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Latin American Electron Devices Conference (LAEDC)

作者： A.X. González-Cely C.F. Blanco-Díaz Díaz Camilo A.R. T Bastos-Filho Telecommunications Laboratory Graduate Program in Electrical Engineering Federal University of Espírito Santo Av. Fernando Ferrari 514-Goiabeiras Vitoria Brazil Robotics and Assistive Technology Laboratory Graduate Program in Electrical Engineering Federal University of Espírito Santo Av. Fernando Ferrari 514-Goiabeiras Vitoria Brazil

The design of electrical wheelchair controllers remains a challenge for the scientific community. In recent years, Polymer Optical Fiber (POF)-based sensors have been used for biomedical applications, however, the application of these types of sensors for the control of assistive devices has been little explored. For this reason, this work proposes the design and validation of a fuzzy logic controller that uses information from an array of POF-based sensors located in a pillow, which is used for wheelchair control in four directions (right, left, forward and stop) by using neck movements. The results allow concluding that the system is fast, accurate, and reliable. This work presents a contribution related to the design of assistive devices based on optical fiber sensors and focuses on people with upper- and lower-limb mobility restrictions. Future studies will address the evaluation of the system for people with disabilities.

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Using Robot-Assisting Personalized Learning for Children with Autism: A Pilot Study of Robot's Actions

Using Robot-Assisting Personalized Learning for Children wit...

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Biomedical engineering International Conference (BMEiCON)

作者： Chatchai Paengkumhag Wisanu Jutharee Warissara Limpornchitwilai Kosin Chamnongthai Boonserm Keawkamnerdpong Biological Engineering Program Faculty of Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand Institute of Field Robotics King Mongkut’s University of Technology Thonburi Bangkok Thailand Department of Electronics and Telecommunication Engineering Faculty of Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand

There are a variety of symptoms of autism spectrum disorders. The appropriate interventions are selected according to the symptoms. Moreover, the key to successful intervention is to provide suitable therapy continuously. Unfortunately, the number of autism specialists is insufficient for the growing demands. Thus, for better intervention outcomes, the collaboration of parents/caregivers who help continue the intervention at home is crucial to the success of the intervention. However, it is not easy for inexperienced parents/caregivers. This study aimed to help parents/caregivers by using a robot to assist personalized learning for children with autism. We developed an artificial intelligence-based program to choose actions appropriate to the child user’s learning style or preference so that the child user stays attended to the activities the robot offers. In this pilot study, we tested using a robot to assist personalized learning with six participants in the special education needs school. The result of this study revealed the possibility of using a robot to assist in personalized learning for children with autism, from the perspective of the participants’ teacher. While interacting with the robot, the participants achieved a high average accuracy percentage of 83.36% and demonstrated a positive learning trend.

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Stress Classification Using a Low-Cost Optical Fiber Physiological Sensor: A Preliminary Study

Stress Classification Using a Low-Cost Optical Fiber Physiol...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： María Gaitán-Padilla Marcela Múnera Carlos A. Cifuentes Maxwell E. Monteiro Maria J. Pontes Camilo A. R. Diaz Graduate Program of Electrical Engineering Federal University of Espirito Santo Vitoria Brazil Bristol Robotics Laboratory University of the West of England Bristol UK Instituto Federal do Espirito Santo (IFES) Serra Brazil

The classification and measurement of stress through physiological sensors have been studied because of their high impact on mental health and well-being. Low-cost optical fiber wearable sensors, can monitor signals and be adaptive systems. Therefore, the present study sought to evaluate a lowcost optical fiber physiological sensor developed for stress classification while monitoring physiological signals. Five volunteers participated in a stress-induced test, where pulse and respiratory measurements were correctly performed with the optical fiber sensor during both stress and relaxation. The data obtained were used to find the best machine-learning classification algorithm for stress detection: a Bagged Decision Tree Classifier with an accuracy of 88%, and a precision of 91%. Thus, the proposed sensor can effectively monitor pulse and respiratory signals for stress classification. Based on these results, a study with more volunteers will be performed.

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Adaptive Fuzzy Sliding Mode Control With Logarithmic Sliding Surface for Active Suspension Systems

Adaptive Fuzzy Sliding Mode Control With Logarithmic Sliding...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Andika Aji Wijaya Fitri Yakub Winda Astuti Mahmud Iwan Solihin S. Syafiie Department of Mechanical Engineering University of Business and Technology (UBT) Jeddah Saudi Arabia Department of Electronic Systems Engineering University of Technology Malaysia (UTM) Kuala Lumpur Malaysia Department of Computer Engineering BINUS ASO School of Engineering Automotive and Robotics Program Bina Nusantara University (BINUS) Jakarta Indonesia Department of Mechanical and Mechatronics Engineering UCSI University Kuala Lumpur Malaysia Department of Chemical and Materials Engineering Faculty of Engineering-Rabigh King Abdulaziz University Jeddah Saudi Arabia

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

This paper introduces a hybrid control strategy that integrates the unique features of natural logarithm sliding mode control (lnSMC) and fuzzy logic systems. The lnSMC control approach ensures that the vibration amplitude remains within a bound, as determined by the parameters of the lnSMC switching function. Furthermore, the fuzzy logic system is employed to approximate the nonlinearities and uncertainties inherent in the suspension system components, such as the spring and damper. The stability of the closed-loop system is analyzed using the Lyapunov stability theorem, guaranteeing convergence within a finite time. To validate the effectiveness of the proposed controller, a simulation study was carried out using a quarter-car suspension model, considering the system’s nonlinearities, parameter uncertainties, and various external disturbances. The results indicate that the proposed controller significantly improves ride comfort while maintaining suspension deflection and road holding within critical safety limits.

