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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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Development of Body Rotational Wheeled Robot and its Verification of Effectiveness

Development of Body Rotational Wheeled Robot and its Verific...

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2020 IEEE International Conference on robotics and Automation, ICRA 2020

作者： Sim, Byeong-Seop Kim, Kun-Jung Yu, Kee-Ho Chonbuk National University Aerospace Robotics and Mechatronics Laboratory Jeonju Korea Republic of

ISBN: (纸本)9781728173955

A wheeled robot operating on various terrains such as scattered obstacles and slopes is required to cope with and overcome the driving environment. In this paper, in order to overcome a step-type obstacle and to steadily ascend on the slope, the main body rotation mechanism, which controls the load distribution on the robot wheels was proposed for a wheel-drive robot. By rotating the center of the body mass, the friction/traction force required for climbing step obstacles can be reduced. In the case of slope traveling, the slip can be suppressed, and the traveling ability improved by controlling the load distribution excessively increased on the downhill wheel due to the attitude change of the robot's body. The mechanical effect of the proposed body rotation mechanism was analyzed. In addition, based on the design and manufacture of the robot platform, the effectiveness of the proposed mechanism was convincingly demonstrated by indoor test for step-obstacle climbing and slope-traveling. © 2020 IEEE.

关键词： Wheels

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The Role of Compaction Roller in Defining the Layup Quality and Laminate Porosity in Robotic Fiber Placement

The Role of Compaction Roller in Defining the Layup Quality ...

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International Conference on mechatronics Technology (ICMT)

作者： Mohamed M.A. Ammar Bijan Shirinzadeh Robotics and Mechatronics Research Laboratory Monash University Clayton Australia

ISBN: (纸本)9781665424608

The automated fiber placement has been commonly used to fabricate composite structures with high performance. However, the automated manufacturing process is limited by the developed defects in the final composite components. The current study focuses on the effect of the compaction roller's configurations and stiffness on the manufactured thermoset com-posites. The robotic fiber placement process is applied to fabricate different composite specimens. Several unidirectional and multi-axes specimens have been manufactured using 4 different rollers. The attitude of the compaction roller is also adjusted to be normal and to ensure uniform distribution of the compaction pressure. The surface quality of the manufactured components has been evaluated through image processing and detecting the layup defects. The scanning electron microscopy is used to estimate the change in the material porosity. The samples manufactured using a compliant and perforated roller included defects such as blisters, wrinkles, overlaps, and distortions. Additionally, the material porosity has been significantly improved when using the solid steel roller.

关键词： Scanning electron microscopy Image processing Solids Distortion Compaction Steel Laminates

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Discrete-time model based control of soft manipulator with FBG sensing

Discrete-time model based control of soft manipulator with F...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Enrico Franco Ayhan Aktas Shen Treratanakulchai Arnau Garriga-Casanovas Abdulhamit Donder Ferdinando Rodriguez y Baena Mechanical Engineering Department Mechatronics in Medicine Laboratory Imperial College London London UK Biomedical and Robotics Technology Laboratory Mahidol University Nakon Pathom Thailand Boston Children's Hospital Harvard Medical School USA

In this article we investigate the discrete-time model based control of a planar soft continuum manipulator with proprioceptive sensing provided by fiber Bragg gratings. A control algorithm is designed with a discrete-time energy shaping approach which is extended to account for control-related lag of digital nature. A discrete-time nonlinear observer is employed to estimate the uncertain bending stiffness of the manipulator and to compensate constant matched disturbances. Simulations and experiments demonstrate the effectiveness of the controller compared to a continuous time implementation.

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Simplifying Robot Grasping in Manufacturing with a Teaching Approach based on a Novel User Grasp Metric

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Procedia Computer Science 2024年 232卷 1961-1971页

作者： Matteo Pantano Vladislav Klass Qiaoyue Yang Akhil Sathuluri Daniel Regulin Lucas Janisch Markus Zimmermann Dongheui Lee Technology Department Siemens Aktiengesellschaft D-81739 Munich Germany Human-Centered Assistive Robotics Technical University of Munich D-80333 Munich Germany Laboratory for Product Development and Lightweight Design Technical University of Munich D-85748 Garching Germany Autonomous Systems Technische Universität Wien AT-1040 Vienna Austria Institute of Robotics and Mechatronics German Aerospace Center D-82234 Wessling Germany

