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

共 24757 条记录，以下是551-560 订阅

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Predictive model based on machine learning for raw material purchasing management in the retail sector. 24

Predictive model based on machine learning for raw material ...

引用

2024 international conference on Advanced robotics, automation Engineering and Machine Learning, ARAEML 2024

作者： Antunez, Julio C. Salazar, Johnny D. Castañeda, Pedro S. Facultad de Ingeniería de Sistemas de Información Universidad Peruana de Ciencias Aplicadas Lima Peru

ISBN: (纸本)9798400717116

Making raw material purchase forecasts for companies is very difficult and, if inadequately controlled, can affect the company's decision making and profitability. Currently, there are optimized systems or mathematical models to try to predict the demands and solve this problem. In this study, a raw material purchase prediction model is proposed that uses the Elastic Net algorithm to analyze historical sales and inventory data. The model is used to improve prediction accuracy, allowing SMEs to optimize inventories, reduce costs and improve efficiency. Experimental results indicate that the proposed model obtains better results in the MAE, RMSE and R2 indicators. © 2024 ACM.

关键词： Prediction models

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A Linearization of Centroidal Dynamics for the Model-Predictive Control of Quadruped Robots 39

A Linearization of Centroidal Dynamics for the Model-Predict...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Chi, Wanchao Jiang, Xinyang Zheng, Yu Tencent Robot X Shenzhen Guangdong Peoples R China

ISBN: (纸本)9781728196817

Centroidal dynamics, which describes the overall linear and angular motion of a robot, is often used in locomotion generation and control of legged robots. However, the equation of centroidal dynamics contains nonlinear terms mainly caused by the robot's angular motion and needs to be linearized for deriving a linear model-predictive motion controller. This paper proposes a new linearization of the robot's centroidal dynamics. By expressing the angular motion with exponential coordinates, more linear terms are identified and retained than in the existing methods to reduce the loss from the model linearization. As a consequence, a model-predictive control (MPC) algorithm is derived and shows a good performance in tracking angular motions on a quadruped robot.

关键词： Legged locomotion automation Tracking Attitude control Robot kinematics Heuristic algorithms Dynamics

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Elastic Tracker: A Spatio-temporal Trajectory Planner for Flexible Aerial Tracking 39

Elastic Tracker: A Spatio-temporal Trajectory Planner for Fl...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Ji, Jialin Pan, Neng Xu, Chao Gao, Fei Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Zhejiang Univ Huzhou Inst Huzhou 313000 Peoples R China

ISBN: (纸本)9781728196817

This paper proposes Elastic Tracker, a flexible trajectory planning framework that can deal with challenging tracking tasks with guaranteed safety and visibility. Firstly, an object detection and intension-free motion prediction method is designed. Then an occlusion-aware path finding method is proposed to provide a proper topology. A smart safe flight corridor generation strategy is designed with the guiding path. An analytical occlusion cost is evaluated. Finally, an effective trajectory optimization approach enables to generate a spatiotemporal optimal trajectory within the resultant flight corridor. Particular formulations are designed to guarantee both safety and visibility, with all the above requirements optimized jointly. The experimental results show that our method works more robustly but with less computation than the existing methods, even in some challenging tracking tasks.

关键词： Costs automation Tracking Trajectory planning Prediction methods Object detection Safety

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Underwater Hyperspectral Imaging for Measuring Seafloor Reflectance

Underwater Hyperspectral Imaging for Measuring Seafloor Refl...

引用

2024 international conference on Intelligent Robots and Systems

作者： Zhang, Hongjie Billings, Gideon Shields, Jackson Williams, Stefan Univ Sydney Australian Ctr Field Robot Sydney NSW Australia

ISBN: (纸本)9798350377712;9798350377705

A known challenge for computer vision methods applied to the underwater domain is that nonlinear attenuation of light in underwater environments distorts the color signal in captured imagery, resulting in inconsistent color and contrast at varying distances to an imaged target. While surface reflectance can provide a useful cue for classifying imagery of the seafloor by object or substrate types, color inconsistency makes robust classification challenging. We introduce a method that leverages hyperspectral imagery with an underwater light formation model and structure from motion to estimate the intrinsic optical properties of the underwater environment and correct seafloor reflectance estimates from radiance measurements. We show that our method enables consistent surface reflectance estimates under both artificial and ambient lighting conditions and is readily integrated on small underwater vehicle platforms, such as a BlueROV.

