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arXiv 2021年

作者： Lobov, Sergey A. Mikhaylov, Alexey N. Berdnikova, Ekaterina S. Makarov, Valeri A. Kazantsev, Victor B. Lobachevsky State University of Nizhny Novgorod Gagarin Ave. 23 Nizhny Novgorod603950 Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Universitetskaya Str. 1 Innopolis420500 Russia Center For Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia Instituto de Matemática Interdisciplinar F. de Ciencias Matemáticas Universidad Complutense de Madrid Madrid28040 Spain

One of the challenges of modern neurosciwence is creating a "living computer" based on neural networks grown in vitro. Such an artificial device is supposed to perform neurocomputational tasks and interact with the environment when embodied in a robot. Recent studies have identified the most critical challenge, the search for a neural network architecture to implement associative learning. This work proposes a model of modular architecture with spiking neural networks connected by unidirectional couplings. We show that the model enables training a neuro-robot according to Pavlovian conditioning. The robot's performance in obstacle avoidance depends on the ratio of the weights in inter-network couplings. We show that besides STDP, critical factors for successful learning are synaptic and neuronal competitions. We use the recently discovered shortest path rule to implement the synaptic competition. This method is ready for experimental testing. Strong inhibitory couplings implement the neuronal competition in the subnetwork responsible for the unconditional response. Empirical testing of this approach requires a technique for growing neural networks with a given ratio of excitatory and inhibitory neurons not available yet. An alternative is building a hybrid system with in vitro neural networks coupled through hardware memristive connections. © 2021, CC BY.

关键词： Neural networks

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On Choosing Structure for a Machine Learning-based Reaction Force Predictor for Walking Robots

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Journal of Physics: Conference Series 2021年第1期1831卷

作者： E Zalyaev S Savin A Salikhzyanov S Golousov Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis 420500 Russia Edge Vision Ltd. Innopolis 420500 Russia Technology Arrival Ltd Banbury London UK

This paper focuses on the topic of contact reaction prediction for walking robots, namely on the analysis of performances on different structures of the machine-learning-based predictors. Predicting reaction forces is important due to the fact that it can allow us to retrieve a simplified model of the contact scenario, as was proposed in the literature preciously. This allows to turn the problem of contact model identification into a data collection and processing problem. In order to do it effectively, both a data compression (feature extraction) and regression strategies might be used. This research provides an analysis of both with respect to the discussed problem.

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Advanced technologies in High Education in Cooperation with High-Tech Companies ⁎

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IFAC-PapersOnLine 2019年第9期52卷 312-317页

作者： Anton A. Pyrkin Alexey A. Bobtsov Alexey A. Vedyakov Sergey V. Shavetov Yuriy S. Andreev Oleg I. Borisov ITMO University Faculty of Control Systems and Robotics 49 Kronverksky Pr. St. Petersburg 197101 Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

The paper discusses advanced educational technologies in control engineering implemented at ITMO university. They are module-based education, project-based bachelor’s degree program and project tracks based on academia-industry collaboration. All of them are oriented on the students needs and aimed to update the educational processes, reduce its bureaucracy and improve its outcome. The positive experience of such initiatives is already confirmed by a number of successful participations of the students in top level world competitions on robotics.

关键词： Education Control education Projects Teaching Industrial control

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Mechanics of compliant serial manipulator composed of dual-triangle segments

arXiv

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arXiv 2020年

作者： Zhao, Wanda Klimchik, Alexandr Pashkevich, Anatol Chablat, Damien UMR CNRS 6004 Ecole Centrale Nantes Nantes France Center Technologies in Robotics and Mechatronics Components Innopolis University Tatarstan Russia UMR CNRS 6004 IMT Atlantique Nantes Nantes France Nantes France

The paper focuses on the mechanics of a compliant serial manipulator composed of new type of dual-triangle elastic segments. Both the analytical and numerical methods were used to find the manipulator stable and unstable equilibrium configurations, as well as to predict corresponding manipulator shapes. The stiffness analysis was carried on for both loaded and unloaded modes, the stiffness matrices were computed using the Virtual Joint Method (VJM). The results demonstrate that either buckling or quasi-buckling phenomenon may occur under the loading, if the manipulator corresponding initial configuration is straight or non-straight one. Relevant simulation results are presented that confirm the theoretical study. Copyright © 2020, The Authors. All rights reserved.

