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International Conference on Control, Artificial Intelligence, robotics & Optimization (ICCAIRO)

作者： Nikolaos Kounalakis Emmanouil Kalykakis Dimitrios Kosmopoulos John Fasoulas Michael Sfakiotakis Control Systems and Robotics Laboratory (CSRL) School of Engineering Hellenic Mediterranean University Heraklion Greece Dept. of Computer Engineering and Informatics University of Patras Patras Greece

We present an integrated framework for intelligent automated plant monitoring, towards early disease and pest detection in greenhouse tomato crops. The framework combines the use of a robotic mobile platform to autonomously collect multi-spectral images of the plants, with a tool that utilizes Faster R-CNN to detect regions that signify the presence of a disease or pest. The robot is based on a modified mobile vertical mast lift platform, and integrates a 6-dof robotic arm that is used to position the plant imaging multi-spectral camera. The robot can navigate autonomously inside the greenhouse via a magnetic guidance sensor. Results from a series of experiments demonstrate the validity and effectiveness of the implemented framework.

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A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification

arXiv

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arXiv 2024年

作者： Zhang, Lu Lambotharan, Sangarapillai Zheng, Gan Liao, Guisheng Demontis, Ambra Roli, Fabio School of Electronic Engineering Xidian University Xi’an710071 China Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough University Loughborough United Kingdom Dept. of Electrical and Electronic Engineering University of Cagliari Piazza d’Armi Cagliari09123 Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Genoa16145 Italy

Motivated by the superior performance of deep learning in many applications including computer vision and natural language processing, several recent studies have focused on applying deep neural network for devising future generations of wireless networks. However, several recent works have pointed out that imperceptible and carefully designed adversarial examples (attacks) can significantly deteriorate the classification accuracy. In this paper, we investigate a defense mechanism based on both training-time and run-time defense techniques for protecting machine learning-based radio signal (modulation) classification against adversarial attacks. The training-time defense consists of adversarial training and label smoothing, while the run-time defense employs a support vector machine-based neural rejection (NR). Considering a white-box scenario and real datasets, we demonstrate that our proposed techniques outperform existing state-of-the-art technologies. Copyright © 2024, The Authors. All rights reserved.

关键词： Support vector machines

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A Machine Learning Approach to Unveil Balance Behavior Through Aging with an Auditory Cue

A Machine Learning Approach to Unveil Balance Behavior Throu...

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Marta Guarischi Yaxin Hu Ahmet Burak Kurt Silvia Zanchi Erhardt Barth Monica Gori Unit for Visually Impaired People Istituto Italiano di Tecnologia Genova Italy Dept. of Informatics Bioengineering Robotics and Systems Engineering Universita degli studi di Genova Genova Italy Institute of Neuro- and Bioinformatics University of Luebeck Luebeck Germany Pattern Recognition Company GmbH Luebeck Germany

ISBN: (数字)9798350307993

ISBN: (纸本)9798350308006

Moving through space involves different sensory cues coming from the environment. Previous works show that auditory cues are used in association with other sensory inputs to maintain balance. Moreover, testing spatial hearing under adverse conditions (e.g., eyes closed) provides additional insights into how the absence of one sensory modality could affect self-motion perception. This work aims to design an innovative approach combining kinematic methods and machine learning algorithms to increase the accuracy of a widely used clinical test (Fukuda-Unterberger stepping test). Thanks to the present protocol, we have quantified motor parameters (e.g., linear displacement, angular displacement, and angle of rotation), detecting variations between different audio conditions and age groups. The first hypothesis is to find an advantage in postural control with the use of an auditory cue, providing a better understanding of the interconnection between hearing and the vestibular organs. The second hypothesis is to discriminate motor test performance between different age groups, in line with the progressive vestibular deterioration due to age.