关键词： Marine robotics Computer Vision for automation Environment Monitoring and Management Mapping

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Novel Approach for Intelligent Fault Diagnosis in Electromechanical Drive Systems Using an Attention-Based Residual 1D Convolutional Neural Network 4

Novel Approach for Intelligent Fault Diagnosis in Electromec...

引用

4th international conference on Artificial Intelligence, robotics, and Communication, ICAIRC 2024

作者： Okonda, Jonathan Xu, Danping Kilundu, Bovic Shanghai University School of Mechatronic Engineering and Automation Shanghai China Department of Mechanical Engineering Brussels Belgium

ISBN: (纸本)9798331531225

Numerous existing deep learning-based fault diagnosis models, have been implemented for intelligent fault diagnosis in electromechanical drive systems (EMDS). However, these models often are designed to detect and diagnose single fault types at specific operating conditions. These models are frequently susceptible to overfitting, suffer from the vanishing gradient problem, and struggle with long-range feature dependencies. Such limitations significantly hinder their accuracy and reliability in diagnosing complex fault scenarios for EMDS under different operating conditions using noisy data. To address these limitations, we propose a novel deep learning-based fault diagnosis model named Attention-based Residual 1D Convolutional Neural Network (AR1D-CNN). This model is designed to effectively diagnose complex faults in EMDS across various load conditions using noisy and imbalanced vibration data. Experimental results demonstrate exceptional classification accuracies of 99.98% and 100.00% on the KAIST dataset for 0 and 2 Nm load conditions, respectively, and 99.31% on the AETWPSU broken rotor bar dataset. Notably, the AR1D-CNN outperforms existing state-of-the-art methods by approximately 4% on the AETWPSU dataset, highlighting its robustness and reliability. This research significantly enhances predictive maintenance strategies by enabling early and precise fault detection, ultimately improving the operational efficiency of EMDS. © 2024 IEEE.

关键词： Convolutional neural networks

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Evaluation on Parameter-Efficient Continual Instruction Tuning of Large Language models 5

Evaluation on Parameter-Efficient Continual Instruction Tuni...

引用

5th international conference on Control, robotics, and Intelligent System, CCRIS 2024

作者： Ren, TianXiang Song, XingShen Shi, JiangYong Deng, JinSheng Cao, JiHao College of Computer Science and Technology National University of Defense Technology ChangSha410073 China College of Advanced Interdisciplinary Studies National University of Defense Technology ChangSha410073 China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

Recent years have witnessed a spurt in large language models for its strong generalization performance, many continual instruction tuning methods based on parameter-efficient tuning have been proposed to further push large language models towards artificial general intelligence. However, comprehensive assessments of recent advancements in these methods are notably lacking. To fill the gap, a three-demensional (average performance, continual learning proficiency and general ability delta) evaluation protocol are introduced based on two task streams, which include wide-span tasks and long sequence tasks. Meanwhile, three continual instruction tuning methods following different strategies are thoroughly evaluated on three distinct language models. The empirical analysis reveals that regularization-based methods are well-suited for wide-range task streams, while replay-based methods excel in long sequence task streams, particularly for tasks of rich logic reasoning in maintaining general ability. Simultaneously, the study underscores the need for new continual intruction tuning methods based on parameter-efficient tuning that balance performance on new tasks with the preservation of general capabilities, especially for more sophisticated architecture-based method . © 2024 SPIE.

关键词： Contrastive Learning

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Topologically-Informed Atlas Learning 39

Topologically-Informed Atlas Learning

引用

IEEE international conference on robotics and automation (ICRA)

作者： Cohn, Thomas Devraj, Nikhil Jenkins, Odest Chadwicke Univ Michigan Robot Inst Dept Elect Engn & Comp Sci Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9781728196817

We present a new technique that enables manifold learning to accurately embed data manifolds that contain holes, without discarding any topological information. Manifold learning aims to embed high-dimensional data into a lower dimensional Euclidean space by learning a coordinate chart, but it requires that the entire manifold can be embedded in a single chart. This is impossible for manifolds with holes. In such cases, it is necessary to learn an atlas: a collection of charts that collectively cover the entire manifold. We begin with many small charts, and combine them in a bottom-up approach, where charts are only combined if doing so will not introduce problematic topological features. When it is no longer possible to combine any charts, each chart is individually embedded with standard manifold learning techniques, completing the construction of the atlas. We show the efficacy of our method by constructing atlases for challenging synthetic manifolds;learning human motion embeddings from motion capture data;and learning kinematic models of articulated objects.

