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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Hemjyoti Das Bjørn Kåre Sæbø Kristin Y. Pettersen Christian Ott Faculty of Electrical Engineering and Information Technology Automation and Control Institute (ACIN) Technical University of Vienna TU Wien Vienna Austria Department of Engineering Cybernetics Centre for Autonomous Marine Operations and Systems (NTNU AMOS) NTNU Norwegian University of Science and Technology Trondheim Norway German Aerospace Center Institute of Robotics and Mechatronics Wessling Germany

Hardware-in-the-loop simulation (HILS) allows a more realistic evaluation of control approaches than what is possible with pure software simulations, but without the actual complexity of the complete system. This is important for some complex systems such as orbital robots, where testing of the system is typically not possible after its launch, and an on-ground replica is used to validate the performance of such a system. In this article, an impedance-matching approach is presented to match the end-effector dynamics of a fixed-base robot manipulator with that of a target vehicle-manipulator system (VMS), while taking into account the redundant nullspace dynamics in a connected real-time simulation framework. This approach ensures that the forces and torques exerted by the system on the environment matches with that of the simulated system. The contact wrenches used in our approach are not obtained from numerical simulations, but rather from real physical interaction, which is one of the main advantages of our approach. The effectiveness of our method is validated by demonstrating various physical interaction tasks with the environment, using a suspended aerial manipulator as the target system.

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Persistent excitation is unnecessary for on-line exponential parameter estimation: A new algorithm that overcomes this obstacle

arXiv

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arXiv 2021年

作者： Korotina, Marina Romero, Jose Guadalupe Aranovskiy, Stanislav Bobtsov, Alexey Ortega, Romeo IETR CentaleSupélec Avenue de la Boulaie Cesson-Sévigné35576 France Faculty of Control Systems and Robotics ITMO University Saint-Petersburg197101 Russia Departamento Académico de Sistemas Digitales ITAM Río hondo 1 Progreso Tizapán Mexico City01080 Mexico

In this paper we prove that it is possible to estimate on-line the parameters of a classical vector linear regression equation Y = Ωθ, where Y ∈ n, Ω ∈ n×q are bounded, measurable signals and θ ∈ Rq is a constant vector of unknown parameters, even when the regressor Ω is not persistently exciting. Moreover, the convergence of the new parameter estimator is global and exponential and is given for both, continuous-time and discrete-time implementations. As an illustration example we consider the problem of parameter estimation of a linear time-invariant system, when the input signal is not sufficiently exciting, which is known to be a necessary and sufficient condition for the solution of the problem with standard gradient or least-squares adaptation algorithms. © 2021, CC BY.

关键词： Parameter estimation

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Parameter estimation of nonlinearly parameterized regressions without overparameterization nor persistent excitation: Application to system identification and adaptive control

arXiv

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arXiv 2019年

作者： Ortega, Romeo Gromov, Vladislav Nuño, Emmanuel Pyrkin, Anton Romero, Jose Guadalupe Laboratoire des Signaux et Systèmes CNRS-SUPELEC Gif-sur-Yvette France Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia Department of Computer Science CUCEI University of Guadalajara Guadalajara Mexico Departamento Académico de Sistemas Digitales ITAM Ciudad de México Mexico

In this paper we propose a solution to the problem of parameter estimation of nonlinearly parameterized regressions-continuous or discrete time-and apply it for system identification and adaptive control. We restrict our attention to parameterizations that can be factorized as the product of two functions, a measurable one and a nonlinear function of the parameters to be estimated. Although in this case it is possible to define an extended vector of unknown parameters to get a linear regression, it is well-known that overparameterization suffers from some severe shortcomings. Another feature of the proposed estimator is that parameter convergence is ensured without a persistency of excitation assumption. It is assumed that, after a coordinate change, some of the elements of the transformed function satisfy a monotonicity condition. The proposed estimators are applied to design identifiers and adaptive controllers for nonlinearly parameterized systems. In continuous-time we consider a general class of nonlinear systems and those described by Euler-Lagrange models, while in discrete-time we apply the method to the challenging problems of direct and indirect adaptive pole-placement. The effectiveness of our approach is illustrated with several classical examples, which are traditionally tackled using overparameterization and assuming persistency of excitation. Copyright © 2019, The Authors. All rights reserved.

关键词： Parameterization

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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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Learning and recognizing behavioral patterns using position and posture of human body and its application to detection of irregular states

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systems and Computers in Japan 2005年第13期36卷 45-56页

作者： Aoki, Shigeki Iwai, Yoshio Onishi, Masaki Kojima, Atsuhiro Fukunaga, Kunio Graduate School of Engineering Osaka Prefecture University Sakai 599-8531 Japan Bio-Mimetic Control Research Center RIKEN Nagoya 463-0003 Japan Library and Science Information Center Osaka Prefecture University Sakai 599-8531 Japan Department of Electronic Control Engineering Kumamoto National College of Technology Japan Robotics Society of Japan Japan Sharp Corporation Japan Bio-Mimetic Control Research Center RIKEN Japan IEEJ Japan Image and Information Media Society Faculty of Liberal Arts and Sciences Osaka Prefecture University Japan Information Processing Society Japan Society for Artificial Intelligence Department of Informatics Faculty of Engineering Institute of Systems Control and Information Engineers Japan IEEE

It is generally considered that human behavior includes both regularities and habits. In this paper, the regularities and habits of behavior are called the behavioral pattern, and we wish to learn and recognize them. The conventional approaches considered behavioral patterns but used only infrared sensors or information about whether electrical appliances were on or off. Thus, it was difficult to recognize in detail how a person was performing motions in the room. In order to realize a procedure for the detailed recognition of motion in ordinary environments, on the other hand, a large number of models must be prepared beforehand. To deal with this problem, this paper proposes the following technique. Motions conducted in the learning period are automatically classified and individual models are constructed. Then, motions can be recognized in detail without preparing a large number of models, and behavioral patterns can be recognized by considering the sequence of motions. In experiments, human motions and behavioral patterns in an indoor environment were learned and recognized, and the effectiveness of the method was demonstrated. © 2005 Wiley Periodicals, Inc.

