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检索条件"任意字段=International Asia Conference on Informatics in Control, Automation, and Robotics"

共 1478 条记录，以下是1351-1360 订阅

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Development of a real-time framework between Matlab/Simulink and SIEMENS PLC for automated relocation of products in the warehouse

Development of a real-time framework between Matlab/Simulink...

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international conference on Methods and Models in automation and robotics (MMAR)

作者： Damian Ignacy Leszek Gomółka Ryszard Kopka Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland SOLPAK Sp. z o.o. Sp. k. ul. Jana Pawła II 2 Nędza Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

The control system design proposed in the article is a work platform that enables the implementation of control algorithms developed in many different programming languages. This functionality is made possible by integrating the MATLAB/Simulink and TIA Portal programming environments using tools such as: SIMATIC S7-1500 ODK 1500S and SIMATIC Target 1500S for Simulink. The combination of these software tools with the physical execution system implemented in the area of automated warehouse system with product relocation function is a new solution, not yet found in the literature. The above described configuration of software and devices provides the opportunity to implement advanced analytical tools in an industrial environment. Such a configuration also gives the possibility to use other programming languages, such as Python, $\mathrm{C}, \mathrm{C}++$, in the algorithm for controlling the automatic warehouse system. The proposed working environment gives the researchers the opportunity to develop and implement complex control algorithms faster in an industrial environment. This allows us to apply advanced artificial intelligence algorithms to control technology.

关键词： Technological innovation Software packages Software algorithms Real-time systems Web servers Artificial intelligence Software tools

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Cooperative Roundabout Navigation: Distributed Predictive control with Virtual Platooning in Mixed Traffic

Cooperative Roundabout Navigation: Distributed Predictive Co...

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IEEE international conference on automation Science and Engineering (CASE)

作者： Alessandro Bozzi Simone Graffione Roberto Sacile Enrico Zero Department of Informatics Bioengineering Robotics and Systems Engineering (DIBRIS) University of Genoa Genoa Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Roundabout entry is a complex manoeuvre that must be efficiently managed to prevent traffic congestion, particularly when multiple vehicles approach the roundabout simultaneously. This paper proposes a distributed predictive control employing the Alternating Direction Method of Multipliers (ADMM) to form a virtual platoon and to determine the roundabout entry order, even in the presence of Human-Driven Vehicles (HDVs). The integration of HDVs introduces complexities in the dynamics of information exchange among the various elements that make up the platoon. To comprehensively assess the efficacy of the proposed control methodology, two distinct case studies are conducted, each exploring scenarios wherein an HDV occupies a different position within the virtual platoon, allowing for an evaluation of the impact of HDV position on platoon string stability. Results confirm that the controller is able to handle the insertion of all elements approaching the roundabout safely and efficiently.

关键词： Uncertainty Heuristic algorithms Convex functions Stability analysis Real-time systems Safety Vehicle dynamics Information exchange Traffic congestion Predictive control

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IASelect: Finding Best-fit Agent Practices in Industrial CPS Using Graph Databases

IASelect: Finding Best-fit Agent Practices in Industrial CPS...

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IEEE international conference on Industrial informatics (INDIN)

作者： Chandan Sharma Roopak Sinha Paulo Leitao IT & Software Engineering Auckland University of Technology New Zealand Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança Bragança Portugal

The ongoing fourth Industrial Revolution depends mainly on robust Industrial Cyber-Physical Systems (ICPS). ICPS includes computing (software and hardware) abilities to control complex physical processes in distributed industrial environments. Industrial agents, originating from the well-established multi-agent systems field, provide complex and cooperative control mechanisms at the software level, allowing us to develop larger and more feature-rich ICPS. The IEEE P2660.1 standardisation project, "Recommended Practices on Industrial Agents: Integration of Software Agents and Low Level automation Functions" focuses on identifying Industrial Agent practices that can benefit ICPS systems of the future. A key problem within this project is identifying the best-fit industrial agent practices for a given ICPS. This paper reports on the design and development of a tool to address this challenge. This tool, called IASelect, is built using graph databases and provides the ability to flexibly and visually query a growing repository of industrial agent practices relevant to ICPS. IASelect includes a front-end that allows industry practitioners to interactively identify best-fit practices without having to write manual queries.

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A study of anti-robot agent mechanisms and process on online games

A study of anti-robot agent mechanisms and process on online...

