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Iberian robotics Conference (ROBOT)

作者： Rodrigo Da-Silva-Gomez Alejandro Rodriguez-Ramos David Perez-Saura Guillermo GP-Lenza Fernando Palacios-Lopez Salvador Dominguez Ana Redondo-Rodriguez Daniel Sanz-Merodio Helder Rodriguez Pascual Campoy Miguel López Computer Vision and Aerial Robotics (CVAR) Centre for Automation and Robotics (CAR) UPM-CSIC ARQUIMEA Research Center (ARC) Universidad Politécnica de Madrid Spain

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

This study employs computer vision techniques to address beach safety concerns, with a focus on camera-equipped UAVs. The UAVs provide five channels of information that require preprocessing and image alignment to remove noise. The main challenges addressed are the identification of dangerous areas and people detection. For segmentation tasks, several lightweight models were evaluated, with YOLOv8-seg demonstrating superior efficiency and computational lightness across diverse conditions. In people detection, YOLOv8 also shows suitable results, identifying beach users, bathers, swimmers, and surfers. These solutions enable the use of UAVs for beach monitoring, providing a foundation for applications that evaluate danger for individuals on the beach. The results demonstrate the models' effectiveness and their capability to be deployed in real-time on board the UAVs.

关键词： computer vision Image segmentation Computational modeling Noise Real-time systems Safety Computational efficiency Monitoring

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Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed Transformer 24

Frequency Guidance Matters: Skeletal Action Recognition by F...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Wu, Wenhan Zheng, Ce Yang, Zihao Chen, Chen Das, Srijan Lu, Aidong Department of Computer Science University of North Carolina at Charlotte CharlotteNC United States Robotics Institute Carnegie Mellon University PittsburghPA United States One Inventory Organization Microsoft Corporation RedmondWA United States Center for Research in Computer Vision University of Central Florida OrlandoFL United States

ISBN: (纸本)9798400706868

Recently, transformers have demonstrated great potential for modeling long-term dependencies from skeleton sequences and thereby gained ever-increasing attention in skeleton action recognition. However, the existing transformer-based approaches heavily rely on the naive attention mechanism for capturing the spatiotemporal features, which falls short in learning discriminative representations that exhibit similar motion patterns. To address this challenge, we introduce the Frequency-aware Mixed Transformer (FreqMixFormer), specifically designed for recognizing similar skeletal actions with subtle discriminative motions. First, we introduce a frequency-aware attention module to unweave skeleton frequency representations by embedding joint features into frequency attention maps, aiming to distinguish the discriminative movements based on their frequency coefficients. Subsequently, we develop a mixed transformer architecture to incorporate spatial features with frequency features to model the comprehensive frequency-spatial patterns. Additionally, a temporal transformer is proposed to extract the global correlations across frames. Extensive experiments show that FreqMiXFormer outperforms SOTA on 3 popular skeleton action recognition datasets, including NTU RGB+D, NTU RGB+D 120, and NW-UCLA datasets. Our project is publicly available at: https://***/wenhanwu95/FreqMixFormer. © 2024 ACM.

关键词： Musculoskeletal system

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Complexity based investigation in collaborative assembly scenarios via non intrusive techniques 4

Complexity based investigation in collaborative assembly sce...

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4th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2022

作者： Panagou, Sotirios Sileo, Monica Papoutsakis, Konstantinos Fruggiero, Fabio Qammaz, Ammar Argyros, Antonis School of Engineering University of Basilicata Potenza85100 Italy Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology - Hellas Heraklion70013 Greece

Human and robot collaboration in assembly tasks is an integral part in modern manufactories. Robots provide advantages in both process and productivity with their repeatability and usability in different tasks, while human operators provide flexibility and can act as safeguards. However, process complexity increases which can lower the overall quality. Increased complexity can negatively influence decision making due to cognitive load on human operators, which can lead to lower quality, be it product, process or human work. Moreover, it can lead to safety risks, human-system error and accidents. In this work, we present the preliminary results on an experiment performed with student-participants, based on an assembly task. The experiment was set up to emulate an industrial assembly, and data collection was performed through qualitative and non-intrusive quantitative methods. Questionnaires were used to assess perceptual task complexity and cognitive load, while a stereo camera provided recordings for after-task analysis on process errors and human work quality based on a 3D skeleton-based human pose estimation and tracking method. The aim of the study is to investigate causes of errors and implications on quality. Future direction of the work is discussed. © 2022 The Authors. Published by ELSEVIER B.V.

关键词： Decision making

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Mitigating Overdiagnosis Bias in CNN-Based Alzheimer’s Disease Diagnosis for the Elderly 2nd

Mitigating Overdiagnosis Bias in CNN-Based Alzheimer’s Dis...

