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

共 24666 条记录，以下是4781-4790 订阅

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A GNN Based Voltage Sensitivity Perception Method for Distribution Networks with Variable Topology

A GNN Based Voltage Sensitivity Perception Method for Distri...

引用

Electrical automation and Artificial Intelligence (ICEAAI), international conference on

作者： Keyang Li Chuanhuai Ji Shuona Li Yajie Tang College of Electrical Engineering Zhejiang University Hangzhou China State Grid Zhejiang Electric Power Co. Ltd. Research Institute Hangzhou China

ISBN: (数字)9798331506797

ISBN: (纸本)9798331506803

Traditional data-driven voltage sensitivity analysis methods exhibit limited adaptability in response to network topology changes, which need to retrain the neural networks according to the updated topology information. To address this issue, this paper proposes a voltage sensitivity perception method based on graph neural networks (GNN). By embedding prior topology knowledge for information propagation, the method can effectively capture the feature mapping patterns of various topologies, thereby demonstrating improved model generalization ability in unknown topology scenarios. Matlab/Simulation results show that, compared to conventional data-driven algorithms, the proposed method achieves faster and more accurate sensitivity calculations in time-varying topology scenarios.

关键词： Adaptation models Sensitivity Accuracy Voltage measurement Network topology Fitting Graph neural networks Mathematical models Data models Topology

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Dynamic Modelling of Mixed Rigid-Flexible Joint Robotic Manipulator Using Recursive Newton-Euler Formulation

Dynamic Modelling of Mixed Rigid-Flexible Joint Robotic Mani...

引用

international conference on Autonomous Robots and Agents, ICARA

作者： Minh Tuan Hua Mohammad Poursina Filippo Sanfilippo Department of Engineering Sciences University of Agder Grimstad Norway

ISBN: (数字)9798350394245

ISBN: (纸本)9798350394252

Rigid joints have good position control accuracy due to their stiffness. On the other hand, elastic joints are advantageous when interacting with the environment due to their compliance characteristics. Most of the current robot arms use all rigid joints or all elastic joints in their designs. This work presents a highly efficient approach to formulate both inverse and forward dynamics of robots with mixed rigid-elastic joints using recursive Newton-Euler algorithm. To simplify the modelling process, a unified rigid body is proposed, where the link and all motors attached to it are unified as a whole unyielding entity. In addition, the effect of gear ratio is considered in the development of this modelling approach. Successively, an inverse dynamics controller is presented. Finally, simulations are conducted based on the proposed modelling method and the inverse dynamics control algorithm.

关键词： Adaptation models Gears Heuristic algorithms Computational modeling Position control Motors Mathematical models

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An Application Study on Reconfigurable Robotic Workcells and Policy Adaptation for Electronic Waste Recycling

An Application Study on Reconfigurable Robotic Workcells and...

引用

IEEE conference on Cybernetics and Intelligent Systems

作者： Mihael Simonič Boris Kuster Matija Mavsar Gašper Šavle Sebastian Ruiz Martin Bem Matevž Majcen Hrovat Aleš Ude Department of Automatics Biocybernetics and Robotics Jožef Stefan Institute Ljubljana Slovenia Department for Computational Neuroscience University of Göttingen Germany

ISBN: (数字)9798350364194

ISBN: (纸本)9798350364200

The recycling of electronic waste (e-waste) presents significant challenges due to the diverse range of device models and conditions that need to be treated. This paper presents an application study that evaluates a reconfigurable modular robotic workcell platform and adaptation at different levels to address these challenges. The performance and effectiveness of the approach are assessed through two common use cases from the e-waste recycling industry: heat cost allocator disassembly and smoke detector disassembly, with the goal of battery removal. The initial setup time (the definition of dismantling procedures for a new device type), reconfiguration times (changing the workcell layout to switch between processes for different known device types) and cycle times (for dismantling one device) were assessed in terms of their key performance indicators (KPIs). The evaluation demonstrated the flexibility and adaptability of the workcell, which enables streamlined process development and efficient disassembly of electronic devices in different scenarios.