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IEEE international conference on Intelligence and Security informatics, ISI

作者： N.W. Lo Shiou-Hung Chen Department of Information Management National Taiwan University of Science and Technology Taipei Taiwan Department of Infonnation Management National Taiwan University of Science and Technology Taipei Taiwan

The target of this paper is to solve illegal software agent or so called the robot (or Bot) agent problem in online game environment. By installing and activating illegal online game agent programs, online game players can get unfair gaming benefits such as gaining credits of his game character from automatic game playing control of Bot programs. An online game with many active Bot players can disperse the playing interest of human players and quickly lead the life cycle of game to an end. To solve this both problem, we propose a Bot detection and handling process. Four phases are adopted in sequence: Bot filtering with random tester selection mechanism, automatic CAPTCHA (completely automated public turing test to tell computers and humans apart) test, potential Bot player tracing, and Bot player sanctions. In addition, we physically implement a CAPTCHA test module onto a primitive online game server to demonstrate the adoptability of automatic CAPTCHA test in online game environment.

关键词： Automatic testing Humans robotics and automation Face detection Information management Environmental management Technology management Software agents Automatic control Filtering

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A Teaching Mechanism of Supernumerary Robotic Limbs for Natural Human-robot Collaboration

A Teaching Mechanism of Supernumerary Robotic Limbs for Natu...

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international conference on Advanced robotics and Mechatronics (ICARM)

作者： Shiyang Liu Jing Luo Chao Zeng Ting Lei Chenguang Yang School of Automation Wuhan University of Technology Wuhan China Department of Informatics University of Hamburg Hamburg Germany School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan China School of Automation Science and Engineering South China University of Technology Guangzhou China

Supernumerary robotic limb (SRL) is an intelligent platform for providing assistance to humans at extreme conditions in natural human-robot collaboration (HRC) tasks. However, it is still difficult to control the SRL by using a simple way and to eliminate the cognitive burden placed on the human operator. of the human operator. Learning that the burden on human operators can be reduced by using Learning from Demonstrations (LfD) which learns repetitive teleoperation tasks. Our study introduces a method for teaching SRL that utilizes Dynamic Time Warping in combination with Gaussian Mixture Model and Gaussian Mixture Regression. The proposed mechanism utilizes a DTW algorithm to align and compare motion patterns between the human teacher and the SRL. Then, the GMM algorithm was applied to encode the motion patterns into statistical models. Additionally, these models are used to reate a task model that is applicable in a broad range of situations through the GMR method, which can be utilized to regulate the motion of SRL in real-time. The proposed mechanism is tested in experiments, and the results show that the SRL can accurately replicate the motion patterns with an average error of less than 10% for the HRC tasks. The proposed teaching mechanism has potential applications in fields such as rehabilitation and industrial automation, where the use of SRL can strengthen human capabilities and improve task efficiency.

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End to End Learning of Spiking Neural Network based on R-STDP for a Lane Keeping Vehicle

End to End Learning of Spiking Neural Network based on R-STD...

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IEEE international conference on robotics and automation

作者： Zhenshan Bing Claus Meschede Kai Huang Guang Chen Florian Rohrbein Mahmoud Akl Alois Knoll Department of Informatics Technical University of Munich Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Sun Yat-Sen University School of Automotive Engineering Tongji University

Learning-based methods have demonstrated clear advantages in controlling robot tasks, such as the information fusion abilities, strong robustness, and high accuracy. Mean-while, the on-board systems of robots have limited computation and energy resources, which are contradictory with state-of-the-art learning approaches. They are either too lightweight to solve complex problems or too heavyweight to be used for mobile applications. On the other hand, training spiking neural networks (SNNs) with biological plausibility has great potentials of performing fast computation and energy efficiency. However, the lack of effective learning rules for SNNs impedes their wide usage in mobile robot applications. This paper addresses the problem by introducing an end to end learning approach of spiking neural networks for a lane keeping vehicle. We consider the reward-modulated spike-timing-dependent-plasticity (R-STDP) as a promising solution in training SNNs, since it combines the advantages of both reinforcement learning and the well-known STDP. We test our approach in three scenarios that a Pioneer robot is controlled to keep lanes based on an SNN. Specifically, the lane information is encoded by the event data from a neuromorphic vision sensor. The SNN is constructed using R-STDP synapses in an all-to-all fashion. We demonstrate the advantages of our approach in terms of the lateral localization accuracy by comparing with other state-of-the-art learning algorithms based on SNNs.

