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2020 International Conference Nonlinearity, Information and robotics, NIR 2020

作者： Grubov, Vadim Maksimenko, Vladimir Kurkin, Semen Khramova, Marina Aleksandrova, Natalya Hramov, Alexander Center for Technologies in Robotics and Mechatronics Components Innopolis University Neuroscience and Cognitive Technology Lab Russia Saratov State University Faculty of Computer Science Saratov Russia

ISBN: (纸本)9781728187631

We have analyzed EEG signals of children during cognitive load of specific type in order to estimate level of attention during this task. EEG signals were recorded in accordance with proposed design of experiment. For obtained EEG data we have analyzed behavioral characteristics as well as EEG-related characteristics. We have found that behavioural characteristic changes through the task, so may the attention level. We have also found that cognitive task completion is accompanied by appearance of spatial structure-specific distribution of wavelet energy across cortex, which partially changes during completion of the task as well. We believe that changes in attention level are tied to changes in energy distribution, so we suggest this distribution to be used as the marker for attention state estimation. © 2020 IEEE.

关键词： Electroencephalography

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Ground and non-ground separation filter for UAV Lidar point cloud

arXiv

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arXiv 2019年

作者： Prathap, Geesara Fedorenko, Roman Klimchik, Alexandr Center for Technologies in Robotics and Mechatronics Components Innopolis University

This paper proposes a novel approach for separating ground plane and non-ground objects on Lidar 3D point cloud as a filter. It is specially designed for real-time applications on unmanned aerial vehicles and works on sparse Lidar point clouds without preliminary mapping. We use this filter as a crucial component of fast obstacle avoidance system for agriculture drone operating at low altitude. As the first step, a point cloud is transformed into a depth image and then places with high density nearest to the vehicle (local maxima) are identified. Then we merge original depth image with identified locations after maximizing intensities of pixels in which local maxima were found. Next step is to calculate range angle image which represents angles between two consecutive laser beams based on improved depth image. Once a range angle image is constructed, smoothing is applied to reduce the noise. Finally, we find out connected components in the improved depth image while incorporating smoothed range angle image. This allows separating the non-ground objects. The rest of the locations of depth image belong to the ground plane. The filter has been tested on a simulated environment as well as an actual drone and provides real-time performance. We make our source code and dataset available online2. Copyright © 2019, The Authors. All rights reserved.

关键词： Optical radar

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Phase-amplitude coupling between mu- and gamma-waves to carry motor commands 3

Phase-amplitude coupling between mu- and gamma-waves to carr...

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

作者： Chholak, Parth Pisarchik, Alexander N. Kurkin, Semen A. Maksimenko, Vladimir A. Hramov, Alexander E. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

The development of brain computer interfaces, especially the ones related to controlling exoskeletons and neurorehabilitation of stroke patients, strongly relies on our understanding of motor system and its neuronal mechanism. Motor imagery (MI) has turned out to be one of the most popular experimental regimes to study this system. Kinesthetic imagery (KI) is a kind of MI which shares a large portion of its neuronal pathway with real movements, except for having an additional inhibitory mechanism to prevent movement execution. Our magnetoencephalographic (MEG) experiments with ten untrained subjects revealed that this inhibitory control implied local neuronal desynchronization. We found that the motor-related communication between the inferior parietal cortex and the prefrontal cortex was carried out using the mu-frequency range. Additionally, three gamma frequencies were also pinpointed that encode the motor command specifics. Using artificial neural networks (ANNs) we classified left- and right-hand MI which reached maximal accuracy when we included these three gamma frequencies in the input signal for ANN. We suggest that mu-activity acts as a carrier of gamma-activity between inferior and parietal areas utilising phase-amplitude coupling. © 2019 IEEE.

关键词： Neural networks

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Propellerless aquatic robots 23rd

Propellerless aquatic robots

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23rd International Conference on Climbing and Walking Robots and the Support technologies for Mobile Machines, CLAWAR 2020

作者： Klekovkin, Anton V. Mamaev, Ivan S. Vetchanin, Evgeny V. Tenenev, Valentin A. Karavaev, Yury L. Kalashnikov Izhevsk State Technical University Izhevsk Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Udmurt State University Izhevsk Russia

ISBN: (纸本)9781916449046

This paper is devoted to investigations of the motion of the propellerless aquatic robots. There are two models of aquatic robots under consideration that move due to rotation of internal rotors. Mathematical models to describe the motion of the robots are proposed. Experiments with different control actions for fabricated prototypes to verify mathematical models have been conducted. © CLAWAR Association Ltd.

关键词： Robots

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Synchronization in the inhibitory coupled Hodgkin-Huxley neural networks

Synchronization in the inhibitory coupled Hodgkin-Huxley neu...