关键词： Fuzzy logic Vibrations Uncertain systems Uncertainty Roads Switches Stability analysis Vehicle dynamics Springs Sliding mode control

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Decentralized Leader-Follower Visual Cooperative Package Transportation using Unmanned Aerial Manipulators

Decentralized Leader-Follower Visual Cooperative Package Tra...

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European Control Conference (ECC)

作者： Dimitris Chaikalis Nikolaos Evangeliou Anthony Tzes Farshad Khorrami Electrical & Computer Engineering Department New York University Brooklyn USA Electrical Engineering Program New York University Abu Dhabi United Arab Emirates Center for Artificial Intelligence and Robotics New York University Abu Dhabi United Arab Emirates

This paper is concerned with the problem of cooperative transportation of payloads by teams of unmanned aerial multirotor vehicles equipped with dexterous robotic arms. In order to increase the autonomy of such systems, a leader-follower setting is implemented. The leader UAV dictates the motion and all other follower UAVs attempt to maintain their desired relative pose with respect to the leader. A fiducial marker structure is attached to the leader, which allows all followers to continuously visually track the leader. Each robotic arm is equipped with force-torque sensors at its end-effector for improving the UAVs’ flight stability. Specialized controllers are designed for the aerial manipulator systems, in order to ensure a compliant behavior against forces transmitted through the payload. Simulations are provided using the Gazebo environment in order to validate the proposed control methods.

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Developing an Integrated Cognitive Test (ICT) for Computerized Assessment of Cognitive Impairment Risk

Developing an Integrated Cognitive Test (ICT) for Computeriz...

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Biomedical engineering International Conference (BMEiCON)

作者： Warissara Limpornchitwilai Chatchai Paengkumhag Wisanu Jutharee Kosin Chamnongthai Boonserm Kaewkamnerdpong Biological Engineering Program Faculty of Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand Institute of Field Robotics and Automation King Mongkut’s University of Technology Thonburi Bangkok Thailand Department of Electrical Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand

In an aging society, dementia is a notable issue that occurs as individuals grow older, impacting cognitive ability and emotional well-being. This has led to the development of cognitive assessment tools to facilitate early detection of cognitive impairment. Limited utilization of computerized tests across different countries is due to the mismatch of existing computerized tests between the educational and cultural backgrounds of the elderly; this study sought to address this issue by developing the Integrated Cognitive Test (ICT). ICT is designed as a computerized tool for assessing the risk of cognitive impairment in Thai older adults with an easy-to-use interface. Thirty-six elderly participants with diverse education levels and without prior cognitive impairment diagnoses participated in the study. They completed MoCA, MMSE, and ICT in a single-day experiment. The scores, reaction time, and overall completion time were recorded for analysis. The study found significant differences between ICT and MMSE scores (p<0.001) but not with MoCA (p=0.421); the results indicated ICT's potential alignment with MoCA for cognitive assessment. The decision tree attained 80.60% accuracy in cognitive impairment risk classification using MoCA output. Key features impacting classification included average reaction time in working memory, memory recall, and standard deviation in language tasks. Overall, the analysis demonstrated that ICT is an effective tool for assessing cognitive impairment, for older adults. Furthermore, designing a cognitive test that considers the unique education and cultural backgrounds of the Thai elderly can serve as a model for creating similar tests for other populations.

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Prototype design of an intelligent Internet of Things system combined green energy storage device

Prototype design of an intelligent Internet of Things system...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Ya-Chun Chen Hsien-Huang Peter Wu Kuo-Hsien Hsia Yung-Tsung Cheng Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Yunlin Taiwan Dept. of Electrical Engineering National Yunlin University of Science and Technology Yunlin Taiwan Bachelor Program in Intelligent Robotics National Yunlin University of Science and Technology Yunlin Taiwan Dept. of Electrical Engineering National Cheng Kung University Tainan Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

A set of miniature energy storage device through repurposing batteries and green power generation devices combined with an intelligent Internet of Things system is designed in this study. A large quantity of recycled and repurposed lithium batteries is applied as the core of the energy storage device; photovoltaic panels and minitype wind generators matching a wind-energy and solar-energy charge controller are used for charging batteries; and finally, an intelligent home Internet of Things system is utilized for monitoring and control. The experimental results reveal that the green power generation device appears longer effective charging time during the day, but could continuously generate electricity and store energy in the evening. The charging capacity is also larger than it simply using photovoltaic panels, and the intelligent home Internet of Things system could effectively monitor the power generation in a day and calculate carbon emissions. The prototype design results satisfy the expected function of an intelligent Internet of Things system combined green energy storage device.

