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

共 24830 条记录，以下是3961-3970 订阅

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Investigating Fused Silica Bending Strength and Damping Characteristics on Resonators Fabricated Through Femtosecond Laser-Assisted Wet Etching: An Experimental Analysis

Investigating Fused Silica Bending Strength and Damping Char...

引用

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

作者： Loïc Amez-Droz Matéo Tunon de Lara Anthony Amorosi Pierre Lambert Christophe Caucheteur Christophe Collette Department of Aerospace and Mechanical Engi-neering Université de Liège Liège Belgium Interfaces & Processes Department Transfers Université libre de Brux-elles Brussels Belgium Electromagnetism and Telecommunication Department UMONS Mons Belgium BEAMS Department Université libre de Bruxelles Brussels Belgium

ISBN: (数字)9798350376807

ISBN: (纸本)9798350376814

Fused silica, renowned for its optical transparency and exceptional mechanical properties, including a high elastic range, challenges traditional material selection for compliant mechanisms. Leveraging femtosecond laser-assisted wet etching to machine three-dimensional fused silica structures, this study investigates the elastic range and damping characteristics of micro-scale monolithic bending specimens. Experimental results offer insights into the fused silica material application range for precision sensors and resonator design. Bending stress estimations are reported between 1.1 GPa and 2.7 GPa and a quality factor $Q=1.85\times 10^{5}$ at a pressure of $2\times 10^{-3}$ mbar.

关键词： Q-factor Damping Wet etching Optical resonators Estimation Bending Data models

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TRASH: Tandem Rover and Aerial Scrap Harvester

TRASH: Tandem Rover and Aerial Scrap Harvester

引用

robotics, automation and Artificial Intelligence (RAAI), IEEE international conference on

作者： Lee Milburn John Chiaramonte Jack Fenton Taskin Padir College of Engineering Northeastern University Boston Massachusetts

ISBN: (数字)9798350307566

ISBN: (纸本)9798350307573

Addressing the challenge of roadside litter in the United States, which has traditionally relied on costly and ineffective manual cleanup methods 1 1 https://***/***, this paper presents an autonomous multi-robot system for highway litter monitoring and collection. Our solution integrates an aerial vehicle to scan and gather data across highway stretches with a terrestrial robot equipped with a Convolutional Neural Network (CNN) for litter detection and mapping. Upon detecting litter, the ground robot navigates to each pinpointed location, re-assesses the vicinity, and employs a “greedy pickup” approach to address potential mapping inaccuracies or litter misplacements. Through simulation studies and real-world robotic trials, this work highlights the potential of our proposed system for highway cleanliness and management in the context of robotics, automation, and Artificial Intelligence.

关键词： Road transportation automation Navigation Wheels System integration Robot sensing systems Sensor systems

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Workpiece Recognition and Localization Based on Improved YOLOv7-Tiny Channel Pruning

Workpiece Recognition and Localization Based on Improved YOL...

引用

robotics, Control and automation Engineering (RCAE), international conference on

作者： Mingyao Teng Guoyang Wan Shoujun Bai Xuna Li Chengwen Wang Hanqi Li School of Electrical Engineering Anhui Polytechnic University Wuhu China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

At present, to address the problem of difficult detection of industrial parts and complex model with large computation, a workpiece recognition and detection algorithm based on improved YOLOv7-Tiny channel pruning is proposed. Firstly, the algorithm integrates the ECA module, an efficient channel attention mechanism, into the backbone network to better retain the information in transmission, so that the data features are more fully retained in the process of transmission, and thus the model can be optimized and the detection accuracy of the model can be improved; secondly, the lightweight up-sampling operator CARAFE is invoked to replace the nearest-neighbor difference of the original up-sampling in the structure of the PAFPN in order to improve the feature fusion ability of the model; finally, the improved model is subjected to channel pruning to reduce the number of parameters and computation of the model to further optimize the model. The experimental results show that our method achieves 81.5% recognition accuracy on the self-constructed dataset, and the number of parameters and computation amount decrease by 75.6% and 74.0%, respectively. The effectiveness of the method is proved.

关键词： Location awareness Accuracy Attention mechanisms Service robots Computational modeling Inspection Feature extraction Data models Computational efficiency Detection algorithms

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LK-ORB-SLAM3: An RGB-D Visual SLAM Algorithm Fusing Optical Flow Tracking and Feature Matching

LK-ORB-SLAM3: An RGB-D Visual SLAM Algorithm Fusing Optical ...

