation behind NLA is that dynamically estimating and emphasizing ambiguous samples at each iteration helps mitigate noise and class imbalance by reducing the model’s bias toward majority classes. To achieve this, NLA consists of two main components: Noise-aware Adaptive Weighting (NAW) and consistency regularization. Specifically, NAW adaptively assigns higher importance to ambiguous samples and lower importance to noisy ones, based on the correlation between the intermediate prediction scores for the ground truth and the nearest negative. Moreover, we incorporate a regularization term to ensure consistent latent distributions. Consequently, NLA enables the model to progressively focus on more challenging ambiguous samples, which primarily belong to the minority class, in the later stages of training. Extensive experiments demonstrate that NLA outperforms existing methods in both overall and mean accuracy, confirming its robustness against noise and class imbalance. To the best of our knowledge, this is the first framework to address both problems simultaneously. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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AvatARoid: A Motion-Mapped AR Overlay to Bridge the Embodiment Gap Between Robots and Teleoperators in Robot-Mediated Telepresence 25

AvatARoid: A Motion-Mapped AR Overlay to Bridge the Embodime...

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2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Ghimire, Amit Hou, Anova Kim, Ig-Jae Yoon, Dongwook Computer Science University of British Columbia VancouverBC Canada AI&Robotics Institute Korea Institute of Science and Technology Seoul Korea Republic of

ISBN: (纸本)9798400713941

Robot-mediated telepresence promises to facilitate effective social interaction between remote teleoperators and on-site users. However, disparities between the robot's form and the teleoperator's representation cause perceptual conflict in on-site users, degrading interaction quality. We introduce AvatARoid, a novel design that bridges this embodiment gap by superimposing the teleoperator's motion-mapped AR avatar overlay on a humanoid. We evaluated our design in a mixed-method study (n=48) using an immersive simulation where participants interacted with a confederate teleoperator, presented in either (a) a humanoid robot, (b) a humanoid robot with video, or (c) AvatARoid. Results suggest AvatARoid significantly improved teleoperator embodiment for on-site users, particularly enhancing co-location, and control perceptions, and providing richer non-verbal gestures. In contrast, video and baseline conditions often resulted in a pronounced disconnect between the teleoperator and the robot for on-site users. Our study offers new insights into designing novel teleoperator representations to promote social interaction in robot-mediated telepresence. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Anthropomorphic robots

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Mirror to Companion: Exploring Roles, Values, and Risks of ai Self-Clones through Story Completion 25

Mirror to Companion: Exploring Roles, Values, and Risks of A...

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2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Huang, Jessica Kim, Ig-Jae Yoon, Dongwook University of British Columbia VancouverBC Canada AI&Robotics Institute Korea Institute of Science and Technology Seoul Korea Republic of

ISBN: (纸本)9798400713941

Advancing technologies enable machine learning applications that replicate the appearance, behavior, and thought patterns of users based on their personal data. Termed as ai self-clones, these digital doppelgangers present introspective opportunities and existential risks, as they might amplify self-awareness or echo problematic self-views. In our study, based on the story completion method, we involved 20 diverse individuals to explore the values and risks they associate with creating ai self-clones. Our participants conceptualized ai self-clones by the roles these clones could assume, such as mirror, probe, companion, delegate, and representative. The perceived values and risks tend to correspond to these roles. For example, using self-clones as representatives could enhance relationship maintenance, yet it might also lead to diminished authenticity in personal connections;utilizing self-clones as probes to explore life scenarios could aid decision-making, but it might amplify regrets about unchosen paths. This research lays the groundwork for an ethical design of ai self-clone applications. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： ai self-clone

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Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset 39

Multi-View Pedestrian Occupancy Prediction with a Novel Synt...

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39th Annual AAai Conference on Artificial Intelligence, AAai 2025

作者： Aung, Sithu Sagong, Min-Cheol Cho, Junghyun Korea Institute of Science and Technology Korea Republic of AI-Robotics KIST School University of Science and Technology Korea Republic of Yonsei-KIST Convergence Research Institute Yonsei University Korea Republic of

ISBN: (纸本)157735897X

We address an advanced challenge of predicting pedestrian occupancy as an extension of multi-view pedestrian detection in urban traffic. To support this, we have created a new synthetic dataset called MVP-Occ, designed for dense pedestrian scenarios in large-scale scenes. Our dataset provides detailed representations of pedestrians using voxel structures, accompanied by rich semantic scene understanding labels, facilitating visual navigation and insights into pedestrian spatial information. Furthermore, we present a robust baseline model, termed OmniOcc, capable of predicting both the voxel occupancy state and panoptic labels for the entire scene from multi-view images. Through in-depth analysis, we identify and evaluate the key elements of our proposed model, highlighting their specific contributions and importance. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Suppressing Uncertainties in Degradation Estimation for Blind Super-Resolution 24