关键词： Green energy Photovoltaic systems Wind energy generation Wind energy Green products Prototypes Companies

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3D Printed 6-Axis Collaborative Arm Robot Using Force Limiting Feature for Service Robot 3

3D Printed 6-Axis Collaborative Arm Robot Using Force Limiti...

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3rd International Conference on Eco engineering Development, ICEED 2019

作者： Saerang, Raymond Wiliem, David Tinggogoy, Feraldy Carles, Deddi Dani, M. Suwandi, Agri Oey, Endra Tan, Sofyan Automotive and Robotics Engineering Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

Collaborative arm robot is a robot that can work alongside humans. By using force limiting (FL) feature, where the force of the arm robot is limited and controlled, the robot can sense collision and stop its movement when it occurs. The idea is to apply the mentioned concept for service purposes. In this research a 6-axis arm robot with collision detection is developed. The design of the arm robot adopted the design of Universal Robot's UR3 with each joint capable of 360° rotation. The design approach is chosen for its flexibility to work in tight space with a maximum reach of half meter, as it is intended to work closely with human. This initial version robot is not intended to carry heavy load or move at high precision. With a maximum load of one Kg, this arm robot targets numerous applications that help human to do complex repetitive tasks, extend the reach of human operators, and help humans on many daily chores that usually does not involve heavy loads. The whole frame, which also serve as the cover of the robot, was made by 3D printing with multiple materials that fit to the strength and temperature requirement at each part of the robot. In order to detect collision, the arm robot employed smart servos at each joint with the ability to detect overcurrent and overvoltage, which allow the implementation of force limiting (FL) feature that will stop the robot in case of collision. The resulting arm robot managed to lift1 kg load and able stop its movement in the event of collision. Future research to improve the movement precision of the arm robot by adaptive methods is promising. © 2020 Published under licence by IOP Publishing Ltd.

关键词： 3D printers

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MambaXCTrack: Mamba-based Tracker with SSM Cross-correlation and Motion Prompt for Ultrasound Needle Tracking

arXiv

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arXiv 2024年

作者： Zhang, Yuelin Ding, Qingpeng Lei, Long Shan, Jiwei Xie, Wenxuan Zhang, Tianyi Yan, Wanquan Tang, Raymond Shing-Yan Cheng, Shing Shin Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Medical Physics Graduate Program Duke Kunshan University Jiangsu Kunshan China Department of Medicine and Therapeutics Institute of Digestive Disease The Chinese University of Hong Kong Hong Kong Department of Mechanical and Automation Engineering T Stone Robotics Institute Shun Hing Institute of Advanced Engineering Multi-Scale Medical Robotics Center Institute of Medical Intelligence and XR The Chinese University of Hong Kong Hong Kong

Ultrasound (US)-guided needle insertion is widely employed in percutaneous interventions. However, providing feedback on the needle tip position via US image presents challenges due to noise, artifacts, and the thin imaging plane of US, which degrades needle features and leads to intermittent tip visibility. In this paper, a Mamba-based US needle tracker MambaXCTrack utilizing structured state space models crosscorrelation (SSMX-Corr) and implicit motion prompt is proposed, which is the first application of Mamba in US needle tracking. The SSMX-Corr enhances cross-correlation by longrange modeling and global searching of distant semantic features between template and search maps, benefiting the tracking under noise and artifacts by implicitly learning potential distant semantic cues. By combining with cross-map interleaved scan (CIS), local pixel-wise interaction with positional inductive bias can also be introduced to SSMX-Corr. The implicit lowlevel motion descriptor is proposed as a non-visual prompt to enhance tracking robustness, addressing the intermittent tip visibility problem. Extensive experiments on a dataset with motorized needle insertion in both phantom and tissue samples demonstrate that the proposed tracker outperforms other stateof- the-art trackers while ablation studies further highlight the effectiveness of each proposed tracking module. © 2024, CC BY.

关键词： Needles

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Vehicle Speed Control in the Dilemma Zone Using Deep Learning

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Journal of Institute of Control, robotics and Systems 2022年第3期28卷 209-217页

作者： Lee, Jaewook Kim, Bongsang Sim, Hongseok Choi, Hyohyuk Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle･Intelligent Robotics The Graduate School of Hongik University Korea Republic of Mechanical and System Design Engineering Hongik University Korea Republic of

The dilemma zone refers to the area where a vehicle approaching an intersection as the light turns yellow must decide whether to stop or not. Often, the vehicle’s speed is too fast for it to stop at the stop line before the light turns red, but the vehicle cannot completely clear the intersection before the three-second yellow signal ends. This can lead to a major accident as the departing vehicle has not cleared the intersection before the opposite light changes to a green signal and cars on the other side of the intersection start to move. To prepare for this situation, traffic light patterns were modified using pre-trained data sets, then the traffic patterns at these lights were recorded using cameras. Autonomous vehicles were introduced into these areas and their speed was controlled based on the recognized traffic light patterns. This paper explores whether deep learning algorithms can effectively control vehicle speed when autonomous vehicles face the dilemma zone. © ICROS 2022.

关键词： Autonomous vehicles

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