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检索条件"任意字段=26th International Conference on Methods and Models in Automation and Robotics"

共 1175 条记录，以下是21-30 订阅

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19th international conference on Computer Aided Systems theory, EUROCAST 2024

19th International Conference on Computer Aided Systems Theo...

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19th international conference on Computer Aided Systems theory, EUROCAST 2024

ISBN: (纸本)9783031838873

the proceedings contain 104 papers. the special focus in this conference is on Computer Aided Systems theory. the topics include: Influence of Spike Encoding, Neuron models and Quantization on SNN Performance;adaptive Combination in Frequency Domain: An Approach for Robust Nonlinear Acoustic Echo Cancellation;using of a Robotic Platform to Detect Acoustic Events for Indoor Environments;modeling Wildlife Accident Risk with Gaussian Mixture models;towards a Unified Incident Detection and Response System for Autonomous Transportation;edge-Processing of Myoelectric Signals for the Control of Hand and Arm-Prostheses;AI-Driven Gesture and Action Recognition for Learning Medicine through Virtual Reality;Medical Protocols and AI-Driven Algorithms for Enhanced Monitoring of Cardiac Implantable Electronic Devices;a Survey of Machine Learning methods for Analyzing Synovitis Arthritis in Human Joints;motion Tracking in Augmented and Mixed Realities for Healthcare and Medicine Applications;advancements and Applications of Medical Human Digital Twin Technology in Cerebral Palsy Diagnosis, therapy, and Rehabilitation;Transformation of IEC 61131-3 onto an Embedded Platform Using LLVM;machine Learning Based Parameter Estimation of Energy models in Digital Production Environments;efficient Classification of Live Sensor Data on Low-Energy IoT Devices with Simple Machine Learning methods;machine Learning Using a Hybrid Quantum Classical Algorithm with Amplitude Data Encoding;quantitative Trend Analysis of Reinforcement Learning Algorithms in Production Systems;Using automationML for Advanced Simulation in Industrial automation;AR Digital Twin Demonstrator for Industrial robotics Education;Accelerating Manual Pick-and-Place Operations with AR-Projected CAD Plans and AI-Assisted Object Recognition;variety Engineering – A Cybernetic Concept with Practical Implications;using a System Archetype to Explore a Business Model for Digital Textile Microfactories;interacting with the Water Cycle -

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LAV-ACT: Language-Augmented Visual Action Chunking with Transformers for Bimanual Robotic Manipulation

LAV-ACT: Language-Augmented Visual Action Chunking with Tran...

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international conference on Autonomous Robots and Agents, ICARA

作者： Dhurba Tripathi Chunting Liu Niraj Pudasaini Yu Hao Anthony Tzes Yi Fang NYU Embodied AI and Robotics Lab New York University Abu Dhabi Abu Dhabi UAE Center for Artificial Intelligence and Robotics New York University Abu Dhabi Abu Dhabi UAE

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Bimanual robotic manipulation, involving the coordinated use of two robotic arms, is essential for tasks requiring complex, synchronous actions. Action Chunking with Transformers (ACT) is a representative framework that enables robots to break down complex tasks into manageable sequences, facilitating autonomous learning of multi-step actions. However, we observe limitations in the ACT framework: it relies solely on visual observations as input, focusing on task-specific action predictions, and it uses a simple ResNet-based feature extractor for image processing, which is often insufficient for complex and multi-view bimanual arm observations. In this paper, we introduce an enhanced language-augmented version of ACT that leverages Voltron-a language-driven representation model-to incorporate both visual observations and language prompts into dense, multi-modal embeddings. these embeddings are used to condition the ResNet backbone feature maps through Featurewise Linear Modulation (FiLM), allowing our model to integrate contextually relevant linguistic information with visual data for more adaptive action chunking. Extensive experiments show that our approach significantly improves the performance of bimanual robot arms in executing complex, multi-step tasks guided by language cues, outperforming traditional ACT methods. Project website: https://***/LAV-ACT/

关键词： Visualization Adaptation models Robot kinematics Modulation Linguistics Transformers Manipulators Feature extraction Data models Context modeling

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A Kinematic Simulation Strategy of a Compliant 4-Bar Linkage with Flexure Hinge Joint

A Kinematic Simulation Strategy of a Compliant 4-Bar Linkage...

