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111 results on '"Greitans, Modris"'

1. Automated Vehicle Platform with Connected Driving Capabilities

Author

Teikmanis, Oskars, Levinskis, Aleksandrs, Mackus, Andris Ivars, Rušiņš, Artis, Elkenawy, Amr, Tropa, Marta, and Greitans, Modris

Subjects
Computer Science - Robotics
Abstract

Augmenting automated vehicles to wirelessly detect and respond to external events before they are detectable by onboard sensors is crucial for developing context-aware driving strategies. To this end, we present an automated vehicle platform, designed with connectivity, ease of use and modularity in mind, both in hardware and software. It is based on the Kia Soul EV with a modified version of the Open-Source Car Control (OSCC) drive-by-wire module, uses the open-source Robot Operating System (ROS and ROS 2) in its software architecture, and provides a straightforward solution for transitioning from simulations to real-world tests. We demonstrate the effectiveness of the platform through a synchronised driving test, where sensor data is exchanged wirelessly, and a model-predictive controller is used to actuate the automated vehicle., Comment: 8 pages, 8 figures. Accepted to the 2023 IEEE International Conference on Intelligent Transportation Systems (ITSC)

Published
2023

4. Method for Muscle Fatigue Detection Using Inertial Sensors

Author

Banga, Beāte, Katashev, Alexei, Greitāns, Modris, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Dekhtyar, Yuri, editor, and Saknite, Inga, editor

Published
2023
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5. Synthetic Data of Randomly Piled, Similar Objects for Deep Learning-Based Object Detection

Author

Arents, Janis, Lesser, Bernd, Bizuns, Andis, Kadikis, Roberts, Buls, Elvijs, Greitans, Modris, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sclaroff, Stan, editor, Distante, Cosimo, editor, Leo, Marco, editor, Farinella, Giovanni M., editor, and Tombari, Federico, editor

Published
2022
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8. A Vision-Based Micro-Manipulation System

Author

Vismanis, Oskars, primary, Arents, Janis, additional, Subačiūtė-Žemaitienė, Jurga, additional, Bučinskas, Vytautas, additional, Dzedzickis, Andrius, additional, Patel, Brijesh, additional, Tung, Wei-Cheng, additional, Lin, Po-Ting, additional, and Greitans, Modris, additional

Published
2023
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15. Construction and benchmark of an autonomous tracked mobile robot system

Author

Ahluwalia, Vaibhav, Arents, Janis, Oraby, Aly, and Greitans, Modris

Subjects
General Medicine
Abstract

Robots require a certain set of skills to perceive and analyse the environment and act accordingly. For tracked mobile robots getting good odometry data from sensory information is a challenging key prerequisite to perform in an unstructured dynamic environment, thus an essential issue in the tracked mobile robotics domain. In this article, we construct a ROS-based tracked mobile robot system taking the Jaguar V4 mobile robot as the base platform. On which several visual odometry solutions based on different cameras and methods (Intel RealSense T265, Zed camera, RTAB-Map RGBD) are integrated and benchmark comparison is performed. Analysis of new challenges faced by different methods while applied on a tracked vehicle as well as recommendations and conclusions are presented. Intel RealSense T265 solution proved to perform well in uncertain conditions which involves bounded vibrations and low lighting conditions with low latency, which result in good map generation. Further evaluations with a path planning algorithm and Intel RealSense T265 were conducted to test the effect of the robot’s motion profiles on odometry data accuracy.

Published
2022
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17. Designing and controlling a self-balancing platform mechanism based on 3-RCC spherical parallel manipulator

Author

Chen, Yen Jung, Tung, Wei-Cheng, Lee, Wei-Rui, Patel, Brijesh, Bučinskas, Vytautas, Greitans, Modris, Lin, Po Ting, Chen, Yen Jung, Tung, Wei-Cheng, Lee, Wei-Rui, Patel, Brijesh, Bučinskas, Vytautas, Greitans, Modris, and Lin, Po Ting

Abstract

Motion control platforms have various applications in the manufacturing and automation industries. Different literature provides multiple issues related to the kinematics and dynamics of self-guided robots for transportation regarding platform balancing. Self-balancing platforms are utilized in many deliveries, stabilization, and transportation systems, and they are especially well suited for outdoor activities when the ground surface is not flat or structured. This paper describes developing a control technique for a self-balancing platform using the 3-RCC spherical parallel manipulator. This mechanism was designed to support an AGV (Automated Guided Vehicle) for transporting and lifting heavy weights for industrial applications. The AGV carries a robotic arm on top for different tasks. When the AGV encounters a steep slope or a rough surface, the AGV tilts, and the robotic arm’s performance is significantly affected. So, this study gives a solution to avoid these circumstances with a novel approach for the platform’s self-balancing mechanism consisting of a 3-RCC spherical parallel manipulator. Real-time stabilization and kinematics analysis methods are used to achieve the self-balancing system of the platform. When both methods are observed through different tilting angles for automation stability, Kinematic analysis performs more efficiently with less time duration when compared with the real-time stabilization method.