关键词： Buckling

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Chaos and hyperchaos in the chain of quantum coherent elements

Chaos and hyperchaos in the chain of quantum coherent elemen...

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School on Dynamics of Complex Networks and their Application in Intellectual robotics (DCNAIR)

作者： Alexander Balanov Andrey Andreev Mark Fromhold Mark Greenaway Alexander Hramov Weibin Li Vladimir Makarov Alexandre Zagoskin Department of Physics Loughborough University Loughborough United Kingdom Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia School of Physics and Astronomy University of Nottingham Nottingham United Kingdom Department of Theoretical Physics and Quantum Technologies National University of Science and Technology MISIS Moscow Russia

ISBN: (数字)9781728172866

ISBN: (纸本)9781728172873

We study the chain of coupled quantum coherent systems with energy pumping and dissipation. Examples of such systems include the coupled Rydberg atoms with laser driving and spontaneous emission or electromagnetically driven artificial qubits with decoherence and dissipation. We found out that such system is able to demonstrate spontaneous onset of chaotic and even hyperchaotic oscillations, which are characterized by one or several positive Lyapunov exponents. Remarkably, the number of the positive Lyapunov exponents grows with the number of the chain elements. Hence a large chain is able to demonstrate highly irregular behavior. We investigate transition from regular to chaotic behavior and reveal the related instabilities.

关键词： Quantum mechanics Neuroscience Robots mechatronics Chaotic communication Control systems

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Noise-induced artificial intelligence

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Physical Review Research 2022年第4期4卷 043069-043069页

作者： Alex Zhao Anastasia Ermolaeva Ekkehard Ullner Juergen Kurths Susanna Gordleeva Alexey Zaikin Department of Mathematics University College London London WC1E 6BT United Kingdom Department of Neurotechnology Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod 603022 Russia Institute for Complex Systems and Mathematical Biology Institute for Pure and Applied Mathematics and Department of Physics (SUPA) University of Aberdeen Aberdeen AB24 3UE United Kingdom Potsdam Institute for Climate Impact Research Telegraphenberg Potsdam D-14415 Germany World-Class Research Center Digital Biodesign and Personalized Healthcare Sechenov First Moscow State Medical University Moscow 119991 Russia Neuroscience Research Institute of Samara State Medical University Samara 443099 Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis 420500 Russia Institute for Women's Health University College London London WC1E 6BT United Kingdom

We show that unavoidable stochastic fluctuations are not only affecting information processing in a destructive or constructive way, but may even induce conditions necessary for the artificial intelligence itself. In this proof-of-principle paper we consider a model of a neuron-astrocyte network under the influence of multiplicative noise and show that information encoding (loading, storage, and retrieval of information patterns), one of the paradigmatic signatures of intelligent systems, can be induced by stochastic influence and astrocytes. Hence, astrocytes, recently proved to play an important role in memory and cognitive processing in mammalian brains, may play also an important role in the generation of a system's features providing artificial intelligence functions. Hence, one could conclude that intrinsic stochasticity is probably positively utilized by brains, not only to optimize the signal response but also to induce intelligence itself, and one of the key roles, played by astrocytes in information processing, could be dealing with noises.

关键词： Coupled oscillators Dynamics of networks Neuronal dynamics

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Formation of working memory in a spiking neuron network accompanied by astrocytes

arXiv

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arXiv 2020年

作者： Gordleeva, Susanna Yu Tsybina, Yulia A. Krivonosov, Mikhail I. Ivanchenko, Mikhail V. Zaikin, Alexey A. Kazantsev, Victor B. Gorban, Alexander N. Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Moscow Russia Institute for Women’s Health Department of Mathematics University College London London United Kingdom University of Leicester United Kingdom