关键词： Manifolds Data analysis automation Feature extraction Motion capture Manifold learning Task analysis

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Towards Optimal Correlational Object Search 39

Towards Optimal Correlational Object Search

引用

IEEE international conference on robotics and automation (ICRA)

作者： Zheng, Kaiyu Chitnis, Rohan Sung, Yoonchang Konidaris, George Tellex, Stefanie Brown Univ Providence RI 02912 USA MIT CSAIL Cambridge MA 02139 USA

ISBN: (纸本)9781728196817

In realistic applications of object search, robots will need to locate target objects in complex environments while coping with unreliable sensors, especially for small or hard-todetect objects. In such settings, correlational information can be valuable for planning efficiently. Previous approaches that consider correlational information typically resort to ad-hoc, greedy search strategies. We introduce the Correlational Object Search POMDP (COS-POMDP), which models correlations while preserving optimal solutions with a reduced state space. We propose a hierarchical planning algorithm to scale up COSPOMDPs for practical domains. Our evaluation, conducted with the AI2-THOR household simulator and the YOLOv5 object detector, shows that our method finds objects more successfully and efficiently compared to baselines, particularly for hard-todetect objects such as srub brush and remote control.

关键词： Correlation Brushes automation Detectors Aerospace electronics Search problems Robot sensing systems

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Research on Adaptive On-Demand Assistive Control Strategy for Upper Limb Rehabilitation Robot 4

Research on Adaptive On-Demand Assistive Control Strategy fo...

引用

4th international conference on Artificial Intelligence, robotics, and Communication, ICAIRC 2024

作者： Zheng, Haoyue Wang, Zhiming Shanghai University School of Mechatronic Engineering and Automation China

ISBN: (纸本)9798331531225

Currently, upper limb exoskeleton rehabilitation robots provide the same level of assistance to different patients during active rehabilitation training, which prevents patients from fully utilizing their own initiative and thus affects the rehabilitation effect. To address this issue, this paper proposes an adaptive on-demand assistive control strategy based on impedance control for upper limbs. By establishing two modules of on-demand assistive control and trajectory tracking control, combined with methods of assessing limb movement state and on-demand control to adapt to the needs of patients at different stages of rehabilitation, the system achieves automatic adjustment of the assistive force size through synovial control, thereby maximizing the patient's moment of main force. The experimental results show that the adaptive assistive force system, compared with traditional methods, provides an average assistive force that is reduced by 41.9% under the same limb movement state coefficient, and can gradually reduce the assistive force provided according to the patient's recovery of motor ability. This indicates that the method is highly adaptable to different patients and can effectively enhance the patient's initiative in rehabilitation training, thereby improving the rehabilitation effect. © 2024 IEEE.

关键词： Exoskeleton (robotics)

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Research on Path Tracking Control Method of Fully Driven AUV under Ocean Current Interference 7

Research on Path Tracking Control Method of Fully Driven AUV...

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7th international conference on Intelligent robotics and Control Engineering, IRCE 2024

作者： Zheng, Wanxi Automation Research Institute Lianyungang China

ISBN: (纸本)9798350352399

Autonomous underwater vehicles (AUVs) play an important role in human understanding and management of the ocean. Fully actuated AUVs can achieve 6 degrees of freedom motion control, with high control accuracy and anti-interference ability, and have high application value in the field of underwater precision operations. This article vectorizes the modeling of a multi thruster fully driven underwater vehicle, establishes a path tracking error model in a non-projective Serret Frenet coordinate system, designs disturbance resistant kinematic and dynamic controllers using inverse control methods, and analyzes the stability of the designed controllers. The simulation results show that the controller can asymptotically stabilize path tracking error, velocity tracking error, and attitude tracking error. © 2024 IEEE.

关键词： Disturbance rejection

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