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

共 24815 条记录，以下是681-690 订阅

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Towards 6DoF Bilateral Teleoperation of an Omnidirectional Aerial Vehicle for Aerial Physical Interaction 39

Towards 6DoF Bilateral Teleoperation of an Omnidirectional A...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Allenspach, Mike Lawrance, Nicholas Tognon, Marco Siegwart, Roland Swiss Fed Inst Technol Autonomous Syst Lab CH-8092 Zurich Switzerland

ISBN: (纸本)9781728196817

Bilateral teleoperation offers an intriguing solution towards shared autonomy with aerial vehicles in contact-based inspection and manipulation tasks. Omnidirectional aerial robots allow for full pose operations, making them particularly attractive in such tasks. Naturally, the question arises whether standard bilateral teleoperation methodologies are suitable for use with these vehicles. In this work, a fully decoupled 6DoF bilateral teleoperation framework for aerial physical interaction is designed and tested for the first time. The method is based on the well established rate control, recentering and interaction force feedback policy. However, practical experiments evince the difficulty of performing decoupled motions in a single axis only. As such, this work shows that the trivial extension of standard methods is insufficient for omnidirectional teleoperation, due to the operator's physical inability to properly decouple all input DoFs. This suggests that further studies on enhanced haptic feedback are necessary.

关键词： Performance evaluation Couplings automation Friction Force feedback Inspection Autonomous aerial vehicles

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Natural Gas Load Forecasting Based on Multi-Stage Model Identification 14

Natural Gas Load Forecasting Based on Multi-Stage Model Iden...

引用

14th IEEE international conference on Cyber Technology in automation, Control, and Intelligent Systems, CYBER 2024

作者： Zhang, Pengbin Wang, Hongrui Xing, Kunpeng Yuan, Mingzhe Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control System Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China China Nuclear Power Engineering Co. Ltd. Shenzhen518124 China

ISBN: (纸本)9798331506056

Natural gas load forecasting is crucial for the safe operation of urban natural gas. Based on the system identification method, the short-term natural gas load forecasting is studied in the paper. Employing a multi-stage identification framework, the initial values of the model parameters using the least squares and the instrumental variables method, while the model parameters are further optimized by the prediction error method to improve the accuracy of the model identification. The proposed method is validated by the simulation based on the public natural gas data in the U.S., demonstrating the algorithm's effectiveness in forecasting the daily natural gas load effectively. © 2024 IEEE.

关键词： Prediction models

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Weakly Supervised Correspondence Learning 39

Weakly Supervised Correspondence Learning

引用

IEEE international conference on robotics and automation (ICRA)

作者： Wang, Zihan Cao, Zhangjie Hao, Yilun Sadigh, Dorsa Stanford Univ Dept Comp Sci Stanford CA 94305 USA

ISBN: (纸本)9781728196817

Correspondence learning is a fundamental problem in robotics, which aims to learn a mapping between state, action pairs of agents of different dynamics or embodiments. However, current correspondence learning methods either leverage strictly paired data-which are often difficult to collect-or learn in an unsupervised fashion from unpaired data using regularization techniques such as cycle-consistency-which suffer from severe misalignment issues. We propose a weakly supervised correspondence learning approach that trades off between strong supervision over strictly paired data and unsupervised learning with a regularizer over unpaired data. Our idea is to leverage two types of weak supervision: i) temporal ordering of states and actions to reduce the compounding error, and ii) paired abstractions, instead of paired data, to alleviate the misalignment problem and learn a more accurate correspondence. The two types of weak supervision are easy to access in real-world applications, which simultaneously reduces the high cost of annotating strictly paired data and improves the quality of the learned correspondence. We show the videos of the experiments on our website.

关键词： Costs automation Unsupervised learning Robots Videos

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A First-Order Approach to Model Simultaneous Control of Multiple Microrobots 5

A First-Order Approach to Model Simultaneous Control of Mult...

引用

5th international conference on Manipulation, automation, and robotics at Small Scales (MARSS)

作者： Beaver, Logan E. Wu, Bingzhi Das, Sambeeta Malikopoulos, Andreas A.

