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arXiv 2023年

作者： Pereira, Ricardo Barros, Tiago Garrote, Luís Lopes, Ana Nunes, Urbano J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal Polytechnic Institute of Tomar Portugal

This work proposes a novel approach that uses a semantic segmentation mask to obtain a 2D spatial layout of the segmentation-categories across the scene, designated by segmentation-based semantic features (SSFs). These features represent, per segmentation-category, the pixel count, as well as the 2D average position and respective standard deviation values. Moreover, a two-branch network, GS2F2App, that exploits CNN-based global features extracted from RGB images and the segmentation-based features extracted from the proposed SSFs, is also proposed. GS2F2App was evaluated in two indoor scene benchmark datasets: the SUN RGB-D and the NYU Depth V2, achieving state-of-the-art results on both datasets. © 2023, CC BY.

关键词： Semantic Segmentation

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Approaching Test Time Augmentation in the Context of Uncertainty Calibration for Deep Neural Networks

arXiv

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arXiv 2023年

作者： Conde, Pedro Barros, Tiago Lopes, Rui L. Premebida, Cristiano Nunes, Urbano J. The Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Portugal Critical Software South Africa

With the rise of Deep Neural Networks, machine learning systems are nowadays ubiquitous in a number of real-world applications, which bears the need for highly reliable models. This requires a thorough look not only at the accuracy of such systems, but also at their predictive uncertainty. Hence, we propose a novel technique (with two different variations, named M-ATTA and V-ATTA) based on test time augmentation, to improve the uncertainty calibration of deep models for image classification. By leveraging an adaptive weighting system, M/V-ATTA improves uncertainty calibration without affecting the model’s accuracy. The performance of these techniques is evaluated by considering diverse metrics related to uncertainty calibration, demonstrating their robustness. Empirical results, obtained on CIFAR-10, CIFAR-100, Aerial Image Dataset, as well as in two different scenarios under distribution-shift, indicate that the proposed methods outperform several state-of-the-art post-hoc calibration techniques. Furthermore, the methods proposed also show improvements in terms of predictive entropy on out-of-distribution samples. Code for M/V-ATTA available at: https://***/pedrormconde/MV-ATTA Copyright © 2023, The Authors. All rights reserved.

关键词： Calibration

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An Effective Two-time Scale Composite Control Contraction Based Chaotic Trajectory Tracking of Two-link Flexible Manipulator

An Effective Two-time Scale Composite Control Contraction Ba...

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IEEE Conference on Decision and Control

作者： Kshetrimayum Lochan Asim Khan Binoy Krishna Roy Bidyadhar Subudhi Lakmal Seneviratne Irfan Hussain Department of Mechanical Engineering Khalifa University Center for Robotics and Autonomous Systems (KUCARS) Khalifa University United Arab Emirates Department of Electrical Engineering National Institute of Technology Silchar India Department of Electrical Engineering National Institute of Technology Warangal India

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, a two-link flexible manipulator n-dimensional model is developed using the assumed modes method. Based on this model, the manipulator dynamics are segregated into two subsystems by the two-time scale decomposition method of singular perturbation. Subsequently, a contraction-based control theory and a backstepping control of composite controller are investigated for the desired chaotic trajectory tracking along with tip deflection vibration suppression. In the two subsystems, the slow subsystem is involved in the modelling of the joint angles, and the fast subsystem is for corrected flexible modes of vibration suppression. In order to guarantee strict stability, Lyapunov’s stability is realized for closed-loop system uniform boundedness. Thus, by choosing the control parameters appropriately, the system states converge to a neighborhood of asymptotic stability. Eventually, extensive validation by comparative simulations of the Quanser model of the two-link flexible manipulator is carried out to demonstrate and indicate the effectiveness of the proposed composite controller in terms of faster tip deflection vibration suppression and better trajectory tracking.

关键词： Vibrations Asymptotic stability Backstepping Trajectory tracking Perturbation methods Stability analysis Robustness Control theory Complexity theory Manipulator dynamics

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Improving Lidar Based Tracking of UAVs Using an Approach Based on Focusing

Improving Lidar Based Tracking of UAVs Using an Approach Bas...

