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

作者： Anara Sandygulova Andrey Yershov Aida Zhanatkyzy Zhansaule Telisheva Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Human action recognition is concerned with analysing, understanding and synthesizing kinematic and kinetic data. Data-driven computer vision solutions have advanced the progress in the field of action recognition while it would not be possible without large and publicly available datasets. While there are numerous datasets available for adult action recognition, child-centered action recognition efforts are still scarce. This paper presents a dataset that consists of video recordings of 200 children of different age and gender groups performing seven actions (boxing, waving, clapping, running, jogging, walking towards the camera, and walking from side to side). Two camera perspectives are provided, with a top view and a frontal view in RGB format. The dataset provides an opportunity for kinematic analysis of children motion while it also aims to bridge the performance gap between activity recognition systems for adults and children.

关键词： Training Legged locomotion Transfer learning Human-robot interaction Estimation Kinematics Cameras Human activity recognition Video recording Testing

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Seat-Focused Multi-DOF Exoskeleton Wheelchair Synergy for Continuous Lower-Limb Rehabilitation

Seat-Focused Multi-DOF Exoskeleton Wheelchair Synergy for Co...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Voicu, Razvan Cristian Freeman, Charles F. Garretson, Christopher E. Sun, Zoe M. Bonus, Ryan H. Slutzky, Zachary A. Mukesh, Niranjan Tanveer, Muhammad Hassan Tello, Yannique Chang, Yusun Kennesaw State University Department of Robotics & Mechatronics Engineering MariettaGA United States

ISBN: (纸本)9798331504847

Wheelchair users with limited or nonexistent lower-limb mobility often struggle with significant muscle atrophy, circulatory complications, and other health issues. Although exoskeletons for gait training have shown promise, many are optimized for upright ambulation and overlook individuals remaining fully seated due to clinical or practical constraints. This article presents a seat-focused exoskeleton synergy integrated with a wheelchair to facilitate multi-DOF lower-limb mobilization without requiring transfers or standing maneuvers. The system addresses a critical gap by providing repeated, lower-intensity knee and ankle exercises throughout the day-either passively, actively with assistance, or in a resistive training mode-thus promoting muscle engagement and circulation from a seated position. The exoskeleton leverages the wheelchair's power source and employs modular, adjustable rails to accommodate diverse leg lengths. Emphasis is placed on biomechanical alignment, safe torque control, and user comfort, supported by a model-based controller accounting for inertia, Coriolis effects, and gravity in real time. Bench tests and preliminary trials confirm stable torque output, accurate tracking of desired motion profiles, and minimal burden when attaching or detaching the device. The article introduces modeling for a two-DOF prototype (knee flexion/extension and ankle dorsiflexion/plantarflexion), expandable to include additional joints or degrees of freedom, enabling broader rehabilitation targets such as hip abduction/adduction. By embedding rehabilitative capabilities directly into the wheelchair environment, the proposed approach seeks to close the gap between infrequent clinic appointments and continuous therapy aimed at mitigating muscle ailments. A seat-focused exoskeleton designed for every-day use can facilitate accessible, on-demand rehabilitation and substantially improve long-term health outcomes for mobility impaired users. © 2025 IEEE.

关键词： Physical therapy

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Gesture-Guided Exosuit Interface: Advancing Motion Tracking and Automation for Robotic Control

Gesture-Guided Exosuit Interface: Advancing Motion Tracking ...

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IEEE Southeastcon

作者： Jaykob Aksoy Jose Gonzalez Siddhant Ala Franccesca Tabertus Jose Chagoya Charles Koduru M. Hassan Tanveer Matthew Marshall Yusun Chang Department of Robotics and Mechatronics Engineering Kennesaw State University Marietta GA USA

Exosuits, also known as exoskeletons, represent a burgeoning technology designed to augment human physical capabilities while alleviating bodily strain. This project introduces a novel approach to exosuit functionality, focusing on motion tracking through a fused deposition modeled apparatus with rotary hall effect sensors. The system precisely monitors shoulder and elbow joint movements, translating them into control signals for a two-wheeled robot. The innovative design aims to provide an affordable, hands-free solution for motion tracking, offering applications in the control and automation of various vehicles, machines, and equipment. The research addresses challenges such as sensor data fusion, aiming to seamlessly integrate sensor information for real-time control. As exosuits evolve, the emphasis lies in minimizing size, enhancing comfort, and expanding applications, potentially leading to inconspicuous, wearable devices with broad compatibility. The goal is to create user-friendly exosuit with a modular design, capable of controlling a variety of devices, with minimal setup and calibration. This project contributes to the ongoing development of exosuit technology, offering a promising avenue for future applications in fields ranging from virtual reality, medical and industrial domains.