关键词： Pattern recognition

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On simple design of a robust finite-time observer

On simple design of a robust finite-time observer

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IEEE Conference on Decision and control

作者： Artem N. Nekhoroshikh Denis Efimov Andrey Polyakov Wilfrid Perruquetti Igor B. Furtat Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia Valse Team Inria Univ. Lille CNRS UMR 9189 - CRIStAL Lille France Univ. Lille CNRS Centrale Lille UMR 9189 CRIStAL Lille France IPME RAS V.O St. Petersburg Russia

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper presents a novel observer that estimates the state of a linear system in the observer canonical form in finite time. Due to the specially selected dynamical gain, the proposed observer is easy to tune and, at the same time, it is robust to external perturbations (e.g., state disturbances and measurement noises). The tuning algorithm consists in solving a simple system of linear matrix inequalities with only two adjustable parameters. Theoretical results and a comparison with homogeneous and prescribed-time observers are illustrated by numerical simulation.

关键词： Linear systems Simulation Perturbation methods Observers Numerical simulation Time measurement Steady-state

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Enhancing Precision Agriculture Through Human-in-the-Loop Planning and control

Enhancing Precision Agriculture Through Human-in-the-Loop Pl...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

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Arctic Respiratory Monitoring System

Arctic Respiratory Monitoring System

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International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： G. Lukyanov A. Rassadina V. Kossareva A.A. Stepanov R.Z. Alexeev The Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia Larionov Institute of Physical and Technical Problems of the North SB RAS Yakutsk Russian Federation Laboratory of Immunological researches Yakut Science Centre of Complex Medical Problems Medical Institute M. K. Ammosov North-Eastern Federal University Yakutsk Russia

ISBN: (数字)9781728169514

ISBN: (纸本)9781728169521

The results of heat transfer dynamic processes during the breathing are presented. The study is relevant for investigation of health in the extreme conditions of the Arctic. For estimation of this processes the measurement system of temperature, pressure and velocity pulsations in nostrils are developed. It has been shown that for respiratory system diagnostic it is necessary to analyze such dynamic characteristics as the power spectral density and entropy.

关键词： Temperature measurement Heat transfer Monitoring Temperature sensors Pressure measurement Fluctuations Semiconductor device measurement

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Machine Learning with Blockchain for Secure E-voting System

Machine Learning with Blockchain for Secure E-voting System

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2020 First International Conference of Smart systems and Emerging Technologies (SMARTTECH)

作者： Muhammad Asaad Cheema Nouman Ashraf Asad Aftab Hassaan Khaliq Qureshi Muhammad Kazim Ahmad Taher Azar National University of Sciences and Technology (NUST) Islamabad Pakistan Telecommunication Software and System Group (TSSG) Waterford Institute of Technology Waterford Ireland Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China Robotics and Internet-of-Things Lab (RIOTU) Prince Sultan University Riyadh Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University

ISBN: (数字)9781728174075

ISBN: (纸本)9781728174082

Voting is a central component of a country's political life cycle. Privacy, authentication and integrity of citizens' votes and their data are considered to be essential to any e-voting program. In order to resolve these concerns, we propose a stable e-voting system based on the principles of blockchain and machine learning. We use blockchain to ensure the integrity and security of votes, machine learning model to detect intrusion in voting data centers and e-voting stations. In the proposed model, we use the concepts of personal and public blockchain. The personal blockchain is used for the purposes of voter registration and voting. The public blockchain is used to maintain the integrity of the personal data of the voters by storing the root hash derived from the Merkle hash tree and revealing the results of the voting stations as soon as the voting process is completed. The proposed blockchain-based e-voting system offers transparency, treasury, confidence and prevents intrusion into the information exchange network.

关键词： Data centers Support vector machine classification Blockchain Machine learning Web servers Registers Electronic voting

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Fall detection for elderly by using an intelligent cane robot based on center of pressure (COP) stability theory

Fall detection for elderly by using an intelligent cane robo...

引用

International Symposium on Micromechatronics and Human Science (MHS)

作者： Pei Di Jian Huang Shotaro Nakagawa Kosuke Sekiyama Toshio Fukuda Department of Micro-Nano Systems Engineering Nagoya University Aichi Nagoya Japan Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Institute for Advanced Research Nagoya University Chikusa-ku Nagoya Japan The Intelligent Robotics Institute School of Mechatronic Engineering Beijing Institute of Technology China The Faculty of Science and Engineering Meijo University Japan

An intelligent cane robot was designed for aiding the elderly and handicapped people walking. The robot consists of a stick, a group of sensors and an omni-directional basis driven by three Swedish wheels. Multiple sensors were used to recognize the user's “walking intention”, which is quantitatively described by a new concept called intentional direction (ITD). Based on the guidance of filtered ITD, a novel intention-based admittance motion control (IBAC) scheme was proposed for the cane robot. To detect the fall of user, a detection method based on Dubois possibility theory was proposed using the combined sensor information from force sensors, a laser ranger finder (LRF) and an on-shoe load sensor. The human fall model was represented in a two-dimensional space, where the relative position between the center of pressure (COP) and the center of support triangle was utilized as a significant feature. The effectiveness of proposed fall detection method was also confirmed by experiments.

关键词： Legged locomotion Robot sensing systems Senior citizens Artificial intelligence

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