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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541-550 订阅

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2023 8th international conference on robotics and automation Engineering, ICRAE 2023

2023 8th International Conference on Robotics and Automation...

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8th international conference on robotics and automation Engineering, ICRAE 2023

ISBN: (纸本)9798350327656

The proceedings contain 50 papers. The topics discussed include: an improved rapidly-exploring random tree star algorithm for manipulator path planning;a robust robot system via multi-sensor fusion localization and optimized path planning;design of a medical expert system to consult selecting an examination department and to provide the path signal for a mobile robot to lead patients to the consulted department;joint delivery path optimization based on improved particle swarm optimization algorithm;slipping control of tracked vehicles in shallow water areas;towards multimodal multitask scene understanding models for indoor mobile agents;gearbox fault diagnosis based on local domain adaptation network under different working conditions;coordinated tuning of slurry shield control parameters based on reinforcement learning;and whole body motion control strategy of humanoid robot based on double-layer quadratic optimization.

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dSEDA: a Differential Series Elastic Damped Actuator 39

dSEDA: a Differential Series Elastic Damped Actuator

引用

IEEE international conference on robotics and automation (ICRA)

作者： Monteleone, Simone Negrello, Francesca Grioli, Giorgio Catalano, Manuel G. Univ Pisa Res Ctr E Piaggio Pisa Italy Fdn Ist Italiano Tecnol Res Ctr Genoa Italy

ISBN: (数字)9781728196817

ISBN: (纸本)9781728196817

Compliant actuation bestows robots with the ability to cope with unstructured environments, move with agility, and interact safely with humans at the expense of reduced tracking accuracy. The inclusion of dampening components aims to reduce oscillatory dynamics and partially restore precision without sacrificing the previously obtained characteristics. This paper introduces the concept and design of a novel damped compliant actuator suitable for building multi-degree of freedom systems. The proposed unit has a unique actuator topology that has never been seen before in the literature. The gearbox is used as a differential component, allowing the design of compact units without giving up safety and accuracy enhancements. We present and analyze the actuator's model and experimentally characterize the actuator prototype and the elastic and damping component.

关键词： Actuators Analytical models Torque Tracking Prototypes Topology Safety

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Rendering Virtual Inertia in Haptic Interfaces: Analysis and Limitations 39

Rendering Virtual Inertia in Haptic Interfaces: Analysis and...

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IEEE international conference on robotics and automation (ICRA)

作者： Juan Gil, Jorge Ugartemendia, Axier Diaz, Inaki Univ Navarra Tecnun Sch Engn Paseo Manuel Lardizabal 13 San Sebastian 20018 Spain CEIT Basque Res & Technol Alliance BRTA Paseo Manuel Lardizabal 15 San Sebastian 20018 Spain

ISBN: (纸本)9781728196817

Virtual environments designed for haptic applications are usually rendered as a combination of spring and damper elements. The resulting haptic experience can be greatly enhanced by also adding virtual inertia, for example when interacting with mobile virtual objects. This paper analyzes the impact of implementing virtual inertia on haptic rendering stability. It describes the methodology followed to identify the physical inertia of a mechanism, to derive the acceleration from position, and the implications of this process on stability. Main results show how digital filtering and internal flexibility of the device affect the expected uncoupled stability region.

关键词： Filtering Virtual environments Predictive models Rendering (computer graphics) Stability analysis Shock absorbers Haptic interfaces

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HGC-Net: Deep Anthropomorphic Hand Grasping in Clutter 39

HGC-Net: Deep Anthropomorphic Hand Grasping in Clutter

引用

IEEE international conference on robotics and automation (ICRA)

作者： Li, Yiming Wei, Wei Li, Daheng Wang, Peng Li, Wanyi Zhong, Jun Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Chinese Acad Sci CAS Ctr Excellence Brain Sci & Intelligence Techn Shanghai Peoples R China Chinese Acad Sci Ctr Artificial Intelligence & Robot Hong Kong Inst Sci & Innovat Hong Kong Peoples R China

ISBN: (纸本)9781728196817

Grasping in cluttered environments is one of the most fundamental skills in robotic manipulation. Most of the current works focus on estimating grasp poses for parallel-jaw or suction-cup end effectors. However, the study for dexterous anthropomorphic hand grasping in clutter remains a great challenge. In this paper, we propose HGC-Net, a single-shot network that learns to predict dense hand grasp configurations in clutter from single-view point cloud input. Our end-to-end neural network can predict hand grasp proposals efficiently and effectively. To enhance generalization, we built a largescale synthetic grasping dataset with 179 household objects, 5K cluttered scenes and over 10M hand annotations. Experiments in simulation show that our model can predict dense and robust hand grasps and clear over 78% of unseen objects in clutter without any post-processing and outperform baseline methods by a large margin. Experiments on the real robot platform also demonstrate that the model trained on synthetic data performs well in natural environments. Code is available at https://***/yimingli1998/hgc net.