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Iberian robotics Conference (ROBOT)

作者： Alberto Cerutti Sedat Dogru Lino Marques Department of Electronics and Telecommunications (DET) Polytechnic University of Turin Turin Italy Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

This paper presents a novel approach for detecting drones using a lidar sensor integrated on a robotic turret. The turret rotates allowing the sensor to scan the sky, and both hardware components communicate in real-time. When the lidar sensor detects a drone, the detection data is used to dynamically adjust the motion pattern of the turret, allowing the system to capture more data by orienting the lidar sensor towards the drone, eventually improving tracking accuracy thanks to the higher number of detections achieved in this manner. In this paper we also explore different motion patterns for the turret, comparing them on the field to track a drone using the built lidar-turret system.

关键词： Laser radar Accuracy Uncertainty Tracking Focusing Robot sensing systems Real-time systems Hardware Optimization Drones

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Development of a Robotic Hand Glove System for Secure Grasp with AI Wireless Sensor Data 20

Development of a Robotic Hand Glove System for Secure Grasp ...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Almassri, Ahmed Koyanagi, Ken'Ichi Wada, Chikamune Horio, Keiichi Hasan, Wan Zuha Wan Toyama Prefectural University Department of Intelligent Robotics 5180 Kurokawa Toyama Imizu Japan Kyushu Institute of Technology Department of Life Science and Systems Engineering 2-4 Hibikino Fukuoka Kitakyushu Japan Universiti Putra Malaysia Department of Electrical and Electronic Selangor 43400 Malaysia Gaza Palestine

ISBN: (纸本)9798350320831

Robotic Hand glove is one of the most commonly used technique in the rehabilitation systems. In this paper, we developed a robotic hand system with a proposed sensing mechanism-based AI algorithm, which can acquire grasping forces from human fingers. It is composed of five low-cost force sensors attached to the glove's fingertips and wireless data logger. Several experiments including grasping a plastic bottle and squeezing a tennis ball are implemented to verify the efficiency of the proposed system using the developed glove. As a result, it accurately estimates the forces applied by each finger with the aim of achieving a secure grasp comparison with conventional methods. © 2023 IEEE.

关键词： Robotic arms

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A Review on Active Customers'Participation in Smart Grids

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Journal of Modern Power systems and Clean Energy 2023年第1期11卷 3-16页

作者： Konrad Schmitt Rabindra Bhatta Manohar Chamana Mahtab Murshed Ilham Osman Stephen Bayne Luciane Canha Electrical and Computer Engineering Department Texas Tech UniversityLubbockTX79409USA Wind Energy Program Texas Tech UniversityLubbockTX79409USA Electromechanical and Power Systems Department Federal University of Santa MariaSanta MariaRS97105-900Brazil Design Release Engineer at Electrification and Power conversion General MotorsGM Tech Center RoadWarrenMI48092USAl IEEE

Industrial,commercial,and residential facilities are progressively adopting automation and generation *** having flexible demand and renewable energy generation,traditional passive customers are becoming active participants in electric power system *** profound coordination among grid operators and active customers,the facilities’capability for demand response(DR)and distributed energy resource(DER)management will be valuable asset for ancillary services(ASs).To comply with the increasing demand and flexible energy,utilities urgently require standards,regulations,and programs to efficiently handle load-side resources without trading off stability and *** study reviews different types of customers’flexibilities for DR,highlighting their capabilities and limitations in performing local ancillary services(LASs),which should benefit the power grid by profiting from it through incentive *** financial incentives and techniques employed around the world are presented and *** potential barriers in technical and regulatory aspects are successfully identified and potential solutions along with future guidance are discussed.

关键词： Active distribution network(ADN) ancillary services energy management flexible demand resiliency

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Camera Lidar Fusion for Unmanned Aerial Vehicle Detection

Camera Lidar Fusion for Unmanned Aerial Vehicle Detection

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Iberian robotics Conference (ROBOT)

作者： Cosimo Leuci Sedat Dogru Lino Marques Department of Electronics and Telecommunications (DET) Polytechnic University of Turin Turin Italy Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Due to their low-cost and ease of use, cameras are very popular for drone detection. Thanks to the feature reach images obtained from the cameras, it is possible to classify drones with a relatively high success ratio. However, cameras lack the means for accurate localization, allowing only a rough measure of the orientation of the target UAV. In order to better localize the UAV, in this study we fuse camera and lidar measurements, localizing UAVs accurately. This fusion was implemented using a Kalman filter, which enables integration of both sensor data, improving detection and tracking accuracy