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2nd International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and 3rd International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with the International Conference on Medical Image Computing and computer Assisted Interventions, MICCAI 2024

作者： Dang, Vien Ngoc Casamitjana, Adrià Hernández-González, Jerónimo Lekadir, Karim Departament de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Research Institute of Computer Vision and Robotics University of Girona Girona Spain Departament d’Informàtica Matemàtica Aplicada i Estadística Universitat de Girona Girona Spain Barcelona Spain

ISBN: (纸本)9783031727863

Diagnosing Alzheimer’s disease (AD) presents significant challenges in the oldest populations due to overlapping symptoms of normal cognitive aging and early-stage dementia. While AI algorithms have matched specialist performance in diagnosing AD, they tend to produce unreliable results for the oldest populations, generating false positives that increase radiologist workloads and healthcare costs. In this study, we focus on mitigating overdiagnosis bias in CNN-based AD diagnosis for these groups. We present a post-hoc bias mitigation technique that significantly improves fairness by reducing overdiagnosis and enhances reliability by improving calibration without compromising overall model accuracy. Code is available at: https://***/ngoc-vien-dang/C-GTOP. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Distortion Correction of AUV-acquired Side-Scan Sonar Data

Distortion Correction of AUV-acquired Side-Scan Sonar Data

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OCEANS

作者： Valerio Franchi Hayat Rajani Rafael Garcia Borja Martinez-Clavel Nuno Gracias Computer Vision and Robotics Research Institute (VICOROB) University of Girona Girona Spain Tecnoambiente (A Tradebe Company) Barcelona Spain

Side scan sonars (SSS) are types of sonars that produce representations of the sea-bed by emitting and receiving acoustic fan-shaped pulses perpendicularly to the motion of the sensor in the water. Generally, SSS are deployed from a towed vehicle pulled from a boat at high speed to avoid oscillatory motions and thus achieve a clean and consistent sea-bed scan. Our approach targets the use of SSSs on small AUVs with limited computing power, and travelling at slow speeds, where the waterfall is directly used for real-time classfication. Due to the increased oscillatory motion, the SSS waterfall tends to have significant distortion, that will preclude the classifier from obtaining correct results. The algorithm described in this paper performs a geometric correction of the sonar scanlines by taking into account the AUV’s change in height, yaw and pitch to calculate correctly their positions on the seabed. The data is mapped into a 2D grid using the scanline intensities to form a mosaic, and the missing mosaic pixels are interpolated using a Gaussian-based kernel. The waterfall is recreated by considering a modified AUV trajectory with smooth changes in heading and a null pitch. The results show a significant improvement in the waterfall output, removing unwanted distortions and displaying the seabed structures with higher geometric consistency. In addition, the concentration of the ping data on the waterfall is constant all around, compared to the varying contribution density in the original one.

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Global Localization: Utilizing Relative Spatio-Temporal Geometric Constraints from Adjacent and Distant Cameras

arXiv

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arXiv 2023年

作者： Altillawi, Mohammad Pataki, Zador Li, Shile Liu, Ziyuan AI Robotics & Simulation Huawei Munich Research Center Germany Computer Vision Center Universitat Autònoma de Barcelona Spain Computer Vision and Geometry Lab ETH Zurich Switzerland

Re-localizing a camera from a single image in a previously mapped area is vital for many computer vision applications in robotics and augmented/virtual reality. In this work, we address the problem of estimating the 6 DoF camera pose relative to a global frame from a single image. We propose to leverage a novel network of relative spatial and temporal geometric constraints to guide the training of a Deep Network for localization. We employ simultaneously spatial and temporal relative pose constraints that are obtained not only from adjacent camera frames but also from camera frames that are distant in the spatio-temporal space of the scene. We show that our method, through these constraints, is capable of learning to localize when little or very sparse ground-truth 3D coordinates are available. In our experiments, this is less than 1% of available ground-truth data. We evaluate our method on 3 common visual localization datasets and show that it outperforms other direct pose estimation methods. © 2023, CC BY-NC-SA.

关键词： Cameras

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Robotic Approach Trajectory Using Reinforcement Learning with Dual Quaternions

Robotic Approach Trajectory Using Reinforcement Learning wit...