The manufacturing industry is undergoing rapid evolution, necessitating flexible and adaptable robots. However, configuring such machines requires technical experts, which are hard to find, especially for small and medium enterprises. Therefore, the process needs to be simplified by allowing non-experts to configure robots. During such configuration, one key aspect is the definition of objects’ grasping poses. The literature proposes deep learning techniques to compute grasping poses automatically and facilitate the process. Nevertheless, practical implementation for inexperienced factory operators can be challenging, especially if task-specific knowledge and constraints should be considered. To overcome this barrier, we propose an approach that facilitates teaching such poses. Our method, employing a novel user grasp metric, combines the operator's initial grasp guess given by a 3D spatial device with a state-of-the-art deep learning algorithm, thus returning reliable grasping poses but simultaneously close to the operator's initial guess. We compare this approach against commercial grasping pose definition interfaces through a user test involving 28 participants and against state-of-the-art deep learning grasp estimators. The results demonstrate a significant improvement in system usability (+24%) and a reduced workload (-16%). Furthermore, our experiments reveal an increased grasp success rate when utilizing the user grasp metric, surpassing state-of-the-art deep learning grasping estimators.

关键词： operator empowerment spatial interaction robotic grasping usability small medium enterprises cobots

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Exploring Neural Networks for Forward Kinematics of the Robotic Arm with Different Length Configurations: A Comparative Analysis

Exploring Neural Networks for Forward Kinematics of the Robo...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Rania Bouzid Jyotindra Narayan Hassène Gritli Higher Institute of Information and Communication Technologies University of Carthage RISC Laboratory (LR16ES07) Borj Cedria Tunisia Department of Mechanical Engineering Mechatronics and Robotics Laboratory Indian Institute of Technology Guwahati Guwahati Assam India Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Tunis Tunisia

Our work investigates the utilization of Artificial Neural Networks (ANNs) to address the complexities associated with Forward Kinematics (FK) problems within the field of robotics. We undertake an extensive comparative analysis to assess how ANNs perform under different circumstances with robotic arms of varying lengths and impact the overall system’s functionality. The training, testing, and validation of ANNs are carried out using MATLAB for a simulated 2-DoF serial robotic arm involving three distinct datasets: fixed step size, random step size, and sinusoidal step size. Three training optimizers, namely Levenberg Marquardt (LM), Bayesian Regularization (BR), and Stochastic Conjugate Gradient (SCG), are considered within the ANN architecture. Based on Mean Square Error (MSE) values, the numerical findings reveal the potential of ANN in estimating forward kinematic solutions of complex robotic manipulators with different arm lengths and reducing computational complexity.

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Online Multi-Contact Feedback Model Predictive Control for Interactive Robotic Tasks

Online Multi-Contact Feedback Model Predictive Control for I...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Seo Wook Han Maged Iskandar Jinoh Lee Min Jun Kim Intelligent Robotic Systems Laboratory Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Institute of Robotics and Mechatronics German Aerospace Center (DLR) Wessling Germany Department of Mechanical Engineering KAIST Daejeon Republic of Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this paper, we propose a model predictive control (MPC) that accomplishes interactive robotic tasks, in which multiple contacts may occur at unknown locations. To address such scenarios, we made an explicit contact feedback loop in the MPC framework. An algorithm called Multi-Contact Particle Filter with Exploration Particle (MCP-EP) is employed to establish real-time feedback of multi-contact information. Then the interaction locations and forces are accommodated in the MPC framework via a spring contact model. Moreover, we achieved real-time control for a 7 degrees of freedom robot without any simplifying assumptions by employing a Differential-Dynamic-Programming algorithm. We achieved 6.8kHz, 1.9kHz, and 1.8kHz update rates of the MPC for 0, 1, and 2 contacts, respectively. This allows the robot to handle unexpected contacts in real time. Real-world experiments show the effectiveness of the proposed method in various scenarios.

关键词： Feedback loop Prediction algorithms Real-time systems Particle filters Task analysis Springs Robots

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Toward Space Exploration on Legs: ISS-to-Earth Teleoperation Experiments with a Quadruped Robot

Toward Space Exploration on Legs: ISS-to-Earth Teleoperation...

