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International Conference on Applied Nonlinear Dynamics, Vibration, and Control, ICANDVC 2023

作者： Yu, Zige Li, Sai Lin, Mengying Hu, Hang Li, Yingying Lei, Qian Huang, Zixin School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Tianjin300350 China

ISBN: (纸本)9789819705535

To address the limitations of single-point tactile perception in soft biomimetic actuators, such as fixed positioning, limited coverage area, low resolution at long distances from the geometric center, and challenges in maintaining high sensitivity and stability over a broad range, a novel soft biomimetic tactile actuator based on a pneumatic array is designed and manufactured. Using liquid silicone rubber and BMP280 pressure sensor, the actuator was crafted by an injection molding process. Silicone gel was injected into the pressure sensor array, and vacuum extraction created a sealed space within the sensor cavity. The pressure excitation applied on the surface of the actuator could be converted into electrical signals, enabling tactile pressure detection. An STM32 microprocessor is utilized for building haptic information acquisition and processing system, with sensitivity assessed using the Kalman filter algorithm. Experimental results show that the soft biomimetic tactile actuator has high sensitivity and minimal repetition error, which can effectively detects changes in tactile force output, mitigates noise interference, and enhances the precision and stability of physiological pressure data feedback in physiotherapy applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bionics

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Monocular Person Localization with Lidar Fusion for Social Navigation

Monocular Person Localization with Lidar Fusion for Social N...

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European Conference on Mobile Robots (ECMR)

作者： Sedat Dogru Carlos A. Silva Lino Marques Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

Smooth social navigation requires not only detection of the people around the robot, but also accurate localization of the people, a process difficult to achieve with a single sensing modality. Hence, literature has focused on various fusion approaches, such as RGB-D, ROI based lidar vision fusion, or Artificial Neural Network (ANN) based lidar vision fusion. However, monocular photogrammetry has always been ignored in the literature. In this work, we propose a fusion approach based on monocular positon estimation and lidar, and show the effectivenes of the approach both on a public dataset and a purpose built dataset with different cameras.

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Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

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Petroleum Science 2023年第2期20卷 1142-1154页

作者： Yun-Peng He Chuan-Zhi Zang Peng Zeng Ming-Xin Wang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyangLiaoning 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyangLiaoning 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyangLiaoning 110169China University of Chinese Academy of Sciences Beijing100049China Shenyang University of Technology ShenyangLiaoning 110870China School of Automation and Electrical Engineering Shenyang Ligong UniversityShenyangLiaoning 110159China

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

关键词： Few-shot learning Indicator diagram Meta-learning Soft thresholding Sucker-rod pumping system Time–frequency signature Working condition recognition

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Exploring Player's Body as a Game Controller for Fitness Activity Promotion

Exploring Player's Body as a Game Controller for Fitness Act...

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Experiment@ International Conference (exp.at)

作者： Diogo Simões Paulo Menezes Electrical and Computer Engineering Department University of Coimbra Institute of Systems and Robotics Coimbra Portugal

ISBN: (数字)9798350314403

ISBN: (纸本)9798350314410

In recent years, there has been a tendency for people to resort to a more sedentary lifestyle, which has only been aggravated by the COVID-19 pandemic and the evermore common remote work policies. This lack of physical activity brings negative health outcomes and can generally be difficult to overcome due to how challenging it can be for a person to find the motivation to adopt a more physically active routine. To address this issue, we propose the use of serious games as an engaging, fun, and highly motivational tool that can aid people in their quest for a healthier lifestyle. We focus on three problem areas: motor control improvement and rehabilitation, post-stroke rehabilitation, and physical activity for general health. There exist multiple solutions for these problems which often require specific equipment that may not be available to the common user. Therefore, we propose a different approach requiring solely a laptop equipped with a camera, thus making it more practical and accessible to the wider public.

关键词： COVID-19 Motor drives Portable computers Pandemics Games Cameras Remote working

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Modifying Gait: A Strategy for Joint Reaction Forces Reduction in Below-Knee Amputees

Modifying Gait: A Strategy for Joint Reaction Forces Reducti...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Haonan He Kaifeng Li Jie Zhang Shengquan Xie Zhi-Qiang Zhang Institute of Robotics Autonomous Systems and Sensing School of Electronic and Electrical Engineering University of Leeds

Compared to healthy people, people with transtibial amputation (TTA) are more prone to arthritis in their intact legs, especially in hip and knee joints. The main reason is that people with TTA typically depend more on their intact legs for generating forward movements, resulting in high joint reaction forces in the intact leg. Therefore, a new gait pattern with lower joint loads is essential to people with TTA to prevent arthritis. In this paper, we use predictive simulation to generate a new gait pattern that can decrease the joint reaction forces for people with TTA. The reflex-based controller is used to control muscle excitation, which is fed into Hill muscle-based forward dynamics to generate muscle forces and thus gait movement based on the motion of the equation. To find the optimal parameters in the reflex-based controller, we then propose a cost function to minimise effort, ground reaction force and joint reaction force together by covariance matrix adaptation evolution strategy. Experimental results have indicated the new gait pattern generated by our approach can reduce the joint reaction forces for people with TTA, while the energy consumption doesn't have a significant change, which demonstrates the effectiveness of this method.

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MuSe4ASD - An Interactive Music Station for Children with ASD

MuSe4ASD - An Interactive Music Station for Children with AS...