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

作者： Andreev, Andrei V. Maksimenko, Vladimir A. Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Universitetskaya Str. 1 Innopolis420500 Russia

ISBN: (数字)9781510645332

ISBN: (纸本)9781510645325

We consider two small-world networks of Hodgkin-Huxley neurons interacting via inhibitory coupling. We found that synchronization indices (SI) in both networks oscillate periodically in time, so that time intervals of high SI alternate with time intervals of low SI. Depending on the coupling strength, the two coupled networks can be in the regime of either in-phase or anti-phase synchronization. We suppose that the inherent mechanism behind such a behavior lies in the cognitive resource redistribution between neuronal ensembles of the brain. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Synchronization

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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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EEG features during maintaining a human body balance.

EEG features during maintaining a human body balance.

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Nonlinearity, Information and robotics, (NIR) International Conference

作者： Vladimir Khorev Vadim Grubov Artem Badarin Vladimir Maksimenko Center for technologies in robotics and mechatronics components Innopolis University Russia

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

We have conducted an experiment involving keeping balance on a platform to research the perception of maintaining body posture. The objective of the present work was to characterize the common features of cortical activity during postural control. Regarding the cortical basis of performance differences during unstable conditions, EEG analysis suggest that central-frontal areas may underlie the cortical interaction including oscillations in general, maybe underlie cortical monitoring of changes in postural state of the body. The obtained results show that the neuronal activity in the β-frequency band can be utilized as the neurophysiological marker of the subject's ability to maintain the equilibrium state.

关键词： Training Process control Robot sensing systems Electroencephalography Stability analysis Task analysis Oscillators

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Path planning followed by kinodynamic smoothing for multirotor aerial vehicles (MAVs)

arXiv

引用

arXiv 2020年

作者： Kulathunga, Geesara Prathap Devitt, Dmitry Fedorenko, Roman Savin, Sergei Klimchik, Alexandr Center for Technologies in Robotics and Mechatronics Components Innopolis University Russia

We explore path planning followed by kinodynamic smoothing while ensuring the vehicle dynamics feasibility for MAVs. We have chosen a geometrically based motion planning technique "RRT*" for this purpose. In the proposed technique, we modified original RRT* introducing an adaptive search space and a steering function which help to increase the consistency of the planner. Moreover, we propose multiple RRT* which generates a set of desired paths, provided that the optimal path is selected among them. Then, apply kinodynamic smoothing, which will result in dynamically feasible as well as obstacle-free path. Thereafter, a b spline-based trajectory is generated to maneuver vehicle autonomously in unknown environments. Finally, we have tested the proposed technique in various simulated environments. Copyright © 2020, The Authors. All rights reserved.

关键词： Motion planning

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Real-Time Long Range Trajectory Replanning for MAVs in the Presence of Dynamic Obstacles

Real-Time Long Range Trajectory Replanning for MAVs in the P...

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Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)

作者： Geesara Kulathunga Roman Fedorenko Sergey Kopylov Alexandr Klimehik Center for Technologies in Robotics and Mechatronics Components Innopolis University Russia

ISBN: (数字)9781728198187

ISBN: (纸本)9781728198194

Real-time long-range local planning is a challenging task, especially in the presence of dynamics obstacles. We propose a complete system which is capable of performing the local replanning in real-time. Desired trajectory is needed in the system initialization phase; system starts initializing sub-components of the system including point cloud processor, trajectory estimator and planner. Afterwards, the multi-rotary aerial vehicle starts moving on the given trajectory. When it detects obstacles, it replans the trajectory from the current pose to pre-defined distance incorporating the desired trajectory. Point cloud processor is employed to identify the closest obstacles around the vehicle. For replanning, Rapidly-exploring Random Trees (RRT*) is used with two modifications which allow planning the trajectory in milliseconds scales. Once we replanned the desired path, velocity components(x,y and z) and yaw rate are calculated. Those values are sent to the controller at a constant frequency to maneuver the vehicle autonomously. Finally, we have evaluated each of the components separately and tested the complete system in the simulated and real environments.

关键词： Trajectory Planning Three-dimensional displays Real-time systems Splines (mathematics) Smoothing methods Message systems

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Fast Sampling-based Next-Best-View Exploration Algorithm for a MAV

Fast Sampling-based Next-Best-View Exploration Algorithm for...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Victor Massagué Respall Dmitry Devitt Roman Fedorenko Alexandr Klimchik Center for Technologies in Robotics and Mechatronics Components Innopolis University Russia

In this work, we present a new exploration algorithm for Micro Aerial Vehicles (MAVs). The planner uses a combination of Next-Best-View (NBV) sampling and frontier-based approaches to reduce the impact of finding unexplored areas in large scenarios. For each sampled point, the yaw angle is optimized to maximize the potential gain for mapping. The gain is expressed as a ratio between the exploration objective and the time it would take to reach the pose, thus, balancing the nearby exploration and global coverage. We reduce the gain computation bottleneck in the sampling strategy by managing a dual-map with different resolutions. The planner maintains a history graph, with nodes that indicate regions of interest for map expansion. We demonstrate the abilities of the proposed algorithm with simulations and real-world experiments. The results outperform state-of-the-art methods in exploration time and computational cost.

关键词： Three-dimensional displays Automation Computational modeling Conferences Computational efficiency History

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