We propose a biologically plausible computational model of working memory (WM) implemented by the spiking neuron network (SNN) interacting with a network of astrocytes. SNN is modelled by the synaptically coupled Izhikevich neurons with a non-specific architecture connection topology. Astrocytes generating calcium signals are connected by local gap junction diffusive couplings and interact with neurons by chemicals diffused in the extracellular space. Calcium elevations occur in response to the increase of concentration of a neurotransmitter released by spiking neurons when a group of them fire coherently. In turn, gliotransmitters are released by activated astrocytes modulating the strengths of synaptic connections in the corresponding neuronal group. Input information is encoded as two-dimensional patterns of short applied current pulses stimulating neurons. The output is taken from frequencies of transient discharges of corresponding neurons. We show how a set of information patterns with quite significant overlapping areas can be uploaded into the neuron-astrocyte network and stored for several seconds. Information retrieval is organised by the application of a cue pattern representing the one from the memory set distorted by noise. We found that successful retrieval with level of the correlation between recalled pattern and ideal pattern more than 90% is possible for multi-item WM task. Having analysed the dynamical mechanism of WM formation, we discovered that astrocytes operating at a time scale of a dozen of seconds can successfully store traces of neuronal activations corresponding to information patterns. In the retrieval stage, the astrocytic network selectively modulates synaptic connections in SNN leading to the successful recall. Information and dynamical characteristics of the proposed WM model agrees with classical concepts and other WM models. © 2020, CC-BY.

关键词： Neural networks

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Approach of Flow Control Around Unmanned Underwater Robot

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IFAC-PapersOnLine 2018年第30期51卷 452-457页

作者： Galushko, Ilya D. Salmina, Vera A. Gafurov, Salimzhan A. Stadnik, Dmitry M. Samara National Research University Samara443086 Russia Saara National Research University Samara443086 Russia Innopolis University Center for Technologies of Robotics and Mechatronics Components Innopolis420500 Russia

The development of a prototype of an underwater robot with a variable geometry of the body is a major complex task, including a whole series of tasks of a scientific, technical, engineering and applied nature, and the creation of new automatic systems for managing it. The creation of such a robot will ensure its high autonomy and maneuverability. In this paper, the development of a solid model of a biomimetic robot hybrid and AUV with a variable geometry of the hull is presented. Also presented is a basic pneumatic circuit integrated into the robot body, which drives the pneumatic muscles fixed to the ribs of the robot's robust body. The experimental part includes the investigation of the vertical and horizontal components of the deformation of the walls of the shell, depending on the pressure supplied by the pneumatic system to the pneumatic cusps. © 2016

关键词： Robots Biomimetics Geometry Pneumatic control Pneumatic equipment Pneumatics Anisotropic bodies Automatic systems Bio mimetic robot Horizontal components Pneumatic muscle Underwater robotics Underwater robots Variable geometry

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ONLINE ESTIMATION OF TIME-VARYING FREQUENCY OF A SINUSOIDAL SIGNAL ⁎

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IFAC-PapersOnLine 2019年第29期52卷 245-250页

作者： Le Van Tuan Marina Korotina Alexey Bobtsov Stanislav Aranovskiy Anton Pyrkin Faculty of Control Systems and Robotics ITMO University 197101 Saint Petersburg Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia IETR - CentraleSupélec Avenue de la Boulaie 35576 Cesson-Sévigné France

We consider the problem of estimation of a (linearly) time-varying frequency of a sinusoidal signal with unknown phase and magnitude. Such a problem may arise in control design for optical telescopes that makes it interesting from the practical point of view. The existing methods typically use unbounded functions of time that, being multiplying by the input signal, may yield significant noise amplification and poor estimation performance. In contrast, we present a novel approach to the estimation of the linearly varying frequency based on iterative filtering yielding simple linear regression model with a scalar parameter. Illustrative numerical simulations support the theoretical results. We also present a comparison with other known methods.

关键词： dynamic extension mixing persistence excitation parameter estimation least squares

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Application of Enhanced Extended Observer in Station-Keeping of a Quadrotor with Unmeasurable Pitch and Roll Angles ⁎

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IFAC-PapersOnLine 2019年第16期52卷 837-842页

作者： Oleg I. Borisov Anton A. Pyrkin Alberto Isidori ITMO University Faculty of Control Systems and Robotics St. Petersburg Russia Innopolis University Center for Technologies in Robotics and Mechatronics Components Innopolis Russia University of Rome “La Sapienza” Department of Computer Control and Management Engineering “A. Ruberti” Rome Italy

In this paper we provide an example of application of the design of a control law that makes use of an enhanced version of the so-called extended observer. The enhancement in question reposes on the extension of a classical Lemma due to Dayawansa to the case of nonlinear systems whose normal form includes time-varying (and measurable) gains. The presented example concerns a station-keeping problem of a quadrotor with unmeasurable pitch and roll angles.

关键词： Dayawansa’s lemma Robust observers Nonlinear systems High-gain observers Quadrotors

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