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Experiment@ International Conference (exp.at)

作者： Beatriz Lagos Paulo Menezes Electrical and Computer Engineering Department University of Coimbra Institute of Systems and Robotics Coimbra Portugal

ISBN: (数字)9798350314403

ISBN: (纸本)9798350314410

This article explores the topic involving children with autism, referencing what this condition is about, as well as the hypotheses for approaching the problem based on the literature reviewed. The proposed approach involves the creation of an adequate space with an immersive interactive system based on musical stimuli, and physical exercise to improve their communication, memory, visual and motor capabilities, and eventually potentiate the development of artistic skills. The development of this interactive system includes the development of an avatar that will be animated using Motion Capture technology, so it can interact with the child and accompany him/her while doing the exercises with fluid movements.

关键词： Visualization Autism Fluids Interactive systems Avatars Music Variable speed drives

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Application of Machine Learning Techniques for Predicting False Data Injection Attacks in Smart Grid 25

Application of Machine Learning Techniques for Predicting Fa...

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25th International Middle East Power System Conference, MEPCON 2024

作者： Sakr, Hesham A. Eladl, Abdelfattah A. Ibrahim, Hegazi M. El-Afifi, Magda I. Elsewedy University of Technology Faculty of Engineering Technology Cairo Egypt Nile Higher Institute for Eng. and Technology Dept. of Elect. and Comm.Eng Mansoura Egypt Mansoura University Faculty of Engineering Electrical Engineering Department El-Mansoura35516 Egypt Egyptian Chinese University Faculty of Computers and Information Systems Cairo Egypt

ISBN: (纸本)9798350379648

Attacks that involve False Data Injection (FDI) provide a substantial risk to the safety and dependability of contemporary power systems. The weaknesses that are present inside the system's infrastructure are exploited by these attacks, which frequently circumvent the conventional measures that detect bad data. Because of the sophistication of these attacks, which are characterized by their ability to circumvent conventional protections and their targeted nature, it is necessary to develop novel techniques to detection and mitigation. For the purpose of identifying, preventing, and predicting FDI threats, this research studies the application of machine learning approaches. In order to improve the security posture of power systems, the strategy that has been developed intends to make use of the potential that data-driven models possess. According to preliminary findings, the approach that was developed demonstrates a high level of accuracy in identifying anomalies within the data of the system, which suggests that it has the potential to be an effective countermeasure against FDI threats. In particular, Extra Trees and XGBClassifier are quite efficient when it comes to identifying attacks that include the injection of bogus data into power systems. © 2024 IEEE.

关键词： Adversarial machine learning

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Impact of UAV Propellers on Gas Plume Tracking

Impact of UAV Propellers on Gas Plume Tracking

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European Conference on Mobile Robots (ECMR)

作者： Rui Baptista Hugo Magalhães Lino Marques Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

Unmanned Aerial Vehicles (UAVs) are highly manoeuvrable platforms that are becoming popular to map and localise the source of chemical substances in the environment. However, their propellers disturb the environment and may seriously impact the measurements and the expected results in such applications. Some works have already addressed this problem, but only for specific cases and proposing different solutions about the best way to mitigate this problem. This work studies the impact of propellers for multiple sensor positions and 3 UAVs of different sizes, in an Odour Source Localisation (OSL) problem under field conditions and compares the results with a non-disturbing setup. The experiments show a significant impact on the measured signals from asymmetrical frames and from the motion of the agent, with the best results achieved from sensors acquiring data on intake air regions.

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A Semantic Mapping Framework for Service Robots 25

A Semantic Mapping Framework for Service Robots

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40th Annual ACM Symposium on Applied Computing, SAC 2025

作者： Frota, Lucyanno Rocha, Rui P. Dept. of Electrical and Computer Engineering University of Coimbra Coimbra Portugal Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (纸本)9798400706295

Service robots are undergoing a massification process similar to what happened with personal computers and cell phones a few decades ago. Their ubiquitous coexistence and interaction with humans requires that their representation models of the workspace go beyond metric information used for safe navigation. They are also required to assign semantic meaning to objects and places, i.e. to build semantic maps, in order to understand scenes and engage in human-like interactions. This paper proposes the Semantic MAPping (SMAP) framework to provide a service robot operating in human populated environments with a semantic mapping layer on top of a metric SLAM layer. SMAP is modular, expandable, and efficient enough to run locally on the robot. It has been implemented in Robot Operating System 2 (ROS2) using modular Docker containers. Preliminary experiments with a Pioneer 3-DX mobile robot having a system on module Nvidia Jetson AGX Xavier demonstrated its potential for future service robotics applications. Copyright © 2025 held by the owner/author(s).

关键词： Modular robots

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Emergency Clinical Procedure Detection via Wearable Sensors 66th

Emergency Clinical Procedure Detection via Wearable Sensors

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66th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2022

作者： Baskaran, Prakash Heard, Jamison Adams, Julie A. Collaborative Robotics and Intelligent Systems Institute Oregon State University CorvallisOR United States Department of Electrical and Microelectronic Engineering Rochester Institute of Technology NY United States

Communicating a patient’s state accurately during transfer from emergency medical technicians to hospital personnel is crucial for optimal care. Prior work demonstrated automated algorithms that combined wearable sensors with video data from cameras to detect clinical procedures and improve this information transfer. However, incorporating video requires task- or environment-specific installation mechanisms, raises privacy concerns, and is susceptible to occlusion and image noise. The presented approach detects clinical procedures using wearable sensors (i.e., inertial and electrophysiological) only and the procedures’ subtasks to mitigate the sensors’ signal variability to provide clinical procedure detection. © 2022 by Human Factors and Ergonomics Society. All rights reserved.

关键词： Ergonomics

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