引用

robotics, Control and automation Engineering (RCAE), international conference on

作者： Juan Dai Shengqiang Sun Jingwei Liu Zhong Su Beijing Key Laboratory of High Dynamic Navigation Technology Beijing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing China School of Automation Beijing Information Science & Technology University Beijing China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

In response to the issue of poor real-time performance caused by the large computational load of feature-based methods, this paper proposed an RGB-D visual SLAM algorithm which integrates optical flow and feature-based methods. This algorithm combined optical flow with the feature-based method, effectively improving the real-time performance of the algorithm while maintaining high precision. Firstly, keyframes are matched using feature-based methods, and camera motion is computed by minimizing the reprojection error. For non-keyframes, keypoints are extracted without computing descriptors and tracked using the optical flow pyramid, and pose estimation is achieved by minimizing the photometric error. Secondly, a dual mechanism based on time and space is employed to execute keyframes insertion which ensures tracking stability. Additionally, an adaptive threshold algorithm is proposed to enhance tracking robustness in low-light environments. Experimental results on the TUM dataset indicated that, with comparable average localization accuracy, the proposed algorithm reduces average tracking cost by 37.19%, achieving real-time frame rates of up to 45 fps on mid-to-low-performance CPUs.

关键词： Location awareness Visualization Costs Accuracy Simultaneous localization and mapping Tracking Heuristic algorithms Real-time systems Optical flow Robots

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Finite element modeling and vibration reduction analysis of thin-walled structure with constraining layer damping

Finite element modeling and vibration reduction analysis of ...

引用

2024 8th international conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Ziyang Liu Yulin Liu Haitao Luo State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences (CAS) Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

Thin-walled structures are widely used in the engineering field, but due to their low stiffness and low damping, they are prone to vibration. The application of constrained layer damping (CLD) surface treatment can effectively improve the vibration suppression ability of thin-walled structures. This paper uses the carbon fiber composite plate as the research object of thin-walled structures and uses finite element method to model the cantilever plate with CLD. The composite element with four nodes and 28 degrees of freedom is used in the modeling. And the comparison of the frequency response and vibration mode obtained by the simulation method in this paper and the Nastran simulation software verifies the correctness of the modeling method. Finally, the optimized shape of the CLD is obtained based on the modal strain of the cantilever plate, verifying the rationality of the CLD configuration method.

关键词： Vibrations Damping Shape Modal analysis Mathematical models Software Finite element analysis Carbon Surface treatment Strain

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Learning Efficient Constraint Graph Sampling for Robotic Sequential Manipulation

Learning Efficient Constraint Graph Sampling for Robotic Seq...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Ortiz-Haro, Joaquim Hartmann, Valentin N. Oguz, Ozgur S. Toussaint, Marc Univ Stuttgart Machine Learning & Robot Lab Stuttgart Germany Max Planck Inst Intelligent Syst Stuttgart Germany TU Berlin Learning & Intelligent Syst Lab Berlin Germany

ISBN: (纸本)9781728190778

Efficient sampling from constraint manifolds, and thereby generating a diverse set of solutions for feasibility problems, is a fundamental challenge. We consider the case where a problem is factored, that is, the underlying nonlinear program is decomposed into differentiable equality and inequality constraints, each of which depends only on some variables. Such problems are at the core of efficient and robust sequential robot manipulation planning. Naive sequential conditional sampling of individual variables, as well as fully joint sampling of all variables at once (e.g., leveraging optimization methods), can be highly inefficient and non-robust. We propose a novel framework to learn how to break the overall problem into smaller sequential sampling problems. Specifically, we leverage Monte-Carlo Tree Search to learn assignment orders for the variable-subsets, in order to minimize the computation time to generate feasible full samples. This strategy allows us to efficiently compute a set of diverse valid robot configurations for mode-switches within sequential manipulation tasks, which are waypoints for subsequent trajectory optimization or sampling-based motion planning algorithms. We show that the learning method quickly converges to the best sampling strategy for a given problem, and outperforms user-defined orderings or fully joint optimization, while providing a higher sample diversity. Video: https://***/mCNdvjTbHNI

关键词： Manifolds Learning systems Costs Monte Carlo methods conferences Optimization methods Planning

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A Fast Calibration Method Based on Constraints for Magnetic Sensor Array for Positioning Capsule Endoscope

A Fast Calibration Method Based on Constraints for Magnetic ...

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2022 IEEE international conference on robotics and Biomimetics, ROBIO 2022

作者： Ren, Mingxin Wu, Xiaoyang Wang, Jiaole Song, Shuang School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9781665481090

The magnetic localization method is suitable for gastrointestinal endoscopy, and the magnetic sensor array can track the position and direction of the capsule in the body. In order to achieve an accurate result, the magnetic sensor needs to be calibrated in advance. However, the existing calibration methods universally demand a large number of samples with known magnet poses, and then use optimization algorithm to obtain calibrated coefficients. To simplify the calibration process, a fast calibration method is proposed in this paper, which does not require to know the specific information of the calibration points. By introducing a novel calibration tool to restrict the orientation of the magnet and the position of the rotating fixed point, the analytical solution of the sensitivity coefficient of the magnetic sensor can be calculated quickly. In this paper, the calibration coefficients under different magnetic rotation ranges have been calculated and compared, and the results verified the effectiveness of the proposed calibration method. © 2022 IEEE.