关键词： Mechatronics Service robots Layout Key performance indicator Random access memory Switches Electronic waste

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A Hybrid Admittance Control Algorithm for Automatic Robotic Cranium-Milling

A Hybrid Admittance Control Algorithm for Automatic Robotic ...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Chen Qian Zhen Li Qiang Ye Peicong Ge Jizong Zhao Gui-Bin Bian Institute of Automation Chinese Academy of Sciences Beijing China China National Clinical Research Center for Neurological Diseases Beijing Tiantan Hospital Capital Medical University Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Prior robot-assisted cranium-milling studies only considered controlling the force in the skull’s vertical direction and neglected the milling cutter’s feed force. Additionally, achieving stable force control in multiple directions is challenging for robots due to the uneven skull surface. Here a hybrid admittance control algorithm incorporating a model-free adaptive nonlinear force control and fuzzy control algorithms is proposed to accomplish effective automatic cranial-milling tasks. First, a pure data-driven model-free adaptive control method based on partial form dynamic linearization is used to control the feed force. Second, fuzzy control minimizes the total error of both the vertical and feed force by adaptively adjusting the milling cutter’s velocity and position. 42 ex vivo animal skull-milling experiments conducted by the automatic robotic cranium-milling system indicate that when using the proposed control algorithm, the force error percentage can be maintained below 5.0% within 3 s and the maximal root mean square error percentages for vertical and feed force are 1.85% and 1.94%, respectively. Moreover, no instances of dura mater damage are observed and the robotic system exhibits a high level of autonomy as it performs the skull milling task with minimal human involvement throughout the entire experiment. The results suggest the potential for advancing the intelligence level of neurosurgery in the future.

关键词： Fuzzy control Adaptation models Force Milling Skull Feeds Task analysis

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MF-MOS: A Motion-Focused Model for Moving Object Segmentation

MF-MOS: A Motion-Focused Model for Moving Object Segmentatio...

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IEEE international conference on robotics and automation (ICRA)

作者： Jintao Cheng Kang Zeng Zhuoxu Huang Xiaoyu Tang Jin Wu Chengxi Zhang Xieyuanli Chen Rui Fan School of Electronic and Information Engineering South China Normal University Foshan China Department of Computer Science Aberystwyth University Aberystwyth U.K. Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China School of Internet of Things Engineering Jiangnan University Wuxi China College of Intelligence Science and Technology National University of Defense Technology Changsha China College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Moving object segmentation (MOS) provides a reliable solution for detecting traffic participants and thus is of great interest in the autonomous driving field. Dynamic capture is always critical in the MOS problem. Previous methods capture motion features from the range images directly. Differently, we argue that the residual maps provide greater potential for motion information, while range images contain rich semantic guidance. Based on this intuition, we propose MF-MOS, a novel motion-focused model with a dual-branch structure for LiDAR moving object segmentation. Novelly, we decouple the spatial-temporal information by capturing the motion from residual maps and generating semantic features from range images, which are used as movable object guidance for the motion branch. Our straightforward yet distinctive solution can make the most use of both range images and residual maps, thus greatly improving the performance of the LiDAR-based MOS task. Remarkably, our MF-MOS achieved a leading IoU of 76.7% on the MOS leaderboard of the SemanticKITTI dataset upon submission, demonstrating the current state-of-the-art performance. The implementation of our MF-MOS has been released at https://***/SCNU-RISLAB/MF-MOS.

关键词： Laser radar Semantics Dynamics Object segmentation Data augmentation Data models Reliability

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Kalman Filter Adaptive Speed Tracking Control for High-speed Trains with Noise Interference

Kalman Filter Adaptive Speed Tracking Control for High-speed...

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IEEE international conference of Intelligent Robotic and Control Engineering (IRCE)

作者： Chunli Zhang Yuwei Xie Lei Yan Fucai Qian College of Automation and Information Engineering Xi’an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an China

ISBN: (数字)9798350352399

ISBN: (纸本)9798350352405

In this paper, high-speed train is regarded as a single prime point, a new tracking control method combining adaptive control and Kalman filtering is proposed. This paper solves the noise interference problem in the tracking control process of high-speed train. The method first linearises the original system, then uses Kalman filtering to do model estimation, and the controller is designed for the predictive model through adaptive control. Finally, MATLAB is used to simulate and verify the effectiveness of this method. This proposed method successfully solves the problems of nonlinearity, noise interference and unknown parameters in system. The error caused by resistance in the high-speed train tracking control process can be dealt with effectively.

关键词： Resistance Filtering Noise Process control Interference Predictive models Mathematical models Kalman filters Adaptive control MATLAB

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An Interval Shrinking Trust Region Algorithm for GNSS/eLoran Pseudorange Fusion Positioning Initialization

An Interval Shrinking Trust Region Algorithm for GNSS/eLoran...