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Data Collection, Heat Map Generation for Crack Detection Using Robotic Dog Fused with FLIR Sensor

Data Collection, Heat Map Generation for Crack Detection Usi...

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IEEE Southeastcon

作者： Jose Chagoya Shrey Patel Charles Koduru Aiden Kovarovics M. Hassan Tanveer Razvan C. Voicu Department of Robotics and Mechatronics Engineering Kennesaw State University Marietta GA USA

The imperative need to monitor critical infrastructure, encompassing power plant transformers and essential civil structures, is paramount for ensuring their sustained longevity and safety. A notable progression in this domain arises from the widespread availability of Forward-Looking Infrared (FLIR) cameras, made possible by reductions in manufacturing costs. These FLIR cameras, distinguished by their remarkable precision in temperature data collection and visualization, hold significant potential across diverse fields. This paper underscores the pioneering application of FLIR cameras in infrastructure monitoring, with a specific focus on power transformers and aging civil structures like bridges. In the realm of transformers, the FLIR camera exhibits the capability to delve into and record internal temperatures, facilitating the early identification of deviations from standard operational temperature ranges. Detection of such anomalies serves as a trigger for preemptive measures, thereby minimizing operational disruptions. Similarly, for structures such as bridges, routine FLIR analyses prove instrumental in discerning temperature variations that may indicate potential wear or fractures. This timely identification allows for proactive maintenance, ensuring structural integrity and averting potential hazards. To augment the safety and efficiency of data collection, this research advocates for the integration of FLIR cameras with mobile robots, exemplified by the Unitree GoAirl. This strategic amalgamation enables precise yet remote surveillance, mitigating risks to operators while maximizing the accuracy of infrastructure health assessments. The proposed approach not only advances the capabilities of FLIR technology but also her-alds a paradigm shift in the realm of infrastructure monitoring, promising enhanced reliability and safety standards.

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Separation of microalgae from bacterial contaminants using spiral microchannel in the presence of a chemoattractant

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Bioresources and Bioprocessing 2024年第1期11卷 511-525页

作者： Leticia F.Ngum Y.Matsushita Samir F.El-Mashtoly Ahmed M.R.Fath El-Bab Ahmed L Abdel-Mawgood Institute of Basic and Applied Sciences Biotechnology ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Institute of Basic and Applied Sciences Nanoscience ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Mechatronics and Robotics Engineering Department Egypt-Japan University of Science and TechnologyAlexandria 21934Egypt.

Cell separation using microfluidics has become an effective method to isolate biological contaminants from bodily fluids and cell cultures,such as isolating bacteria contaminants from microalgae cultures and isolating bacteria contaminants from white blood *** this study,bacterial cells were used as a model contaminant in microalgae culture in a passive microfluidics device,which relies on hydrodynamic forces to demonstrate the separation of microalgae from bacteria contaminants in U and W-shaped cross-section spiral microchannel fabricated by defocusing CO_(2) laser *** a flow rate of 0.7 ml/min in the presence of glycine as bacteria chemoattractant,the spiral microfluidics devices with U and W-shaped cross-sections were able to isolate microalgae(Desmodesmus sp.)from bacteria(***)with a high separation efficiency of 92%and 96%*** the same flow rate,in the absence of glycine,the separation efficiency of microalgae for U-and W-shaped cross-sections was 91%and 96%,*** was found that the spiral microchannel device with a W-shaped cross-section with a barrier in the center of the channel showed significantly higher separation *** microchannel chips with U-or W-shaped cross-sections were easy to fabricate and exhibited high *** these advantages,these devices could be widely applicable to other cell separation applications,such as separating circulating tumor cells from blood.

关键词： W-shaped cross-section CO_(2)laser ablation Glycine Separation efficiency Removal ratio

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Planar Metastructure-based Gas Sensors for High Stretchability and Stable NO2 Sensing

Planar Metastructure-based Gas Sensors for High Stretchabili...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Jeonhyeong Park Hyeoncheol Lim Chaehyun Ryu Soon In Jung Il Ryu Jang Hoe Joon Kim Department of Robotics and Mechatronics Engineering DGIST South Korea

The paper presents a flexible and stretchable carbon nanotube (CNT) based gas sensor fabricated on a planar metastructure, kirigami substrate with anatase TiO 2 functionalization for improved NO 2 sensing performances with high stretchability. The developed kirigami-based sensor possesses a network of notches with high softness and stretchability, ensuring a stable sensor operation of up to 80% strain. Such a high strain range overcomes the current limitation of gas sensors, which generally utilize rather brittle and rigid sensing materials. The innovative claims include (1) the utilization of kirigami architecture to mitigate the uniaxial strain effect and (2) the enhancement of sensor performance regarding the sensitivity and recovery time owing to TiO 2 functionalization. Mechanical properties of the kirigami structure can be analyzed via stress-strain relation, and the sensing material properties are characterized using Fourier-transform infrared spectroscopy (FT-IR) and Raman spectroscopy. The suggested kirigami-based gas sensors could be applied to wearable and stretchable gas sensing applications.