关键词： Voltage control Task analysis Robot sensing systems Training Synapses Neurons

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Preference relation and Community detection

Preference relation and Community detection

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international Symposium on Computational Intelligence and informatics

作者： József Dombi Sakshi Dhama Institute of Informatics University of Szeged Szeged Hungary

ISBN: (数字)9781728156255

ISBN: (纸本)9781728156262

To study the properties of complex networks we have to generate artificial networks. Here, we analyze the existing fitness function for the creation of the communities in the synthesis of an artificial network. One of the first benchmarks known as the GN benchmark, it was used to generate networks with non-overlapping communities. In 2008 Lancichinetti-Fortunato proposed a new benchmark (LFR). This benchmark generated networks with overlapping communities. In this paper, we introduce a new preference-based fitness function to assign a membership relation to the nodes. Here, we introduce a novel approach for controlling the creation of overlapping structures by using preferences. The proposed method works well if there are less than ten percent of outliers when tested on smaller graphs of size ≈ 15 to ≈ 500.

关键词： Preference relation Overlapping Structure community detection outliers complex networks complex networks outliers Communities BENCHMARKS approach control Preferences Network Overriding structures radar approach control

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Robot Path Planning using Particle Swarm Optimization of Ferguson Splines

Robot Path Planning using Particle Swarm Optimization of Fer...

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international conference on Emerging Technologies and Factory automation (ETFA)

作者： Martin Saska Martin Macas Libor Preucil Lenka Lhotska Informatics VII: Robotics and Telematics Julius-Maximilians University Wuerzburg Germany Gerstner Laboratory for Intelligent Decision Making Czech Technical University Prague Czech Republic

Robot path planning problem is one of most important task mobile robots. This paper proposes an original approach using a path description by string of cubic splines. Such path is easy executable and natural for car-like robot. Furthermore, it is possible to ensure smooth derivation in connections of particular splines. In this case, the path planning is equivalent to optimization of parameters of splines. An evolutionary technique called particle swarm optimization (PSO) was used hereunder due to its relatively fast convergence and global search character. Various settings of PSO parameters were tested and the best setting was compared to two classical mobile robot path planning algorithms.

关键词： Path planning Particle swarm optimization Mobile robots Intelligent robots Laboratories Decision making Shape control Robot control Iterative algorithms Collision avoidance

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Evolutionary Morphology for Real Cubic Modular Robots

Evolutionary Morphology for Real Cubic Modular Robots

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Congress on Evolutionary Computation

作者： T. Tohge K. Shimada H. Iba Department of Frontier Informatics Graduate School of Frontier Science University of Tokyo Bunkyo Tokyo Japan

Recently modular robots have become more capable of practical applications with the recent improvement of sensors and actuators. Among them, a robot has been developed which can change its pattern according to the landscape or for its own purpose. However, deciding the appropriate pattern and controller manually is not easy with the increased number of modules. In this paper, we propose a new approach to automatically building patterns of block-type robots by means of artificial-life morphogenesis. We empirically show the emergence of the effective patterns in both virtual and real worlds, some of which seem to be surprisingly counter-intuitive.

关键词： Morphology robotics and automation Robot sensing systems Robotic assembly Insects Biological system modeling informatics Actuators Automatic control Fault tolerance

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A new system architecture for applying symbolic learning techniques to robot manipulation tasks

A new system architecture for applying symbolic learning tec...

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IEEE international Workshop on Intelligent Robots and Systems (IROS)

作者： J. Kreuziger M. Hauser Karlsruher Institut fur Technologie - Campus Nord Eggenstein-Leopoldshafen Baden-WÃ¼rttemberg DE

Presents a new system architecture that enables a robot control system to learn at a symbolic level during planning and executing tasks. A user can program the robot by simply demonstrating the tasks it should perform. By performing inductive generalization and specialization steps, the system is able to improve its knowledge base. The architecture consists of a set of distributed knowledge units which realize a focus of attention that is necessary for efficient execution and learning, and which also makes competition between different problem solutions possible.

关键词： Robot control robotics and automation Telerobotics Educational robots Robot programming Problem-solving Production systems Computer architecture control systems informatics

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