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IEEE-RAS International Conference on Humanoid Robots

作者： Alexander Fabisch Manuela Uliano Dennis Marschner Melvin Laux Johannes Brust Marco Controzzi Robotics Innovation Center DFKI GmbH Bremen Germany The BioRobotics Institute Scuola Superiore Sant’ Anna Pisa Italy Department of Excellence in Robotics & AI Pisa Italy Robotics Research Group University of Bremen Plan-Based Robot Control DFKI GmbH

ISBN: (纸本)9798350309805

Manipulating objects with robotic hands is a complicated task. Not only the fingers of the hand, but also the pose of the robot's end effector need to be coordinated. Using human demonstrations of movements is an intuitive and data-efficient way of guiding the robot's behavior. We propose a modular framework with an automatic embodiment mapping to transfer recorded human hand motions to robotic systems. In this work, we use motion capture to record human motion. We evaluate our approach on eight challenging tasks, in which a robotic hand needs to grasp and manipulate either deformable or small and fragile objects. We test a subset of trajectories in simulation and on a real robot and the overall success rates of about 70% are aligned.

关键词： Robot kinematics Robot vision systems Humanoid robots Reinforcement learning Grasping Cameras Motion capture

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Optimal Design of a Multipurpose Test Stand for RoboWalk Assistive Device

Optimal Design of a Multipurpose Test Stand for RoboWalk Ass...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian Mahdi Nabipour Vahid Akbari Omid Mahdizadeh Arash T. Beydokhti Amin Kiani Center of Excellence in Robotics and Control K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665420952

The user safety in wearable robotics is an inevitable major issue. In this paper, to ensure the proper performance of the various components of lower-limb wearable robots, a multipurpose test stand for the stance leg is designed for the first time and presented for RoboWalk. This multipurpose test stand is developed to simulate the performance of a stance leg motion during different walking gaits with manually controlled various speeds. The design procedure of different subsystems including the main body, human-robot interaction force measuring unit, power transmission unit, ankle path (gait) production mechanism, and the electronics of the test stand are expressed in detail. Eventually, the entire system is evaluated dynamically using the ADAMS multibody dynamics simulation software, which reveals the merits of the designed multipurpose test stand.

关键词： Legged locomotion Actuators Force measurement Torque Power measurement Dynamics Power transmission

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Dynamics Modelling and Parameters Estimation for Nonlinear-Model Predictive control of Underwater Robots

Dynamics Modelling and Parameters Estimation for Nonlinear-M...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian Mohammad Jamali Omid Mahdizadeh Vahid Akbari Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665420952

Underwater robots are to be extensively used in various submerged missions. A few research works have been conducted to investigate the nonlinear dynamical behavior of such systems in ocean flows. In this paper, dynamics modeling and parameters estimation for these complicated systems are developed for using model-based predictive control. It is begun by presenting the nonlinear equations governing the dynamics of an underwater robot in an ocean open flow. Additionally, the movement of the diving and depth motion of the robot in such cases is analyzed. A method to estimate hydrodynamic and other parameters of an underwater robot is presented and compared with experimental data. This method consists of close-to-reality simulation using a CFD subsystem of the ANSYS software. Finally, these parameters are used to design a model-based controller. Numerical simulations are carried out to evaluate the performance of the controllers. Among all the model-based controllers, nonlinear Model Predictive control (nonlinear-MPC) with constraints will be able to follow the setpoints within less time and less control effort. The experimental data confirm the simulation results, proving the underwater robot's capability for path-following in an ocean open flow.

关键词： Autonomous underwater vehicles Parameter estimation Oceans Simulation Predictive models Mathematical models Software

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RoboWalk Trajectory Planning Based on the Human Gait Prediction Using LSTM

RoboWalk Trajectory Planning Based on the Human Gait Predict...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali. A. Moosavian Amin Kiani Vahid Akbari Mahdi Nabipour Sina Ghanaat Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665420952

The increasing demand for rehabilitation robots alongside the complexity of such devices have made their designing procedure a challenging task. One of the challenges is generating a walking pattern for lower limb exoskeletons in such a way that tasks like load carrying or rehabilitation can be performed with minimum disturbance to the human normal gait. This paper presents a deep learning method to predict the next step of RoboWalk joint angle patterns using previous trajectories of former steps. Six different gait data from an individual are chosen as the learning and test dataset. The human joint trajectories during each of the six considered gaits and the augmented human-RoboWalk kinematic model are used to extract RoboWalk’s joint trajectories. The Long-Short-Term Memory (LSTM) network is then used for predicting the future trajectory and classifying the phase of walking. The accuracy for the prediction is about 98.5 percent and the overall error in all the gait modes is less than 5 degrees.