关键词： Calibration

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Highlight Removal with Orthogonal Decomposition 4

Highlight Removal with Orthogonal Decomposition

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4th international conference on Data-Driven Optimization of Complex Systems, DOCS 2022

作者： Zhang, Zhen Ren, Weihong Lu, Yang Zhou, Shijun Tang, Yandong Tian, Jiandong Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Shenyang China Shenzhen China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang China

ISBN: (数字)9781665459822

ISBN: (纸本)9781665459822

In this paper, based on orthogonal decomposition, we present a robust and effective method for highlight removal. First, we obtain the reflectance image of an image through orthogonal decomposition. Then, the reflectance image is used to cluster the image. According to the clustering results, illumination chromaticity is estimated. Finally, we separate diffuse and specular reflections per pixel according to the distance from each pixel chromaticity to illumination chromaticity, where the diffuse reflection image is the highlight removal image. According to our extensive experimental results, the proposed method outperforms all the existing state-of-the-art (SOTA) methods according to the Peak-Signal-to-Noise-Ratio (PSNR) and the Structural Similarity (SSIM) Index score. © 2022 IEEE.

关键词： Pixels

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Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach 41

Sequential Asynchronous Action Coordination in Multi-Agent S...

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41st international conference on Machine Learning, ICML 2024

作者： Zhang, Bin Mao, Hangyu Li, Lijuan Xu, Zhiwei Li, Dapeng Zhao, Rui Fan, Guoliang Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China SenseTime Research China School of Computer Science and Technology Shandong University China

Asynchronous action coordination presents a pervasive challenge in Multi-Agent Systems (MAS), which can be represented as a Stackelberg game (SG).However, the scalability of existing Multi-Agent Reinforcement Learning (MARL) methods based on SG is severely restricted by network architectures or environmental *** address this issue, we propose the Stackelberg Decision Transformer (STEER).It efficiently manages decision-making processes by incorporating the hierarchical decision structure of SG, the modeling capability of autoregressive sequence models, and the exploratory learning methodology of *** approach exhibits broad applicability across diverse task types and environmental configurations in *** results demonstrate both the convergence of our method towards Stackelberg equilibrium strategies and its superiority over strong baselines in complex scenarios. Copyright 2024 by the author(s)

关键词： Multi agent systems

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Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMs

Kinematic-aware Prompting for Generalizable Articulated Obje...

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IEEE international conference on robotics and automation (ICRA)

作者： Wenke Xia Dong Wang Xincheng Pang Zhigang Wang Bin Zhao Di Hu Xuelong Li Gaoling School of Artificial Intelligence Renmin University of China Shanghai Artificial Intelligence Laboratory Northwestern Polytechnical University Institute of Artificial Intelligence China Telecom Corp Ltd

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Generalizable articulated object manipulation is essential for home-assistant robots. Recent efforts focus on imitation learning from demonstrations or reinforcement learning in simulation, however, due to the prohibitive costs of real-world data collection and precise object simulation, it still remains challenging for these works to achieve broad adaptability across diverse articulated objects. Recently, many works have tried to utilize the strong in-context learning ability of Large Language models (LLMs) to achieve generalizable robotic manipulation, but most of these researches focus on high-level task planning, sidelining low-level robotic control. In this work, building on the idea that the kinematic structure of the object determines how we can manipulate it, we propose a kinematic-aware prompting framework that prompts LLMs with kinematic knowledge of objects to generate low-level motion trajectory waypoints, supporting various object manipulation. To effectively prompt LLMs with the kinematic structure of different objects, we design a unified kinematic knowledge parser, which represents various articulated objects as a unified textual description containing kinematic joints and contact location. Building upon this unified description, a kinematic-aware planner model is proposed to generate precise 3D manipulation waypoints via a designed kinematic-aware chain-of-thoughts prompting method. Our evaluation spanned 48 instances across 16 distinct categories, revealing that our framework not only outperforms traditional methods on 8 seen categories but also shows a powerful zero-shot capability for 8 unseen articulated object categories with only 17 demonstrations. Moreover, the real-world experiments on 7 different object categories prove our framework’s adaptability in practical scenarios. Code is released at https://***/GeWu-Lab/LLM_articulated_object_manipulation.

关键词： Solid modeling Three-dimensional displays Large language models Imitation learning Kinematics Reinforcement learning Trajectory

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