引用

automation, robotics and Computer Engineering (ICARCE), international conference on

作者： Kaiqi Liu Wenhe Yan Jiangbin Yuan Zaihui Xiao Chaozhong Yang Yu Hua Chinese Academy of Sciences National Time Service Center Xi’an China Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Key Laboratory of Precise Positioning and Timing Technology Xi’an China Chinese Academy of Sciences National Time Service Cente Key Laboratory of Precise Positioning and Timing Technology Xi’an China

ISBN: (纸本)9781665475495

Fusion of Global Navigation Satellite System (GNSS) with eLoran can greatly improve the coverage and availability of Positioning Navigation and Timing (PNT) services. However, due to the strong nonlinearity in the eLoran pseudorange equations, traditional methods may fail to converge or converge incorrectly when solving the fused pseudorange equation system. In this paper, an interval shrinking trust region algorithm (ISTR) is proposed to solve the pseudorange-based eLoran/GNSS fusion positioning problem, especially when no reliable initial values are available. Simulation and measured data verify that the ISTR algorithm can help the receiver to complete reliable positioning initialization without reliable initial values, and the initialization success rate is 100%.

关键词： Global navigation satellite system Receivers Interference Position measurement Mathematical models Data models Timing

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GUTS: Generalized Uncertainty-Aware Thompson Sampling for Multi-Agent Active Search

GUTS: Generalized Uncertainty-Aware Thompson Sampling for Mu...

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IEEE international conference on robotics and automation (ICRA)

作者： Nikhil Angad Bakshi Tejus Gupta Ramina Ghods Jeff Schneider Robotics Institute School of Computer Science Carnegie Mellon University Pittsburgh PA

Robotic solutions for quick disaster response are essential to ensure minimal loss of life, especially when the search area is too dangerous or too vast for human rescuers. We model this problem as an asynchronous multi-agent active-search task where each robot aims to efficiently seek objects of interest (OOIs) in an unknown environment. This formulation addresses the requirement that search missions should focus on quick recovery of OO1s rather than full coverage of the search region. Previous approaches fail to accurately model sensing uncertainty, account for occlusions due to foliage or terrain, or consider the requirement for heterogeneous search teams and robustness to hardware and communication failures. We present the Generalized Uncertainty-aware Thompson Sampling (GUTS) algorithm, which addresses these issues and is suitable for deployment on heterogeneous multi-robot systems for active search in large unstructured environments. We show through simulation experiments that GUTS consistently outperforms existing methods such as parallelized Thompson Sampling and exhaustive search, recovering all OOIs in 80% of all runs. In contrast, existing approaches recover all OOIs in less than 40% of all runs. We conduct field tests using our multirobot system in an unstructured environment with a search area of ≈75,000 m 2 . Our system demonstrates robustness to various failure modes, achieving full recovery of OOIs (where feasible) in every field run, and significantly outperforming our baseline.

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Decision-making strategy for multi-agents using a probabilistic approach: application in soccer robotics

Decision-making strategy for multi-agents using a probabilis...

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international conference on Control, automation and Information Sciences (ICCAIS)

作者： Hoang Anh Pham Valentin Gies Thierry Soriano University of Toulon Toulon France

The efficient coordination of soccer robots is a complex topic because there are numerous possible scenarios in the game, and the state of the robots can change rapidly. It requires the robot to be able to analyze and make decisions in a short time. In this article, we first use Dec-POMDP to describe the actions and states of the soccer robot team. Secondly, we introduce a probabilistic approach so that the robots can quickly make decisions corresponding to specific situations. More specifically, we present a method for calculating and evaluating the expected points corresponding to each particular action for each robot. The robots then choose the actions with the highest expected points. Finally, we have developed a simulator based on the digital twin approach to verify the proposed strategies on simulation models and implement these strategies rapidly on real robots.

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Evaluation of a Data-Driven Model for Deformable Linear Objects Manipulated by Two Robot Manipulators Using Experimental Data

Evaluation of a Data-Driven Model for Deformable Linear Obje...

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international conference on Control, automation and Systems ( ICCAS)

作者： Jiyoung Choi G. Micheale Haileslassie Geon Kim Ayoung Hong Department of Mechanical Engineering Chonnam National University Gwangju South Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Deformable objects such as cables, ropes, and cloth-like objects are more commonly used in our daily lives rather than rigid bodies. However, manipulating these deformable objects with a robot is challenging due to their high degrees of freedom and complex deformations, making it difficult to generate dynamic models using traditional analytical methods. Data-driven models have been employed to develop dynamic models for such deformable objects. However, to learn the models from experimental data, it is recommended to reduce the number of variables. In this paper, we established an experimental environment where deformable linear objects (DLOs) can be manipulated using a dual-arm robot. We evaluated the performance of the data-driven model using the positional information of the objects obtained in this setup. We achieved an average position error of 0.010 m for forward prediction and 0.073 m for long-term prediction. In future research, we intend to employ this data-driven model to manipulate cables into desired shapes.

关键词： Deformable models Solid modeling automation Shape Deformation Predictive models Control systems Data models Manipulator dynamics Cables

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