关键词： Protocols Machine learning algorithms Accuracy Auditory system Machine learning Kinematics Aging

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NeBULA: A Standardized Protocol for the Benchmarking of Robotic-based Upper Limb Neurorehabilitation

NeBULA: A Standardized Protocol for the Benchmarking of Robo...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： F. Garro E. Fenoglio I. Forsiuk M. Canepa M. Mozzon L. De Michieli S. Buccelli M. Chiappalone M. Semprini Istituto Italiano di Tecnologia Rehab Technologies Genoa Italy Dept. of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy The Open University Affiliated Research Centre at Istituto Italiano di Tecnologia (ARC@IIT) Genoa Italy

The use of robotic technologies in neurorehabilitation is growing, because they allow highly repeatable exercise protocols and patient-tailored therapies. However, there is a lack of objective methods for assessing these technologies, which makes it difficult to determine their value in rehabilitation settings. While there exist many outcome measurements for motor assessment from a clinical standpoint (such as the Fugl-Meyer scale), the evaluation of performance and clinical benefits of technology for rehabilitation still lacks a standardized approach from a technical *** this work, we describe NeBULA (Neuromechanical Biomarkers for Upper Limb Assessment), a benchmarking platform for evaluating robotic technology for upper limb neurorehabilitation. By utilizing standardized neuromechanical biomarkers, NeBULA aims at providing a groundwork for assessing and comparing neurorehabilitation robots. We describe its implementation and preliminary results assessing a novel upper limb *** Relevance— Standardized evaluation of neurorehabilitation robots can lead to better patient outcomes, optimizing resources by identifying the most effective technology and by boosting their use in clinical practice. This would provide quantitative and objective information to complement clinical motor evaluation – preventing suboptimal treatments and ensuring that patients receive personalized care. It can also facilitate the transfer of technologyto clinics, identifying the most promising ones for further investment and research.

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Ensuring Safety for UAVs Through Event-Triggered Predictive Control

Ensuring Safety for UAVs Through Event-Triggered Predictive ...

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Mediterranean Conference on Control and Automation (MED)

作者： Sotirios N. Aspragkathos George C. Karras Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens Athens Greece Dept. of Informatics and Telecommunications University of Thessaly Lamia Greece Engineering Division and Center for AI & Robotics (CAIR) New York University Abu Dhabi UAE

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

This paper presents a control system for un-manned aerial vehicles (UAVs) that track deformable objects. Using Event-Triggered (ET) principles and Image Moments-Based Nonlinear Model Predictive Control (NMPC), the suggested approach improves flexibility by triggering control changes in response to specific occurrences. The incorporation of Barrier Functions (BFs) enforces safety requirements, which are critical for negotiating uncertain terrains. The framework's implementation and testing on a UAV tracking deformable coastlines are intended to demonstrate its effectiveness in adapting to dynamic situations while adhering to safety limitations.

关键词： Coastlines Target tracking Streaming media Aerodynamics Visual servoing Safety Vehicle dynamics

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An NMPC Framework for Tracking and Releasing a Cable-suspended Load to a Ground Target Using a Multirotor UAV

An NMPC Framework for Tracking and Releasing a Cable-suspend...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Fotis Panetsos George C. Karras Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens Athens Greece Dept. of Informatics and Telecommunications University of Thessaly Lamia Greece Center of AI & Robotics (CAIR) New York University Abu Dhabi

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this work, we present a nonlinear Model Predictive Control (NMPC) scheme for tracking a ground target using a multirotor with a cable-suspended load. The NMPC framework relies on the dynamic model of the UAV with the suspended load and, hence, an estimate of the load state is obtained by fusing the measurements of a downward-facing camera and a load cell with an Unscented Kalman Filter (UKF). Additionally, since the NMPC relies on the future behavior of the system, the trajectory of the ground target throughout the predicted time horizon of the NMPC, is required. Towards this direction, Bézier curves are employed in order to predict the future trajectory of the target, which moves in an arbitrary way. The ultimate goal of the proposed framework is to release the suspended load to the ground target and, consequently, a condition is checked at each time instant that triggers the opening of a gripper, located at the lower edge of the cable. The performance of the proposed control scheme is experimentally validated using an octorotor.