关键词： Point cloud compression Annotations Neural networks Grasping Predictive models End effectors Data models

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Prediction of Depth Camera Missing Measurements Using Deep Learning for Next Best View Planning 39

Prediction of Depth Camera Missing Measurements Using Deep L...

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IEEE international conference on robotics and automation (ICRA)

作者： Monica, Riccardo Aleotti, Jacopo Univ Parma Dept Engn & Architecture Parma Italy

ISBN: (纸本)9781728196817

Depth images usually contain pixels with invalid measurements. This paper presents a deep learning approach that receives as input a partially-known volumetric model of the environment and a camera pose, and it predicts the probability that a pixel would contain a valid depth measurement if a camera was placed at the given pose. The proposed network architecture consists of a 3D Convolutional Neural Network (CNN) module and a 2D CNN module, connected by a deep learning attention-based projection module. The method was integrated into a CNN-based probabilistic Next Best View planner, resulting in a more realistic prediction of the information gain for each possible viewpoint with respect to state of the art approaches. Experiments were carried out in tabletop scenarios using a robot manipulator with an eye-in-hand depth camera.

关键词： Deep learning Three-dimensional displays Volume measurement Robot vision systems Predictive models Cameras Probabilistic logic

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Underwater Dock Detection through Convolutional Neural Networks Trained with Artificial Image Generation 39

Underwater Dock Detection through Convolutional Neural Netwo...

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IEEE international conference on robotics and automation (ICRA)

作者： Chavez-Galaviz, Jalil Mahmoudian, Nina Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781728196817

Autonomous Underwater Vehicles (AUVs) are a vital element for ocean exploration in various applications;however, energy sustainability still limits long-term operations. An option to overcome this problem is using underwater docking for power and data transfer. To robustly guide an AUV into a docking station, we propose an underwater vision algorithm for short-distance detection. In this paper, we present a Convolutional Neural Network architecture to accurately estimate the dock position during the terminal homing stage of the docking. Additionally, to alleviate the lack of available underwater datasets, two methods are proposed to generate synthetic datasets, one using a CycleGAN network, and another using Artistic Style transfer network. Both methods are used to train the same CNN architecture to compare the results. Finally, implementation details of the CNN are presented under the backseat architecture and ROS framework, running on an IVER3 AUV.

关键词： Training Computer interfaces Autonomous underwater vehicles automation Image synthesis Oceans Data transfer

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Brain Tumor Diagnosis Using a Hybrid Method of BoVW, LBP, and Neural Networks 3

Brain Tumor Diagnosis Using a Hybrid Method of BoVW, LBP, an...

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3rd IEEE international conference on robotics, automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Hasan, Nowshad Islam, Md Saiful Sharif, Md. Maskat Chowdhury, Arafat Anam Rahman, Miskatur Khan, Md Tohedur Rahaman Khan, Md Rokibul Fahad Bahar, Anamul Chittagong University of Engineering and Technology Department of Electronics and Telecommunication Engineering Chittagong Bangladesh North South University Department of Computer Science Enginnering Dhaka Bangladesh International Islamic University Chittagong Department of Computer Science Enginnering Chittagong Bangladesh International Islamic University Chittagong Department of Electronics and Telecommunication Engineering Chittagong Bangladesh University of London Department of Computer Science Enginnering London United Kingdom

ISBN: (纸本)9798331534400

Brain tumor is one of the most deadly diseases today. Early identification is the key in treatment and automated method of image classification can help in this process. But, there are significant obstacles in precisely identifying brain tumors and increasing the classification accuracy for different types of tumors. In order to address the problem, the work suggests a hybrid model for effectively detecting and classifying brain tumors. First, the obtained pictures are preprocessed with resizing, application of sharpening filter and final stage of contrast enhancement. Further preprocessing in carried out using the K-mean clustering algorithm Next, Feature extraction is done by using the BoVW together with LBP which deal with the overall and region-specific texture features respectively. Following that, the seven statistical features are extracted, and then they are utilized as input to the artificial neural network classifier in order to obtain the classification of the glioma, meningioma, and pituitary tumor. The training function 'Levenberg-Marquardt' is also used in this work. This method provides 99.0 % of accuracy on Dataset I and 99.2% accuracy on Dataset II. Moreover, in relation to other modern methods, the selected seven statistical features employed in this study are relatively limited in demonstrating this performance. © 2024 IEEE.

关键词： K-means clustering

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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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Underwater Hyperspectral Imaging for Measuring Seafloor Reflectance

Underwater Hyperspectral Imaging for Measuring Seafloor Refl...

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

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

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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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