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7th Scientific School: Dynamics of Complex Networks and their Applications, DCNA 2023

作者： Ibrahim, Sinan Khusainov, Ramil Jnadi, Ali Ahsan Kazmi, S.M. Innopolis University Institute of Robotics and Computer Vision Russia Innopolis University Center for Technologies in Robotics and Mechatronics Components Russia Computer Science and Creative Technologies Bristol United Kingdom

ISBN: (纸本)9798350305746

There is a burgeoning interest in the field of Reinforcement Learning (RL) across various domains, including robotics. Traditional control approaches for robotic systems, such as semi-definite programming (SDP) or mixed integer programming (MIP), typically rely on the assumption of a known and deterministic model of the environment. In contrast, this study aims to introduce a novel RL method for planning the reward function specifically tailored for underactuated robotic systems with parameter uncertainty. We propose a method with a single RL agent to address the challenge of swing up and balance of a Pendubot system with uncertain parameters. The ultimate objective is to enhance the system's ability to adapt and perform reliably in the face of varying uncertainties. © 2023 IEEE.

关键词： Reinforcement learning

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Convolutional Neural Network and Adversarial Autoencoder in EEG images classification 5

Convolutional Neural Network and Adversarial Autoencoder in ...

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5th Scientific School on Dynamics of Complex Networks and their Applications, DCNA 2021

作者： Nasybullin, Albert Kurkin, Semen Faculty of Computer Science and Engineering Innopolis University Innopolis Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781665442824

In this paper, we consider applying computer vision algorithms for the classification problem one faces in neuroscience during EEG data analysis. Our approach is to apply a combination of computer vision and neural network methods to solve human brain activity classification problems during hand movement. We pre-processed raw EEG signals and generated 2D EEG topograms. Later, we developed supervised and semi-supervised neural networks to classify different motor cortex activities. © 2021 IEEE

关键词： Computer vision

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Saratov Fall Meeting 2020 - Computations and Data Analysis: From Molecular Processes to Brain Functions

作者： Frolov, Nikita Pitsik, Elena Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis420500 Russia

ISBN: (数字)9781510645332

ISBN: (纸本)9781510645325

Healthy aging affects structural and neurochemical properties of the human brain neural network. It also changes the brain functioning via the transformation of neural interactions both within and between functionally distinct brain areas. The age-related degradation of the brain functioning is evident on the behavioral level in terms of the decline in reaction time, low ability to execute and control complex motor actions, weak flexibility in learning new skills. In this paper we apply functional connectivity analysis to reveal the age-related changes in the integrative brain dynamic during the motor initiation before the dominant hand movements accompanied. Analyzing the whole-scalp electroencephalography (EEG) signals on the sensor level, we find higher theta-band coupling in the ipsilateral hemisphere. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Electroencephalography

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How Long short-term memory artificial neural network, synthetic data, and fine-tuning improve the classification of raw EEG data 6

How Long short-term memory artificial neural network, synthe...

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6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022

作者： Nasybullin, Albert Maksimenko, Vladimir Kurkin, Semen Innopolis University Laboratory of Data Analysis and Bioinformatics Center for Artificial Intelligence Innopolis Russia Innopolis University Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis Russia

ISBN: (数字)9781665461740

ISBN: (纸本)9781665461740

In this paper, we discuss a Machine Learning pipeline for the classification of EEG data. We propose a combination of synthetic data generation, long short-term memory artificial neural network (LSTM), and fine-tuning to solve classification problems for experiments with implicit visual stimuli, such as the Necker cube with different levels of ambiguity. The developed approach increased the quality of the classification model of raw EEG data. © 2022 IEEE.