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Iberian robotics Conference (ROBOT)

作者： Daniel Frau-Alfaro Santiago T. Puente Ignacio De Loyola Páez-Ubieta Edison Velasco-Sánchez AUtomatics RObotics and Artificial Vision Lab University Institute for Computer Research San Vicente Spain University Institute for Engineering Research University Miguel Hernández Elche Spain

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Manipulation tasks in robotics usually involve two phases: an approach to the object and the grasp itself. The first action allows the robot to reach a certain pose in space that is likely to allow the object to be manipulated. Reinforcement Learning (RL) techniques allow a policy to be learned through experience given a set of states and actions, so this is a powerful tool for developing controllers for specific tasks such as positioning the robot in a particular point in space. However, when manipulating an object, orientation is as relevant as position. For this reason, a method of RL for positioning the robot's end effector in a suitable position and orientation for manipulation in simulation is presented. This approach models the problem of computing the distance for the reward function using dual quaternions parameterisation, an element that can represent the pose and attitude of a rigid body in Euclidean space in a compact way without having to apply any constraints.

关键词： Training Quaternions Computational modeling Process control Reinforcement learning Aerospace electronics End effectors Trajectory Robots

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Complexity based investigation in collaborative assembly scenarios via non intrusive techniques

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Procedia computer Science 2023年 217卷 478-485页

作者： Sotirios Panagou Monica Sileo Konstantinos Papoutsakis Fabio Fruggiero Ammar Qammaz Antonis Argyros School of Engineering University of Basilicata 85100 Potenza Italy Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology – Hellas 70013 Heraklion Greece

关键词： collaboration assembly task complexity cognitive load human pose estimation tracking

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*** 1.0: The Full Autonomous Stack for Oval Racing at High Speeds

Field Robotics

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Field robotics 2025年 4卷 99-137页

作者： Ayoub Raji Danilo Caporale Francesco Gatti Andrea Giove Micaela Verucchi Davide Malatesta Nicola Musiu Alessandro Toschi Silviu Roberto Popitanu Fabio Bagni Massimiliano Bosi Alexander Liniger Marko Bertogna Daniele Morra Francesco Amerotti Luca Bartoli Federico Martello Riccardo Porta University of Modena and Reggio Emilia Italy University of Parma Italy Technology Innovation Institute-Autonomous Robotics Research Center UAE HIPERT srl University of Pisa Italy HIPERT srl Computer Vision Lab ETH Zurich Switzerland

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at an unprecedented speed and in a head-to-head scenario, using independently developed software on open-wheel race cars. This paper presents the complete software architecture used by the team TII EuroRacing (TII-ER), covering all the modules needed to avoid static obstacles, perform active overtakes, and reach speeds above 75m/s (270km/h). In addition to the most common modules related to perception, planning, and control, we discuss the approaches used for vehicle dynamics modeling, simulation, telemetry, and safety. Overall results and the performance of each module are described, as well as the lessons learned during the first two events of the competition on oval tracks, where the team placed second and third, respectively.

关键词： Automobiles Cameras Laser radar Autonomous vehicles Location awareness Safety Planning Vehicle dynamics Testing Sports Motion planning Environmental monitoring

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Enhanced Electrical Signature Analysis (e-ESA) for Offshore Wind Permanent Magnet Generators

Enhanced Electrical Signature Analysis (e-ESA) for Offshore ...

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IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD)

作者： Jaime Renedo Anglada Weizhong Yan Bojun Feng Manoj Shah Electrical Systems GE Vernova Advanced Research Niskayuna NY USA Robotics AI & Computer Vision Group GE Vernova Advanced Research Niskayuna NY USA Electrical Systems GE Aerospace Research Niskayuna NY USA

ISBN: (数字)9798331520748

ISBN: (纸本)9798331520755

Offshore wind turbines can generate large amount of renewable energy, but the operation and maintenance (O&M) can be challenging due to the harsh and not easily accessible environment, which can increase operational costs. This work aims to develop methodologies that use the electrical signals of the power converters to detect faults that are not readily detected by existing protection systems of the generator. Currently there are condition monitoring systems based on vibration, thermal and electrical sensors but they can't detect faults like turn shorts and increased crimp resistance in direct-drive permanent magnet generators (PMGs). Detecting these faults early before they evolve into catastrophic failures can help to optimize O&M operations, prevent unplanned downtime and therefore reduce the operational expenditures (OPEX). The detection methodology uses the harmonic content of the electrical signals. The case study of a 6 MW turbine presents simulation results under healthy and unhealthy conditions, and the field data collected from operational wind farms. The results of the features considered show a promising separability between healthy and unhealthy conditions, which indicates that this methodology could be implemented for condition monitoring of PMGs in offshore wind farms.

关键词： Condition monitoring Vibrations Renewable energy sources Permanent magnet generators Thermal resistance Simulation Wind farms Thermal sensors Sensor systems Wind turbines

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