ISBN: (数字)9781665459730

ISBN: (纸本)9781665459730

The control of swarm systems is relatively well understood for simple robotic platforms at the macro scale. However, there are still several unanswered questions about how similar results can be achieved for microrobots. In this paper, we propose a modeling framework based on a dynamic model of magnetized self-propelling Janus microrobots under a global magnetic field. We verify our model experimentally and provide methods that can aim at accurately describing the behavior of microrobots while modeling their simultaneous control. The model can be generalized to other microrobotic platforms in low Reynolds number environments.

关键词： Adaptation models Magnetic separation Computational modeling Switches Magnetic moments Mathematical models Trajectory

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Receding Horizon Tracking of an Unknown Number of Mobile Targets using a Bearings-Only Sensor 39

Receding Horizon Tracking of an Unknown Number of Mobile Tar...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Turner, James D. McMahon, James Zavlanos, Michael M. Naval Res Lab Phys Acoust Branch Code 7130 Washington DC 20375 USA Duke Univ Dept Mech Engn & Mat Sci Durham NC 27708 USA

ISBN: (纸本)9781728196817

Planning the motion of bearings-only sensors is critical for enabling accurate tracking of the positions of moving targets. In this paper, we demonstrate planning the observer's motion over horizons greater than one step for estimating an unknown and varying number of indistinguishable, maneuvering targets of interest using a probability hypothesis density (PHD) filter, with a Renyi divergence reward for selecting actions. We describe approximations to make this approach computationally feasible, and we propose using Monte Carlo tree search (MCTS) to further reduce the cost. Finally, we present simulation results showing that longer planning horizons reduce the error in the estimates and that MCTS can reduce the cost of planning without sacrificing the quality of the estimates.

关键词： Costs Target tracking Monte Carlo methods automation Simulation Estimation Observers

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AI-based Finite-Element Simulation automation Workflow applied to Automotive Electronics Field 25

AI-based Finite-Element Simulation Automation Workflow appli...

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25th international conference on Electronic Packaging Technology (ICEPT)

作者： Wang, Yinlong Xie, Pei Bosch Automot Prod Suzhou Co Ltd Engn Technol China & Digitalizat Suzhou Peoples R China

ISBN: (纸本)9798350353808

Electronic component is one of the key design elements considered during the development of automotive ECU (Electronic Control Unit). As the current state-of-the-art method, FEM (Finite-Element Method) simulation is widely used for thermal design optimization and solder joint reliability assessment of electronics at early stage of ECU development. To address the challenges of modeling fidelity and efficiency, the AI (Artificial Intelligence) integrated automated simulation workflow platform is developed. Leveraging standard and Bosch in-house developed Python libraries called "pyact", an Ansys-based automation toolset has been developed which accelerates the simulation workflow. With the assistance of AI methodologies, more precise electronic component models could be expected during calibration process. This paper presents 3 different industrial practices and examples focusing on the board level thermal management and solder joint reliability assessment. The first industrial example presents the standardization and automatization of the reliability simulation workflow of chip-resistor components. Utilizing Ansys ACT (Application Customization Toolkit), basic APIs (Application Programming Interface) of ACT are encapsulated into the Python library as pyact, enabling a fully automated simulation workflow to predicted solder joint lifetime. To further realize the fast assessment of reliability and component virtual release, an AI metamodel is derived from automated simulation-based DoE (Design of Experiments). For pursuit of accuracy for simulation models, the second industrial example presents the combination of Bayesian Optimization with BGA (Ball Grid Array) warpage calibration process to outperform the traditional manual methods. The third industrial example outlines another application of Bayesian optimization into the Zth (Transient Thermal Impedance) calibration process for component thermal models. Utilizing the multi-objective optimization algorithm, the Zth c

关键词： Electronic Components Simulation automation Solder Joint Reliability AI Thermal Management BGA Chip-resistor ECU Automotive Electronics Ansys Hybrid Modeling

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A physics-informed, vision-based method to reconstruct all deformation modes in slender bodies 39

A physics-informed, vision-based method to reconstruct all d...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Kim, Seung Hyun Chang, Heng-Sheng Shih, Chia-Hsien Uppalapati, Naveen Kumar Halder, Udit Krishnan, Girish Mehta, Prashant G. Gazzola, Mattia Univ Illinois Mech Sci & Engn Champaign IL 61801 USA Univ Illinois Coordinated Sci Lab Champaign IL USA

ISBN: (纸本)9781728196817

This paper is concerned with the problem of estimating (interpolating and smoothing) the shape (pose and the six modes of deformation) of a slender flexible body from multiple camera measurements. This problem is important in both biology, where slender, soft, and elastic structures are ubiquitously encountered across species, and in engineering, particularly in the area of soft robotics. The proposed mathematical formulation for shape estimation is physics-informed, based on the use of the special Cosserat rod theory whose equations encode slender body mechanics in the presence of bending, shearing, twisting and stretching. The approach is used to derive numerical algorithms which are experimentally demonstrated for fiber reinforced and cable-driven soft robot arms. These experimental demonstrations show that the methodology is accurate (<5 mm error, three times less than the arm diameter) and robust to noise and uncertainties.