关键词： Classification (of information)

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Wireless personal training tracker for sports shooting 5

Wireless personal training tracker for sports shooting

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5th Scientific School on Dynamics of Complex Networks and their Applications, DCNA 2021

作者： Antipov, Vladimir Badarin, Artem Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Lobachevsky University Nizhny Novgorod Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia

ISBN: (纸本)9781665442824

The article describes the process of developing a wireless software arrapat complex for measuring and logging various aspects of sports shooting training. The purpose of the development is to optimize and personalize the training process. This paper proposes an approach that allows synchronization up to 1 ms over a wireless network. As well as a method of writing a large amount of this on a microSD flash drive with minimal latency. © 2021 IEEE

关键词： Sports

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Customizable and Flexible Pressure Sensor Matrix 5

Customizable and Flexible Pressure Sensor Matrix

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5th Scientific School on Dynamics of Complex Networks and their Applications, DCNA 2021

作者： Antipov, Vladimir Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Lobachevsky University Nizhny Novgorod Russia

ISBN: (纸本)9781665442824

The paper presents a method of creating and manufacturing customizable, deformable pressure sensor matrix. The purpose of the development is creating and implementing a variety of matrix sensors with integrated electronics and software to determine the distributed pressure on different types of surfaces, as well as further use of this sensor in medical, robotics and sports. Experimental studies of the individual components and the overall sensor error were conducted. As a result of the work, the developed experimental sample was investigated, a flexible metallized base for the new sensor was developed, and also the board of onboard electronics for processing of the sensor matrix was designed and manufactured. © 2021 IEEE

关键词： Pressure sensors

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Investigation of complex nonlinear processes in systems with intense relativistic electron beams 3

Investigation of complex nonlinear processes in systems with...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Kurkin, Semen Neuroscience and Cognitive Techology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Saratov State University Saratov Russia

ISBN: (纸本)9781728124704

The following novel schemes of relativistic generators with virtual cathode were proposed and investigated in terms of nonlinear dynamics analysis, enhancing output power, efficiency and generation frequency: multibeam vircator, vircator with elliptical resonator, vircator with photonic crystal. The carried-out analysis and obtained results have shown efficiency of the proposed vircator schemes. © 2019 IEEE.

关键词： Photonic crystals

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Chimera-like state in ensemble of bistable neurons

Chimera-like state in ensemble of bistable neurons

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2020 International Conference Nonlinearity, Information and robotics, NIR 2020

作者： Andreev, Andrey Frolov, Nikita Alexandrova, Natalija Chaban, Marija Innopolis University Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis Russia Saratov State University Faculty of Information Technologies Saratov Russia

ISBN: (纸本)9781728187631

We investigate the nonlinear dynamics of a neural network. As a model of a neuron, we use Hodgkin-Huxley mathematical model. We choose the neuron's parameters corresponding to a bistable region in which both fixed point and limit cycle are coexisting. We discover that depending on external current and coupling strength we can achieve a chimera-like state when one part of the neurons is in the resting state, while the other one is in the oscillatory regime in a certain area of coupling strength and external current amplitude. © 2020 IEEE.

关键词： Neurons

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On the movement of center-pivot irrigation machine for processing non-circeular fields 3

On the movement of center-pivot irrigation machine for proce...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Lepetukhin, Konstantin Yu. Miroshkina, Maria V. Platonov, Vitaliy N. Maloletov, Alexander V. Briskin, Eugene S. Department of Theoretical Mechanics Volgograd State Technikal University Volgograd Russia Center for Technologies in Robotics and Mechatronics Components University Innopolis Innopolis Russia

The movement of center-pivot irrigation machine as group of linked mobile robots is considered. Variants of increasing and decreasing radius of movement for mobile towers are presented. The algorithms needed to get to... 详细信息

ISBN: (纸本)9781728124704

关键词： Mobile robots

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Interactive Industrial Robot Programming based on Mixed Reality and Full Hand Tracking

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IFAC-PapersOnLine 2022年第10期55卷 2791-2796页

作者： Mikhail Ostanin Stanislav Zaitsev Adelia Sabirova Alexandr Klimchik Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

The paper show a state-of-the-art approach for programming industrial robotics manipulator via mixed reality holographic interface. In mixed reality, we implement basic functionality for robot programming: setting up the base and tool frames, setting the sequence of Cartesian poses and Joint positions for robot motion, robot movements simulation. The software developed is based on Unity, ROS, and MoveIt frameworks. We compared cursor-based interface (Microsoft HoloLens 1) and full hand tracking (Microsoft HoloLens 2 and Oculus Quest 2) functionalities for interactive robot programming. We tested our approach on the UR10e collaborative robot in the virtual scene and real environment. The full hand tracking human-robot interaction approach improves the setup of Cartesian and Joints robot goals in respect to cursor based interaction.

关键词： human-robot interaction mixed reality industrial robots hand tracking

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