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international conference on Autonomous Robots and Agents, ICARA

作者： Pengfei Wang Lailu Li Rui Wang Xin Guo Dongyu Li Shanghai Radio Equipment Research Institute Shanghai China School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin China

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Compliant mechanisms have drawn a lot of attention in recent years. Discrete elastic rod theory has paved the way in designing and analyzing linkage mechanisms with flexure hinges (compliant linkage mechanism). In order to achieve a same kinematic as the rigid linkage mechanism, this paper gives a general model for the kinematic of a compliant linkage mechanism: crank and rocker mechanism: Firstly, modeling of a compliant linkage mechanism based on discrete elastic rod theory, taking a typical example of a cranker and rod mechanism; Secondly, kinematic modeling of the rigid cranker and rod mechansim; thirdly, optimization flow is introduced, including BFGS optimization method, cubic hermix spline method and other relevant settings; Lastly, the simulation results demonstrate that this model could be used in the analysis and design of the compliant linkage mechanism.

关键词： Couplings Analytical models Interpolation Manufacturing processes Simulation Optimization methods Kinematics Fasteners Splines (mathematics) Robots

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Let Hybrid A* Path Planner Obey Traffic Rules: A Deep Reinforcement Learning-Based Planning Framework

Let Hybrid A* Path Planner Obey Traffic Rules: A Deep Reinfo...

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international conference on Autonomous Robots and Agents, ICARA

作者： Xibo Li Shruti Patel Christof Büskens Optimization and Optimal Control Center for Industrial Mathematics University of Bremen Bremen Germany Department for Autonomous Systems TOPAS Industriemathematik Innovation gGmbH Bremen Germany

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Deep reinforcement learning (DRL) allows a system to interact with its environment and take actions by training an efficient policy that maximizes self-defined rewards. In autonomous driving, it can be used as a strategy for high-level decision making, whereas low-level algorithms such as the hybrid A* path planning have proven their ability to solve the local trajectory planning problem. In this work, we combine these two methods where the DRL makes high-level decisions such as lane change commands. After obtaining the lane change command, the hybrid A* planner is able to generate a collision-free trajectory to be executed by a model predictive controller (MPC). In addition, the DRL algorithm is able to keep the lane change command consistent within a chosen time-period. Traffic rules are implemented using linear temporal logic (LTL), which is then utilized as a reward function in DRL. Furthermore, we validate the proposed method on a real system to demonstrate its feasibility from simulation to implementation on real hardware.

关键词： Training Trajectory planning Predictive models Deep reinforcement learning Prediction algorithms Planning Trajectory Logic Autonomous vehicles Robots

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14th international conference ON methods AND models IN automation AND robotics

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IFAC Proceedings Volumes 2009年第13期42卷 i-iii页

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Model-Free Predictive Control Strategy for Inverter Based on Adaptive Super- Twisting Sliding Mode Observer

Model-Free Predictive Control Strategy for Inverter Based on...

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26th international conference on Industrial Technology, ICIT 2025

作者： Shu, Zejian Luo, Wensheng Zhang, Ruifang Leon, Jose I. Alcaide, Abraham M. Franquelo, Leopoldo G. School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China School of Astronautics Harbin Institute of Technology Harbin China School of Engineering Universidad de Sevilla Electronic Engineering Department Seville Spain

ISBN: (纸本)9798331521950

the application of model predictive control (MPC) in inverters needs to consider the influence of parameter accuracy. the mismatch between the modeling circuit parameters and the actual circuit parameters will restrict the performance of the traditional model predictive control. Model-free predictive control (MFPC) using ultra-local models has been extensively studied. However, the model-free predictive control of algebraic methods requires a large amount of historical voltage and current sampling data, resulting in slower dynamic characteristics. therefore, this paper proposes a model-free predictive control method based on super-local model and adaptive super-twisting sliding mode observer. Firstly, the influence of parameter variation on the conventional model predictive control is analyzed, and the first-order ultra-local model of the inverter is established. Secondly, a super-twisting sliding mode observer with an adaptive factor is used to estimate the dynamic part of the ultra-local model. Finally, in the simulation, the proposed method is compared with MPC and algebra-based MFPC to verify the effectiveness and superiority. the results show that the proposed method can significantly reduce the current thD value in steady state and shorten the adjustment time in dynamic state. © 2025 IEEE.