Published
2023

18. Supplementation of synthetic object replicas for increasing precision of microrobot trajectory keypoints

Author

Laizans, Modris, Arents, Janis, Vismanis, Oskars, Bučinskas, Vytautas, Dzedzickis, Andrius, Greitans, Modris, Laizans, Modris, Arents, Janis, Vismanis, Oskars, Bučinskas, Vytautas, Dzedzickis, Andrius, and Greitans, Modris

Abstract

Artificial neural networks are becoming more popular with the development of artificial intelligence. These networks require large amounts of data to function effectively, especially in the field of computer vision. The quality of an object detector is primarily determined by its architecture, but the quality of the data it uses is also important. In this study, we explore the use of novel data set enhancement technique to improve the performance of the YOLOv5 object detector. Overall, we investigate three methods: first, a novel approach using synthetic object replicas to augment the existing real data set without changing the size of the data set; second - rotation augmentation data set propagating technique and their symbiosis, third, only one required class is supplemented. The solution proposed in this article improves the data set with a help of supplementation and augmentation. Lower the influence of the imbalanced data sets by data supplementation with synthetic yeast cell replicas. We also determine the average supplementation values for the data set to determine how many percent of the data set is most effective for the supplementation.

Published
2023

20. Processing of Palm Print and Blood Vessel Images for Multimodal Biometrics

Author

Fuksis, Rihards, Greitans, Modris, Pudzs, Mihails, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Vielhauer, Claus, editor, Dittmann, Jana, editor, Drygajlo, Andrzej, editor, Juul, Niels Christian, editor, and Fairhurst, Michael C., editor

Published
2011
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23. Designing and controlling a self-balancing platform mechanism based on 3-RCC spherical parallel manipulator.

Author

Yen Jung Chen, Wei-Cheng Tung, Wei-Rui Lee, Patel, Brijesh, Bučinskas, Vytautas, Greitans, Modris, and Po Ting Lin

Subjects
PARALLEL robots, MANIPULATORS (Machinery), ROBOT dynamics, ROUGH surfaces, OUTDOOR recreation, AUTOMATION
Abstract

Motion control platforms have various applications in the manufacturing and automation industries. Different literature provides multiple issues related to the kinematics and dynamics of self-guided robots for transportation regarding platform balancing. Self-balancing platforms are utilized in many deliveries, stabilization, and transportation systems, and they are especially well suited for outdoor activities when the ground surface is not flat or structured. This paper describes developing a control technique for a self-balancing platform using the 3-RCC spherical parallel manipulator. This mechanism was designed to support an AGV (Automated Guided Vehicle) for transporting and lifting heavy weights for industrial applications. The AGV carries a robotic arm on top for different tasks. When the AGV encounters a steep slope or a rough surface, the AGV tilts, and the robotic arm's performance is significantly affected. So, this study gives a solution to avoid these circumstances with a novel approach for the platform's self-balancing mechanism consisting of a 3-RCC spherical parallel manipulator. Real-time stabilization and kinematics analysis methods are used to achieve the self-balancing system of the platform. When both methods are observed through different tilting angles for automation stability, Kinematic analysis performs more efficiently with less time duration when compared with the real-time stabilization method. [ABSTRACT FROM AUTHOR]

Published
2023
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25. Synthetic Data of Randomly Piled, Similar Objects for Deep Learning-Based Object Detection

Author

Arents Janis, Lesser Bernd, Bizuns Andis, Kadikis Roberts, Buls Elvijs, and Greitans Modris

Subjects
Synthetic data, Deep learning, Object detection
Abstract

Currently, the best object detection results are achieved by supervised deep learning methods, however, these methods depend on annotated training data. With the synthetic data generation approach, we intend to mimic the real data characteristics and diversify the dataset by a systematic rendering of highly realistic synthetic pictures. We systematically explore how different combinations and portions of real and synthetic datasets affect object detectors performance. The developed synthetic data generation framework shows promising results in deep learning-based object detection tasks and can supplement real data when the variety of real training data is insufficient. However, when synthetic data ratio increases over real data ratio, a decrease in average precision can be observed, which has the most affect on 0.75-0.95 IoU threshold range.

