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arXiv 2022年

作者： Kulathunga, Geesara Klimchik, Alexandr Center for Technologies in Robotics and Mechatronics Components Innopolis University Russia

In general, optimal motion planning can be performed both locally and globally. In such a planning, the choice in favour of either local or global planning technique mainly depends on whether the environmental conditions are dynamic or static. Hence, the most adequate choice is to use local planning or local planning alongside global planning. When designing optimal motion planning both local and global, the key metrics to bear in mind are execution time, asymptotic optimality, and quick reaction to dynamic obstacles. Such planning approaches can address the aforesaid target metrics more efficiently compared to other approaches such as path planning followed by smoothing. Thus, the foremost objective of this study is to analyse related literature in order to understand how the motion planning, especially trajectory planning, problem is formulated, when being applied for generating optimal trajectories in real-time for Multirotor Aerial Vehicles (MAVs), impacts the listed metrics. As a result of the research, the trajectory planning problem was broken down into a set of subproblems, and the lists of methods for addressing each of the problems were identified and described in detail. Subsequently, the most prominent results from 2010 to 2022 were summarized and presented in the form of a timeline. © 2022, CC BY.

关键词： Model predictive control

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Path Planning Followed by Kinodynamic Smoothing for Multirotor Aerial Vehicles (MAVs)

Path Planning Followed by Kinodynamic Smoothing for Multirot...

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Nonlinearity, Information and robotics, (NIR) International Conference

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

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

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.

关键词： Smoothing methods Planning Trajectory Vehicle dynamics Splines (mathematics) Robots

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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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Real-time long range trajectory replanning for MAVs in the presence of dynamics obstacles

arXiv

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arXiv 2020年

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

—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. Copyright © 2020, The Authors. All rights reserved.

关键词： Polynomial approximation

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Workspace Analysis of Tensegrity Structures with an Iterative Energy-based Algorithm

Workspace Analysis of Tensegrity Structures with an Iterativ...

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Nonlinearity, Information and robotics, (NIR) International Conference

作者： Sergei Savin Oleg Balakhnov Alexandr Klimchik Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

The paper studies the use of energy-based forward and inverse kinematics procedures for calculation of operational space of tensegrity robotics structures. Tensegrity structures are compliant and highly dynamical, which makes them a favorable robotics component for a number of difficult tasks (such as collaborative robotics, space exploration and others), but at the same times make trajectory planning and control highly non-trivial. In the paper it is demonstrated that the studied forward and inverse kinematics methods can be used to find workspaces of tensegrity structures, using six bar structure as an example. It is shown that the method can adjust to the choice of actuated and passive elastic elements, making it a design tool which maps the actuation pattern to the resulting workspace or to the law of change of the rest lengths of the actuated elastic elements.

关键词： Trajectory planning Kinematics Iterative algorithms Trajectory Space exploration Task analysis Robots

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Biomarkers of brain activity for the performance evaluation in the process of solving cognitive tasks 5

Biomarkers of brain activity for the performance evaluation ...

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

作者： Badarin, Artem Smirnov, Nikita Kurkin, Semen 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

In this paper, we analyze the brain activity during the execution by the subject of simple cognitive tasks associated with visual attention and symbol perception. We obtain biomarkers of brain activity in the process of solving cognitive tasks. These biomarkers make it possible to relate the quality and speed of execution of the tasks offered to the subject with the brain’s activity of the cortical network. We use a combination of time-frequency and statistical analysis to calculate activity characteristics. The results obtained can be used to develop neural interfaces for training attention and adjusting the learning process. © 2021 IEEE

关键词： Biomarkers

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Energy-based local forward and inverse kinematics methods for tensegrity robots

Energy-based local forward and inverse kinematics methods fo...

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IEEE International Conference on Robotic Computing (IRC)

作者： Sergei Savin Oleg Balakhnov Alexandr Klimchik Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis

ISBN: (数字)9781728152370

ISBN: (纸本)9781728152387

This paper describes an energy-based forward kinematics method for tensegrity robotics structures. The method can be implemented as a nonlinear optimization procedure and solved with standard optimization algorithms. Based on this result, the paper proposes a local linearization-based approach to inverse kinematics for tensegrity robots, for which a gradient descent-like algorithms is formulated. A preliminary study of the algorithm numerical behavior is given, and examples of the use cases for both forward and inverse kinematics methods are provided. It is shown that the method allows planing trajectories in the Cartesian space for the end effector and discover the desired law of change of the rest lengths of the actuated elastic elements.

关键词： Planing Kinematics Trajectory Quadratic programming Robots Optimization Standards

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Effect of prehistory on the ambiguous stimuli processing in the human brain 5

Effect of prehistory on the ambiguous stimuli processing in ...

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

作者： Kuc, Alexander Neuroscience and Cognitive Technology Lab 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

To model the picture of the external environment, the brain uses data coming from the sensory system. However, it is believed that the brain’s representation of the external environment is formed not only by sensory information, but also by a priori knowledge, the so-called predictions. This work considers how the previous sensory information (sensory prehistory) influences the processing of the current visual stimuli. Bistable images of the Necker cube with varying degrees of ambiguity were used as visual stimuli. We found EEG biomarkers possibly reflecting the effect of prehistory on the brain state and the ongoing stimulus processing. © 2021 IEEE

关键词： Visualization Complex networks Biomarkers Brain modeling Electroencephalography Data models Time factors

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Trajectory tracking for quadrotors: An optimization-based planning followed by controlling approach

Research Square

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Research Square 2021年

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

We present an optimization-based reference trajectory tracking method for quadrotor robots for slow-speed maneuvers. The proposed method uses planning followed by the controlling paradigm. The basic concept of the proposed method is an analogy to Linear Quadratic Gaussian (LQG) in which Nonlinear Model Predictive Control (NMPC) is employed for predicting optimal control policy in each iteration. Multiple-shooting (MS) is suggested over Direct-collocation (DC) for imposing constraints when modelling the NMPC. Incremental Euclidean Distance Transformation Map (EDTM) is constructed for obtaining the closest free distances relative to the predicted trajectory;these distances are considered obstacle constraints. The reference trajectory is generated, ensuring dynamic feasibility. The objective is to minimize the error between the quadrotor’s current pose and the desired reference trajectory pose in each iteration. Finally, we evaluated the proposed method with two other approaches and showed that our proposal is better than those two in terms of reaching the goal without any collision. Additionally, we published a new dataset, which can be used for evaluating the performance of trajectory tracking algorithms. © 2021, CC BY.

关键词： Trajectories

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Quasi-movements as an intermediate type of motion 5

Quasi-movements as an intermediate type of motion

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

作者： Smirnov, Nikita M. Kurkin, Semen 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

This paper discusses the three distinct types of motor activity, namely quasi, real, and imagery. Quasi-motion is voluntary movements that are minimized to the point that finally become undetectable by objective measures. This type of motion is particular from the point of difficulty of classifying it as real or imaginary. In this paper, we are aiming to show it from the sensor- and source-level perspectives. © 2021 IEEE

关键词： Dynamics Complex networks

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