关键词： Location awareness YOLO Laser radar Accuracy Robot vision systems Cameras Autonomous aerial vehicles Kalman filters Vehicle dynamics Drones

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Segmentation of Retina Vessels in 2D OCT-Reconstructed Fundus Images with 3D UNet

Segmentation of Retina Vessels in 2D OCT-Reconstructed Fundu...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Tomasz Marciniak Agnieszka Stankiewicz Przemysław Zaradzki Department of Control Robotics and Electrical Engineering Division of Electronic Systems and Signal Processing Institute of Automatic Control and Robotics Poznan University of Technology Poznan Poland

This paper presents an analysis of the effectiveness of blood vessel segmentation in human retinal images. The segmentation process was carried out for three-dimensional optical coherence tomography (OCT) scans using the author’s publicly available CAVRI-C database. A 3D version of the U-Net artificial neural network was used. Various dimensions of the input blocks were investigated to determine their influence on the segmentation process. The effectiveness of the proposed solutions was evaluated using various metrics and the results obtained were compared with the 2D solution, also based on neural networks. The use of the proposed solutions allowed us to improve the segmentation even by 15% (in the case of the F1-score).

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Logarithmically Quantized Distributed Optimization over Dynamic Multi-Agent Networks

arXiv

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arXiv 2024年

作者： Doostmohammadian, Mohammadreza Pequito, Sérgio Mechatronics Department Faculty of Mechanical Engineering Semnan University Semnan Iran Department of Electrical and Computer Engineering Institute for Systems and Robotics Instituto Superior Técnico University of Lisbon Portugal

Distributed optimization finds many applications in machine learning, signal processing, and control systems. In these real-world applications, the constraints of communication networks, particularly limited bandwidth, necessitate implementing quantization techniques. In this paper, we propose distributed optimization dynamics over multi-agent networks subject to logarithmically quantized data transmission. Under this condition, data exchange benefits from representing smaller values with more bits and larger values with fewer bits. As compared to uniform quantization, this allows for higher precision in representing near-optimal values and more accuracy of the distributed optimization algorithm. The proposed optimization dynamics comprise a primary state variable converging to the optimizer and an auxiliary variable tracking the objective function's gradient. Our setting accommodates dynamic network topologies, resulting in a hybrid system requiring convergence analysis using matrix perturbation theory and eigenspectrumanalysis. © 2024, CC BY.

关键词： Support vector machines

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PointNetPGAP-SLC: A 3D LiDAR-based Place Recognition Approach with Segment-level Consistency Training for Mobile Robots in Horticulture

arXiv

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arXiv 2024年

作者： Barros, T. Garrote, L. Conde, P. Coombes, M.J. Liu, C. Premebida, C. Nunes, U.J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal Dept. of Aeronautical and Automotive Engineering LUCAS Lab Loughborough University United Kingdom

3D LiDAR-based place recognition remains largely underexplored in horticultural environments, which present unique challenges due to their semi-permeable nature to laser beams. This characteristic often results in highly similar LiDAR scans from adjacent rows, leading to descriptor ambiguity and, consequently, compromised retrieval performance. In this work, we address the challenges of 3D LiDAR place recognition in horticultural environments, particularly focusing on inter-row ambiguity by introducing three key contributions: (i) a novel model, PointNetPGAP, which combines the outputs of two statistically-inspired aggregators into a single descriptor;(ii) a Segment-Level Consistency (SLC) model, used exclusively during training to enhance descriptor robustness;and (iii) the HORTO-3DLM dataset, comprising LiDAR sequences from orchards and strawberry fields. Experimental evaluations conducted on the HORTO-3DLM and KITTI Odometry datasets demonstrate that PointNetPGAP outperforms state-of-the-art models, including OverlapTransformer and PointNetVLAD, particularly when the SLC model is applied. These results underscore the model’s superiority, especially in horticultural environments, by significantly improving retrieval performance in segments with higher ambiguity. The dataset and the code will be made publicly available at https://***/Cybonic/*** © 2024, CC BY.

关键词： Deep learning

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