关键词： Uncertainty Three-dimensional displays Smoothing methods Shape Shape measurement Soft robotics Bending

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Time Series Classification and Forecasting Method Selection in the Task of Intellectual Systems Development

Time Series Classification and Forecasting Method Selection ...

引用

2024 international Russian automation conference, RusAutoCon 2024

作者： Sergeev, Pavel S. Yarushkina, Nadezhda G. Ulyanovsk State Technical University Information Systems department Ulyanovsk Russia

Nowadays, it is important to implement intellectual analysis methods in information systems of different areas. Processes in such systems are described by temporal data and can be presented in the form of time series. While analyzing those time series, one of the main tasks is forecasting. There are many forecasting methods and models known. This variety poses for a researcher a problem of choice of an efficient one. This paper proposes the model of the forecasting method selection based on valuable time series characteristics. The proposed model can be implemented as a multiclass classifier via neural networks such as a multilayer perceptron. Different multilayer perceptron architectures are presented in this paper. A comparison of their performances using the KFold method is also provided. © 2024 IEEE.

关键词： Prediction models

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Autonomous Vehicle Parking in Dynamic Environments: An Integrated System with Prediction and Motion Planning 39

Autonomous Vehicle Parking in Dynamic Environments: An Integ...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Leu, Jessica Wang, Yebin Tomizuka, Masayoshi Di Cairano, Stefano Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA Mitsubishi Elect Res Labs Cambridge MA 02139 USA

ISBN: (纸本)9781728196817

This paper presents an integrated motion planning system for autonomous vehicle (AV) parking in the presence of other moving vehicles. The proposed system includes 1) a hybrid environment predictor that predicts the motions of the surrounding vehicles and 2) a strategic motion planner that reacts to the predictions. The hybrid environment predictor performs short-term predictions via an extended Kalman filter and an adaptive observer. It also combines short-term predictions with a driver behavior cost-map to make long-term predictions. The strategic motion planner comprises 1) a model predictive control-based safety controller for trajectory tracking;2) a search-based retreating planner for finding an evasion path in an emergency;3) an optimization-based repairing planner for planning a new path when the original path is invalidated. Simulation validation demonstrates the effectiveness of the proposed method in terms of initial planning, motion prediction, safe tracking, retreating in an emergency, and trajectory repairing.

关键词： Trajectory tracking Predictive models Observers Planning Trajectory Safety Kalman filters

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Adaptive Dynamic Programming-Based Distributed Coordinated Control for Dual-Arm Reconfigurable Manipulators 6

Adaptive Dynamic Programming-Based Distributed Coordinated C...

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6th international conference on robotics, Control and automation Engineering, RCAE 2023

作者： Liu, Guanting Li, Yuanchun Qu, Meng An, Tianjiao Zhu, Mingchao Ma, Bing Changchun University of Technology Department of Control Science and Engineering Changchun China Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Department of Control Science and Engineering Changchun China

ISBN: (纸本)9798350315301

In this paper, a distributed coordinated control method of dual-arm reconfigurable manipulators based on adaptive dynamic programming is proposed. Through kinematic analysis, the dynamic models of the reconfigurable manipulators and the grasped object are established, respectively. According to the load distribution method, the motion induction force is effectively distributed on each arm. Then, the dynamic model of a single reconfigurable manipulator is obtained. The performance index function is defined to reflect the joint position tracking error and internal force tracking error. The neural network is utilized to approximate the performance index function to obtain the optimal control strategy through the Policy Iteration (PI) algorithm. Thus, a distributed optimal coordinated controller is acquired. The tracking error of the manipulator system is proved be ultimately uniformly bounded (UUB) through Lyapunov's stability. Finally, the effectiveness of the developed control method is verified by simulations. © 2023 IEEE.

关键词： Dynamic models

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