Suppressing Uncertainties in Degradation Estimation for Blin...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Lin, Junxiong Tao, Zen Tong, Xuan Mai, Xinji Wang, Haoran Wang, Boyang Wang, Yan Zhao, Qing Yu, Jiawen Lin, Yuxuan Yan, Shaoqi Gao, Shuyong Zhang, Wenqiang Shanghai Engineering Research Center of Ai & Robotics Academy for Engineering & Technology Fudan University Shanghai China East China University of Science and Technology Shanghai China Fudan University Shanghai China Engineering Research Center of Ai & Robotics Ministry of Education Academy for Engineering & Technology Fudan University Shanghai China

ISBN: (纸本)9798400706868

The problem of blind image super-resolution aims to recover high-resolution (HR) images from low-resolution (LR) images with unknown degradation modes. Most existing methods model the image degradation process using blur kernels. However, this explicit modeling approach struggles to cover the complex and varied degradation processes encountered in the real world, such as high-order combinations of JPEG compression, blur, and noise. Implicit modeling for the degradation process can effectively overcome this issue, but a key challenge of implicit modeling is the lack of accurate ground truth labels for the degradation process to conduct supervised training. To overcome this limitations inherent in implicit modeling, we propose an Uncertainty-based degradation representation for blind Super-Resolution framework (USR). By suppressing the uncertainties of local degradation representations in images, USR facilitated self-supervised learning of degradation representations. The USR consists of two components: Adaptive Uncertainty-Aware Degradation Extraction (AUDE) and a feature extraction network composed of Variable Depth Dynamic Convolution (VDDC) blocks. To extract Uncertainty-based Degradation Representation from LR images, the AUDE utilizes the Self-supervised Uncertainty Contrast module with Uncertainty Suppression Loss to suppress the inherent model uncertainty of the Degradation Extractor. Furthermore, VDDC block integrates degradation information through dynamic convolution. The VDDC also employs an Adaptive Intensity Scaling operation that adaptively adjusts the degradation representation according to the network hierarchy, thereby facilitating the effective integration of degradation information. Quantitative and qualitative experiments affirm the superiority of our approach. © 2024 ACM.

关键词： Self-supervised learning

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Comprehensive ATM Security Framework Combining GSM Alert Messaging and GPS Location Tracking

Comprehensive ATM Security Framework Combining GSM Alert Mes...

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International Conference on Smart Applications and Sustainability in the Artificial Intelligence of Things, SAS-aioT 2024

作者： Jimale, Mohamud Ahmed Ali, Mohamed Abdullahi Ahmed, Bashir Abdinur Mohamud, Mohamed Abdullahi Al-Turjman, Fadi Jamhuriya University of Science and Technology Mogadishu Somalia Research Center for AI IoT and Robotics Institute Near East University Nicosia Nicosia Cyprus

ISBN: (纸本)9783031782756

The proliferation of automated teller machines (ATMs) has made banking and financial transactions more convenient for consumers. However, the security of ATMs has become a growing concern, with increasing incidents of theft, skimming, and other criminal activities targeting these systems. This paper proposes designing and implementing a GSM and GPS-based ATM security system that utilizes sound and the ADXL335 accelerometer sensor to enhance the protection of ATM transactions. The proposed system incorporates a GSM module to enable real-time communication with a central monitoring station, allowing immediate notification of suspicious activities. Additionally, integrating a GPS module provides location-tracking capabilities, allowing tracking and identification of ATM locations in case of a security breach. The ADXL335 accelerometer sensor detects any physical tampering or movements of the ATM enclosure, triggering an alarm and transmitting the location data to the central monitoring station. Furthermore, the system employs sound-based detection methods to identify any unusual noises or disturbances within the ATM vicinity, providing an additional layer of security. The combination of GSM, GPS, accelerometer, and sound-based monitoring allows for a comprehensive security solution that effectively detects and responds to various threats targeting ATM systems. This research paper presents the proposed ATM security system's design, implementation, and evaluation, showcasing its effectiveness in enhancing the overall security of ATM transactions and protecting both users and financial institutions from criminal activities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Accelerometers

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