关键词： Target tracking Autonomous aerial vehicles Cameras Robot sensing systems Trajectory Grippers Vehicle dynamics

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Carrying the uncarriable: a deformation-agnostic and human-cooperative framework for unwieldy objects using multiple robots

arXiv

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arXiv 2022年

作者： Sirintuna, Doganay Ozdamar, Idil Ajoudani, Arash Human-Robot Interfaces and Interaction Laboratory Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy

— This manuscript introduces an object deformability-agnostic framework for co-carrying tasks that are shared between a person and multiple robots. Our approach allows the full control of the co-carrying trajectories by the person while sharing the load with multiple robots depending on the size and the weight of the object. This is achieved by merging the haptic information transferred through the object and the human motion information obtained from a motion capture system. One important advantage of the framework is that no strict internal communication is required between the robots, regardless of the object size and deformation characteristics. We validate the framework with two challenging real-world scenarios: co-transportation of a wooden rigid closet and a bulky box on top of forklift moving straps, with the latter characterizing deformable objects. In order to evaluate the generalizability of the proposed framework, a heterogenous team of two mobile manipulators that consist of an Omni-directional mobile base and a collaborative robotic arm with different DoFs is chosen for the experiments. The qualitative comparison between our controller and the baseline controller (i.e., an admittance controller) during these experiments demonstrated the effectiveness of the proposed framework especially when co-carrying deformable objects. Furthermore, we believe that the performance of our framework during the experiment with the lifting straps offers a promising solution for the co-transportation of bulky and ungraspable objects. Copyright © 2022, The Authors. All rights reserved.

关键词： Controllers

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Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection

arXiv

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arXiv 2023年

作者： Molina-Coronado, Borja Ruggia, Antonio Mori, Usue Merlo, Alessio Mendiburu, Alexander Miguel-Alonso, Jose The Dept. of Computer Architecture and Technology University of the Basque Country UPV/EHU Donostia Spain The Dept. of Computer Science and Artificial Intelligence University of the Basque Country UPV/EHU Donostia Spain The Dept. of Informatics Bioengineering Robotics and Sytems Engineering University of Genoa Genoa Italy The CASD - Centre for Advanced Defense Studies Rome Italy

Malware authors have seen obfuscation as the mean to bypass malware detectors based on static analysis features. For Android, several studies have confirmed that many anti-malware products are easily evaded with simple program transformations. As opposed to these works, ML detection proposals for Android leveraging static analysis features have also been proposed as obfuscation-resilient. Therefore, it needs to be determined to what extent the use of a specific obfuscation strategy or tool poses a risk for the validity of ML malware detectors for Android based on static analysis features. To shed some light in this regard, in this article we assess the impact of specific obfuscation techniques on common features extracted using static analysis and determine whether the changes are significant enough to undermine the effectiveness of ML malware detectors that rely on these features. The experimental results suggest that obfuscation techniques affect all static analysis features to varying degrees across different tools. However, certain features retain their validity for ML malware detection even in the presence of obfuscation. Based on these findings, we propose a ML malware detector for Android that is robust against obfuscation and outperforms current state-of-the-art detectors. © 2023, CC BY-NC-SA.

关键词： Static analysis

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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robotics, engineering, Science, and Technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

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Improving Obstacle Awareness to Enhance Interaction in Virtual Reality

Improving Obstacle Awareness to Enhance Interaction in Virtu...

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IEEE Annual International Symposium Virtual Reality

作者： Ivan Valentini Giorgio Ballestin Chiara Bassano Fabio Solari Manuela Chessa Dept. of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Italy

ISBN: (数字)9781728156088

ISBN: (纸本)9781728156095

Currently, immersive virtual reality is experienced through head-mounted displays while the user is physically present into a real, cluttered environment. This causes the problem of avoiding dangerous collisions with obstacles in the real environment that are invisible to the user, and also hampers the interaction with real objects. Following the augmented virtuality paradigm, these obstacles should be embedded into the virtual environment. Thus, there is the need of knowing the 3D structure of the real environment to align it with the virtual one. In this paper, we present a method to create a virtual scenario composed of virtual objects having the same spatial occupancy of the corresponding real ones. The real scene is scanned to detect the position and bounding box of objects and obstacles, then virtual elements having similar spatial properties are added to the virtual scene. Two different real environment structure detection and clustering techniques are described and compared, both quantitatively and by considering users’ sense of presence with respect to the standard Chaperone technique. Our results show that the method is a good solution to maintain the real environment awareness while keeping an high level of immersivity and sense of presence.

关键词： Three-dimensional displays Virtual environments Solid modeling Computational modeling Transmission line matrix methods Resists

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