关键词： Legged locomotion Training Performance evaluation Trajectory planning Kinematics Rehabilitation robotics Trajectory

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Distributed formation control of networked mechanical systems

arXiv

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arXiv 2022年

作者： Javanmardi, Najmeh Borja, P. Yazdanpanah, M.J. Scherpen, J.M.A. Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Cognitive Robotics Delft University of Technology Delft Netherlands Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen Netherlands

This paper investigates a distributed formation tracking control law for large-scale networks of mechanical systems. In particular, the formation network is represented by a directed communication graph with leaders and followers, where each agent is described as a port-Hamiltonian system with a constant mass matrix. Moreover, we adopt a distributed parameter approach to prove the scalable asymptotic stability of the network formation, i.e., the scalability with respect to the network size and the specific formation preservation. A simulation case illustrates the effectiveness of the proposed control approach. © 2022, CC BY.

关键词： Networked control systems

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A Modular Approach to the Embodiment of Hand Motions from Human Demonstrations

arXiv

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arXiv 2022年

作者： Fabisch, Alexander Uliano, Manuela Marschner, Dennis Laux, Melvin Brust, Johannes Controzzi, Marco Robotics Innovation Center DFKI GmbH Robert-Hooke-Straße 1 BremenD-28359 Germany The BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy The Department of Excellence in Robotics & AI Scuola Superiore Sant'Anna Pisa Italy Robotics Research Group University of Bremen Germany Plan-Based Robot Control DFKI GmbH Germany

关键词： End effectors

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A Modified Dempster Shafer Approach to Classification in Surgical Skill Assessment

A Modified Dempster Shafer Approach to Classification in Sur...

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Iranian Conference on Electrical Engineering (ICEE)

作者： Arash Iranfar Mohammad Soleymannejad Behzad Moshiri Hamid D. Taghirad School of Electrical and Computer Engineering University College of Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is.

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Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

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Asian Journal of control 2022年第1期24卷 388-400页

作者： Moaveni, Bijan Rashidi Fathabadi, Fatemeh Molavi, Ali Center of excellence for Modelling and Control of Complex Systems Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Western Michigan University MI United States Institute of Robotics and Industrial Informatics Polytechnical University of Catalonia Barcelona Spain

This study proposes an anti-slip control system for electric trains based on the fuzzy logic theory, which prevents the wheels from slipping during the acceleration and simultaneously tracks the desired speed profile. To improve the control performance, the train longitudinal velocity and the slip ratio are estimated. By using a field-oriented control (FOC), the angular speed of the traction motor is controlled. The fuzzy control system determines the desired angular speed of the traction motor as the reference input of FOC to obtain the desired slip ratio and track the desired speed profile. Simulation results show the effectiveness of the control system in various wheel–rail surface conditions based on the real parameters of ER24PC locomotive. © 2020 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Traction motors

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Towards an Efficient Computational Framework for Surgical Skill Assessment: Suturing Task by Kinematic Data

Towards an Efficient Computational Framework for Surgical Sk...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Parisa Hasani Faraz Lotfi Hamid D. Taghirad Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical Engineering K.N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665420952

During the course of the residency, novice surgeons develop specific skills before they perform actual surgical procedures. Manual feedback and assessment in basic robotic-assisted minimally invasive surgery (RMIS) training take up much of the expert surgeons’ time, while it is very favorable to automatically feedback to all surgeons in various skill levels. Towards this end, we use the surgical robot kinematic dataset named JIGSAWS, a public database collected from Da Vinci robot operated by 7 surgeons, to extract 49 metrics for the suturing task using three types of features, namely time and motion-based, entropy-based, and frequency-based. To find out the most relevant metrics in skill assessment, we perform and compare two feature selection/reduction methods, namely principal component analysis (PCA) and relief algorithm. We separately reduce the features based on these two methods, while using a combination method. Although resulting in an acceptable accuracy of 84% when using each separately, the combination method results in 92% particularly noteworthy accuracy.

关键词： Measurement Training Time-frequency analysis Minimally invasive surgery Medical robotics Kinematics Feature extraction

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Robustcontainment control of heterogeneous multi-agent systems with structured uncertainty and external disturbances

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International Journal of Robust and Nonlinear control 2021年第2期32卷

作者： Hajar Atrianfar Abolghasem Karimi Center of Excellence on Control and Robotics Department of Electrical Engineering Amirkabir University of Technology Tehran Iran

This article considers the robust containment control problem of heterogeneous linear multi-agent systems subject to structured uncertainties and external disturbances. By introducing a new neighborhood error of follower agents, the containment control problem can be formulated into output regulation problem. By employing a distributed compensator and robust control approach, sufficient conditions in terms of linear matrix inequalities are derived to ensure that all followers asymptotically converge to the convex hull spanned by the leaders with the prescribed performance under fixed topology. A numerical example is provided to verify the effectiveness of the proposed method.

关键词： external disturbances controller heterogeneous linear multi-agent system linear fractional transformation robust containment control structured uncertainties

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