Published
2022

26. Smart Industrial Robot Control Trends, Challenges and OpportunitiesWithin Manufacturing

Author

Arents Janis and Greitans Modris

Subjects
smart industrial robots, cognitive robotics, computer vision, reinforcement learning, imitation learning, synthetic data, simulation, smart manufacturing, future factories, artificial intelligence
Abstract

Industrial robots and associated control methods are continuously developing. With the recent progress in the field of artificial intelligence, new perspectives in industrial robot control strategies have emerged, and prospects towards cognitive robots have arisen. AI-based robotic systems are strongly becoming one of the main areas of focus, as flexibility and deep understanding of complex manufacturing processes are becoming the key advantage to raise competitiveness. This review first expresses the significance of smart industrial robot control in manufacturing towards future factories by listing the needs, requirements and introducing the envisioned concept of smart industrial robots. Secondly, the current trends that are based on different learning strategies and methods are explored. Current computer-vision, deep reinforcement learning and imitation learning based robot control approaches and possible applications in manufacturing are investigated. Gaps, challenges, limitations and open issues are identified along the way.

Published
2022

32. Wearable Smart Sensing platform for environmental and health monitoring: the Convergence project

Author

Saoutieff, Elise, Polichetti, Tiziana, Jouanet, Laurent, Faucon, Adrien, Vidal, Audrey, Pereira, Alexandre, Boisseau, Sébastien, Ernst, Thomas, Miglietta, Maria Lucia, Alfano, Brigida, Massera, Ettore, de Vito, Saverio, Bui, Do Hanh Ngan, Benech, Philippe, Vuong, Tan-Phu, Moldovan, Carmen, Danlee, Yann, Walewyns, Thomas, Petre, Sylvain, Flandre, Denis, Ancans, Armands, Greitans, Modris, Ionescu, Adrian M., Département Systèmes (DSYS), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), ENEA C.R. Portici, Department for Sustainability, Portici, 00196 Naples, Italy, Laboratoire d'Innovation pour les Technologies des Energies Nouvelles et les nanomatériaux (LITEN), Institut National de L'Energie Solaire (INES), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Institut de Microélectronique, Electromagnétisme et Photonique - Laboratoire d'Hyperfréquences et Caractérisation (IMEP-LAHC), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), National Institute for Research and Development in Microtechnologies (IMT-Bucharest), Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), Université Catholique de Louvain = Catholic University of Louvain (UCL), Institute of Electronics and Computer Science, University of Latvia (LU), Ecole Polytechnique Fédérale de Lausanne (EPFL), and FLAG-ERA JTC 2016

Subjects
autonomous sensing platform, wearable electronics, NOx sensor, health monitoring, CO sensor, environment monitoring, integration, [PHYS.PHYS.PHYS-CHEM-PH]Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph], [SDE.ES]Environmental Sciences/Environmental and Society, low-power consumption, Internet of Things (IoT), [SPI.TRON]Engineering Sciences [physics]/Electronics
Abstract

International audience; The low-power sensing platform proposed by the Convergence project is foreseen as a wireless, low-power and multifunctional wearable system empowered by energy-efficient technologies. This will allow meeting the strict demands of life-style and healthcare applications in terms of autonomy for quasi-continuous collection of data for early-detection strategies. The system is compatible with different kinds of sensors, able to monitor not only health indicators of individual person (physical activity, core body temperature and biomarkers) but also the environment with chemical composition of the ambient air (NOx, COx, NHx particles) returning meaningful information on his/her exposure to dangerous (safety) or pollutant agents. In this article, we introduce the specifications and the design of the low-power sensing platform and the different sensors developed in the project, with a particular focus on pollutant sensing capabilities and specifically on NO2 sensor based on graphene and CO sensor based on polyaniline ink.