关键词： model-free predictive control parameter robustness super-twisting sliding mode observer ultra-local model

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A Remark on Cascaded Energy Based Trajectory Tracking Control of a Quadrotor 26

A Remark on Cascaded Energy Based Trajectory Tracking Contro...

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26th international conference on methods and models in automation and robotics

作者： Horn, Joachim Helmut Schmidt Univ Univ Fed Armed Forces Hamburg Fac Elect Engn Hamburg Germany

Considering the cascaded energy based trajectory tracking control of a quadrotor, the first and second time derivative of the orientation of the desired thrust force are derived, that are required for the trajectory t... 详细信息

ISBN: (数字)9781665468589

ISBN: (纸本)9781665468596;9781665468589

关键词： Closed-form solutions automation Trajectory tracking Attitude control Force Robots

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Model parameters variation in constrained discrete time sliding mode control 26

Model parameters variation in constrained discrete time slid...

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26th international conference on methods and models in automation and robotics

作者： Jaskula, Marek Lesniewski, Piotr Lodz Univ Technol Inst Automat Control 18 Stefanowskiego St PL-90537 Lodz Poland

ISBN: (数字)9781665468589

ISBN: (纸本)9781665468596;9781665468589

In this paper we take into account the variation of the model parameters, during the regulation process, in the discrete time sliding mode control approach. Moreover, the system is affected by unknown, but bounded external disturbances that do not need to satisfy the matching conditions. the controller guarantees the fastest, monotonic and finite time convergence of the representative point to the switching hyperplane, simultaneously ensuring constraints satisfaction on both state and input signal. Sufficient condition that assures all mentioned properties is formally proved and the simulation example demonstrates advantages of the theoretical considerations.

关键词： Sufficient conditions Uncertainty automation Process control Switches Regulation Sliding mode control

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Machine learning methods for anomaly detection in computer networks 26

Machine learning methods for anomaly detection in computer n...

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26th international conference on methods and models in automation and robotics

作者： Gajda, Jakub Kwiecien, Joanna Chmiel, Wojciech AGH Univ Sci & Technol Dept Automat Control & Robot Al Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (数字)9781665468589

ISBN: (纸本)9781665468596;9781665468589

With a large increase in the amount of data that are transferred via publicly available computer networks, the global demand for new protection and prevention methods could be observed in recent studies of many research groups. the paper deals with anomaly detection, focusing on cybersecurity applications, as there are only few papers that address this topic. Four methods, such as DBSCAN, One-class SVM, LSTM and Isolation forest were used to solve this problem. During the experimental part, the implementation and experiments were performed to examine the performance on common dataset to assess the ability and further possible applications.

关键词： anomaly detection machine learning cybersecurity

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Forecasting models for Polish coal mining accidents 26

Forecasting models for Polish coal mining accidents

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26th international conference on methods and models in automation and robotics

作者： Kraszewska, Marta Kashpruk, Nataliia Baranowski, Jerzy Kapusta, Mariusz AGH Univ Sci & Technol Dept Automat Control & Robot Krakow Poland AGH Univ Sci & Technol Fac Civil Engn & Resource Management Krakow Poland

ISBN: (数字)9781665468589

ISBN: (纸本)9781665468596;9781665468589

In paper, forecasting models using exponential smoothing for Polish coal mining safety accidents are presented. Prior to this, data is analyzed and approach for building forecasting models in Tableau is described in details. three forecasting models are revealed, respectively for all accidents in coal mines, fatal accidents and employment. Received results are promising and confidence intervals cover the predictions well. Improved forecast accuracy with presented models might provide coal mine enterprises more precise data, supporting safety management in those organizations.

关键词： safety accidents fatal accidents forecasting exponential smoothing time series coal mining

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