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Improving Road Safety With Enhanced Vehicle Detection for Night-time Traffic in Mirpur 6

Improving Road Safety With Enhanced Vehicle Detection for Ni...

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6th International Conference on robotics and Automation in Industry, ICRAI 2024

作者： Younis, Usama Riaz, Faisal Raza, Umar Atali, Gokhan Rabnawaz, Hamid HEC Control Automotive and Robotics Lab Islamabad Pakistan Manchester Metropolitan University Department of Engineering Manchester United Kingdom Mechatronics Engineering Sakarya University of Applied Sciences Sakarya54050 Turkey Selftech Pvt Ltd Pakistan

ISBN: (纸本)9798350355703

This paper presents a study on improving night-time vehicle detection in the Mirpur region through a modified neural network model. Given the challenges of low visibility at night, the research focused on optimizing a deep learning algorithm to enhance detection accuracy. A dataset of 10,000 images covering various vehicle types was collected and annotated to train and test the model. The study found a 7% increase in detection performance compared to the standard model, highlighting the potential for tailored algorithms in specific environmental conditions. The findings suggest significant implications for road safety and autonomous driving systems, particularly in regions with similar night-time driving challenges. The research contributes to the broader field of computer vision by showing the effectiveness of model optimization in real-world conditions. © 2024 IEEE.

关键词： Vehicle safety

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Humanoid robotics Powered by Vision-Based LLM Zero Shot Interactions

Humanoid Robotics Powered by Vision-Based LLM Zero Shot Inte...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Smith, Gabriel David Debrah-Pinamang, Kwasi Voicu, Razvan Cristian Kennesaw State University Department of Robotics & Mechatronics Engineering MariettaGA United States

ISBN: (纸本)9798331504847

Advancements in artificial intelligence (AI) have transformed robotics by enabling systems to autonomously execute complex tasks with minimal human involvement. Traditional methods, however, often depend on costly hardware, continuous monitoring, and intricate software integration, which constrain scalability and widespread implementation. This research presents an innovative approach that combines vision-based large language models (LLMs) with zero-shot prompting to autonomously program robotic systems, including a humanoid robot equipped with dual manipulators. The proposed system harnesses contextual image data to efficiently generate task-specific code, eliminating the need for iterative corrections. Training is conducted through OpenAI's Assistant feature, utilizing documents predominantly comprising images, while continuous operation is facilitated by a self-looping mechanism. Experimental results highlight the system's capability to perform manipulator tasks with notable accuracy, paving the way for scalable, adaptive, and dynamic automation. This study addresses both practical and theoretical challenges in automation, providing a cost-effective framework for next-generation robotic systems. © 2025 IEEE.

关键词： Anthropomorphic robots

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Design and Implementation of a Cost-Effective Semi-Autonomous Scissor Lift Robot for Industrial Material Handling

Design and Implementation of a Cost-Effective Semi-Autonomou...

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IEEE Southeastcon

作者： Ricardo Juarez Marquis Ledet Daisie Johnson M. Hassan Tanveer Matthew Marshall Department of Robotics and Mechatronics Engineering Kennesaw State University Marietta GA USA

This paper presents the mechanism, system configuration, basic control algorithm, and integrated functions of a Semi-Autonomous Robotic Lift designed for efficient industrial material handling. The robot combines the capabilities of traditional manual tools with advanced sensors, including infrared, ultrasonic, and gesture sensors, to carry, lift, and navigate within a specified area. The use of a gesture sensor enables a user-friendly command protocol for scissor lift operations through simple hand movements. The robot's stability on uneven surfaces is ensured by four wheels and robust materials, such as steel and 3/4” wood, allowing it to withstand heavy loads safely. Safety protocols, including speed limits, light indicators, and an emergency stop button, adhere to industry standards. The Semi-Autonomous Robotic Lift, constructed with a mixture of steel and plywood, aims to facilitate the transportation of heavy materials in indoor industrial or warehouse settings, providing a cost-effective alternative to existing products.

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Guest Editorial: Future Mobility Technology

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Journal of Institute of Control, robotics and Systems 2023年第5期29卷

作者： Yun, Donwon Department of Robotics and Mechatronics Engineering DGIST Korea Republic of

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