Published
2021
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33. A Wearable Low-Power Sensing Platform for Environmental and Health Monitoring: The Convergence Project

Author

UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique, Saoutieff, Elise, Polichetti, Tiziana, Jouanet, Laurent, Faucon, Adrien, Vidal, Audrey, Pereira, Alexandre, Boisseau, Sébastien, Ernst, Thomas, Miglietta, Maria Lucia, Alfano, Brigida, Massera, Ettore, De Vito, Saverio, Bui, Do Hanh Ngan, Benech, Philippe, Vuong, Tan-Phu, Moldovan, Carmen, Danlée, Yann, Walewyns, Thomas, Pétré, Sylvain, Flandre, Denis, Ancans, Armands, Greitans, Modris, Ionescu, Adrian M., UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique, Saoutieff, Elise, Polichetti, Tiziana, Jouanet, Laurent, Faucon, Adrien, Vidal, Audrey, Pereira, Alexandre, Boisseau, Sébastien, Ernst, Thomas, Miglietta, Maria Lucia, Alfano, Brigida, Massera, Ettore, De Vito, Saverio, Bui, Do Hanh Ngan, Benech, Philippe, Vuong, Tan-Phu, Moldovan, Carmen, Danlée, Yann, Walewyns, Thomas, Pétré, Sylvain, Flandre, Denis, Ancans, Armands, Greitans, Modris, and Ionescu, Adrian M.

Abstract

The low-power sensing platform proposed by the Convergence project is foreseen as a wireless, low-power and multifunctional wearable system empowered by energy-efficient technologies. This will allow meeting the strict demands of life-style and healthcare applications in terms of autonomy for quasi-continuous collection of data for early-detection strategies. The system is compatible with different kinds of sensors, able to monitor not only health indicators of individual person (physical activity, core body temperature and biomarkers) but also the environment with chemical composition of the ambient air (NOx, COx, NHx particles) returning meaningful information on his/her exposure to dangerous (safety) or pollutant agents. In this article, we introduce the specifications and the design of the low-power sensing platform and the different sensors developed in the project, with a particular focus on pollutant sensing capabilities and specifically on NO2 sensor based on graphene and CO sensor based on polyaniline ink.

Published
2021

35. A Wearable Low-Power Sensing Platform for Environmental and Health Monitoring: The Convergence Project

Author

Saoutieff, Elise, primary, Polichetti, Tiziana, additional, Jouanet, Laurent, additional, Faucon, Adrien, additional, Vidal, Audrey, additional, Pereira, Alexandre, additional, Boisseau, Sébastien, additional, Ernst, Thomas, additional, Miglietta, Maria Lucia, additional, Alfano, Brigida, additional, Massera, Ettore, additional, De Vito, Saverio, additional, Bui, Do Hanh Ngan, additional, Benech, Philippe, additional, Vuong, Tan-Phu, additional, Moldovan, Carmen, additional, Danlee, Yann, additional, Walewyns, Thomas, additional, Petre, Sylvain, additional, Flandre, Denis, additional, Ancans, Armands, additional, Greitans, Modris, additional, and Ionescu, Adrian M., additional

Published
2021
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39. Sensors platform for health and environmental monitoring

Author

UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique, Saoutieff, Elise, Faucon, Adrien, Boisseau, Sébastien, Ernst, Thomas, Policheti, Tiziana, Miglietta, Maria Lucia, Alfano, Brigida, Massera, Ettore, De Vito, Saverio, Pétré, Sylvain, Walewyns, Thomas, André, Nicolas, Flandre, Denis, Moldovan, Carmen, Dinulescu, Silviu, Greitans, Modris, Romani, Aldo, Workshop Nano2sense, UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique, Saoutieff, Elise, Faucon, Adrien, Boisseau, Sébastien, Ernst, Thomas, Policheti, Tiziana, Miglietta, Maria Lucia, Alfano, Brigida, Massera, Ettore, De Vito, Saverio, Pétré, Sylvain, Walewyns, Thomas, André, Nicolas, Flandre, Denis, Moldovan, Carmen, Dinulescu, Silviu, Greitans, Modris, Romani, Aldo, and Workshop Nano2sense

Abstract

n/a

Published
2018

44. Improved RGB‐D‐T based face recognition

Author

Simón, Marc Oliu, primary, Corneanu, Ciprian, additional, Nasrollahi, Kamal, additional, Nikisins, Olegs, additional, Escalera, Sergio, additional, Sun, Yunlian, additional, Li, Haiqing, additional, Sun, Zhenan, additional, Moeslund, Thomas B., additional, and Greitans, Modris, additional

Published
2016
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50. Signal-dependent sampling and reconstruction method of signals with time-varying bandwidth

Author

Greitans, Modris, Shavelis, Rolands, Torrésani, Bruno, and Laurent Fesquet and Bruno Torrésani

Subjects
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract

The paper describes the sampling method of nonstationary signals with time-varying spectral bandwidth. The reconstruction procedure exploiting the low-pass filter with time-varying cut-off frequency is derived. The filter application in signal reconstruction from its level-crossing samples is shown. The results of computer simulations are presented.

Published
2009

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