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Telepresence, IEEE Conference on

作者： Daniel Seidel Annika Schmidt Xiaozhou Luo Antonin Raffin Luisa Mayershofer Tristan Ehlert Davide Calzolari Milan Hermann Thomas Gumpert Florian Löffl Emiel Den Exter Anne Köpken Rute Luz Adrian Bauer Nesrine Batti Florian Lay Ajithkumar Manaparampil Alin Albu-Schäffer Daniel Leidner Peter Schmaus Thomas Krüger Neal Y. Lii German Aerospace Center (DLR) Institute of Robotics and Mechatronics Wessling Germany TUM School of Computation Information and Technology Technical University of Munich Garching Germany European Space Agency (ESA) Human Robot Interaction Laboratory Noordwijk The Netherlands

ISBN: (数字)9798331528249

ISBN: (纸本)9798331528256

In uneven terrains of lunar and planetary surfaces, a teleoperated legged robot enables the exploration of areas that may be inaccessible to wheeled rovers. The on-going DLR-ESA Surface Avatar technology demonstration mission studies and validates technologies needed to realize the command of a heterogeneous robotic team with various command modalities. In the latest experiments, the crew on-board the International Space Station (ISS) is tasked to command a team of different robots with Scalable Autonomy, meaning they may choose to command the robots through direct control, shared control, or delegate tasks with Supervised Autonomy. One of the robots in the robotic team is DLR’s small quadruped, Bert. Equipped with a robotic arm on its back, also serving as camera mount, Bert can observe its surroundings and pick up small objects. Due to its serial-elastic joints, the hardware is robust to impacts, which is critical for space deployment. Applying adaptive learning strategies, Bert’s gaits can be (re)trained directly on hardware to adapt to different environment and gravity conditions. The quadruped as well as its back-mounted arm can be commanded through direct control by the astronauts via a joystick on-board the ISS. Additionally, simple preset task-level commands complement the user interface to ease the astronauts’ workload. This paper presents the ISS experiments of the first legged robot telecommanded from space. Examining different aspects of Bert’s telerobotic performance as well as the ISS crew feedback, we discuss the feasibility of teleoperated walking robots in space exploration.

关键词： Legged locomotion Telepresence Arms Aerospace electronics User interfaces Hardware Space exploration Quadrupedal robots Robots Telerobotics

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Design and Analysis of a Piezo-based Decoupled 3-DOF (XYθ) Micropositioner with Large Workspace

Design and Analysis of a Piezo-based Decoupled 3-DOF (XYθ) ...

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International Conference on Computer and Information Technology (ICCIT)

作者： Tilok Kumar Das Rifat Shahrear Bijan Shirinzadeh Dept. of Mechanical Engineering Chittagong University of Engineering and Technology (CUET) Chattogram Bangladesh Dept. of Mechanical and Aerospace Engineering Robotics and Mechatronics Research Laboratory Monash University Melbourne Australia

This paper presents a piezo-based compliant planer 3-DOF micropositioning stage for decoupled large workspace of the platform. Three piezoelectric actuators inside three double-stairs bridge-type mechanisms were used to drive the output platform in XYθ directions. A-3PPR type kinematic chain has been oriented parallelly in such a way to have a rotational symmetry about the centroid. Two different types of prismatic flexure joints with a passive rotary flexure joint were utilized in each kinematic chain. The proposed design focused on the redundancy of the cross-axis coupling effect from the other axes during directional movements. To evaluate the performance, Finite Element Analysis (FEA) has been conducted. The decoupled 3-DOF micropositioning stage is able to maintain the maximum parasitic motion of 0.05% and 1.95 % in the Y and θ directions of their respective directional working range. So, the effect of cross-coupling motion during directional movement can be presumed to be less in this case. Further, the FEA results show that the micropositioning stage has a large work envelope of ±271.1 μm × 235 μm × ± 6.0352 mrad. Moreover, the evaluation of the dynamic characteristics predicts that out-of-plane motion will be less likely to occur. Thus, the 3-DOF micropositioning stage can provide a unidirectional decoupled large range of motions.

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Artificial neural network predicts inter-areal functional connectivity

Artificial neural network predicts inter-areal functional co...

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

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

ISBN: (数字)9781510645332

ISBN: (纸本)9781510645325

In the present paper, we introduce an extended machine-learning-based approach to detect inter-areal functional connectivity based on an artificial neural network (ANN). Using the concept of generalized synchronization, we show that the proposed approach is relevant to infer functional dependencies between remote brain areas of interest from multivariate EEG recordings. We verify the ANN-based method to capture the reconfiguration of functional connectivity during motor execution. The proposed model showed good ability to approximate functional relations between the electrical activity of parietal and frontal areas and motor cortex at different stages of motor execution, providing an adequate pattern of functional connectivity network. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Multilayer neural networks

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