检索结果-内蒙古大学图书馆

OCEANS

作者： Valerio Franchi Hayat Rajani Rafael Garcia Borja Martinez-Clavel Nuno Gracias Computer Vision and Robotics Research Institute (VICOROB) University of Girona Girona Spain Tecnoambiente (A Tradebe Company) Barcelona Spain

Side scan sonars (SSS) are types of sonars that produce representations of the sea-bed by emitting and receiving acoustic fan-shaped pulses perpendicularly to the motion of the sensor in the water. Generally, SSS are deployed from a towed vehicle pulled from a boat at high speed to avoid oscillatory motions and thus achieve a clean and consistent sea-bed scan. Our approach targets the use of SSSs on small AUVs with limited computing power, and travelling at slow speeds, where the waterfall is directly used for real-time classfication. Due to the increased oscillatory motion, the SSS waterfall tends to have significant distortion, that will preclude the classifier from obtaining correct results. The algorithm described in this paper performs a geometric correction of the sonar scanlines by taking into account the AUV’s change in height, yaw and pitch to calculate correctly their positions on the seabed. The data is mapped into a 2D grid using the scanline intensities to form a mosaic, and the missing mosaic pixels are interpolated using a Gaussian-based kernel. The waterfall is recreated by considering a modified AUV trajectory with smooth changes in heading and a null pitch. The results show a significant improvement in the waterfall output, removing unwanted distortions and displaying the seabed structures with higher geometric consistency. In addition, the concentration of the ping data on the waterfall is constant all around, compared to the varying contribution density in the original one.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Complexity based investigation in collaborative assembly scenarios via non intrusive techniques

引用

Procedia computer Science 2023年 217卷 478-485页

作者： Sotirios Panagou Monica Sileo Konstantinos Papoutsakis Fabio Fruggiero Ammar Qammaz Antonis Argyros School of Engineering University of Basilicata 85100 Potenza Italy Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology – Hellas 70013 Heraklion Greece

Human and robot collaboration in assembly tasks is an integral part in modern manufactories. Robots provide advantages in both process and productivity with their repeatability and usability in different tasks, while human operators provide flexibility and can act as safeguards. However, process complexity increases which can lower the overall quality. Increased complexity can negatively influence decision making due to cognitive load on human operators, which can lead to lower quality, be it product, process or human work. Moreover, it can lead to safety risks, human-system error and accidents. In this work, we present the preliminary results on an experiment performed with student-participants, based on an assembly task. The experiment was set up to emulate an industrial assembly, and data collection was performed through qualitative and non-intrusive quantitative methods. Questionnaires were used to assess perceptual task complexity and cognitive load, while a stereo camera provided recordings for after-task analysis on process errors and human work quality based on a 3D skeleton-based human pose estimation and tracking method. The aim of the study is to investigate causes of errors and implications on quality. Future direction of the work is discussed.

关键词： collaboration assembly task complexity cognitive load human pose estimation tracking

来源：评论

学校读者我要写书评

暂无评论

*** 1.0: The Full Autonomous Stack for Oval Racing at High Speeds

Field Robotics

引用

Field robotics 2025年 4卷 99-137页

作者： Ayoub Raji Danilo Caporale Francesco Gatti Andrea Giove Micaela Verucchi Davide Malatesta Nicola Musiu Alessandro Toschi Silviu Roberto Popitanu Fabio Bagni Massimiliano Bosi Alexander Liniger Marko Bertogna Daniele Morra Francesco Amerotti Luca Bartoli Federico Martello Riccardo Porta University of Modena and Reggio Emilia Italy University of Parma Italy Technology Innovation Institute-Autonomous Robotics Research Center UAE HIPERT srl University of Pisa Italy HIPERT srl Computer Vision Lab ETH Zurich Switzerland

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at an unprecedented speed and in a head-to-head scenario, using independently developed software on open-wheel race cars. This paper presents the complete software architecture used by the team TII EuroRacing (TII-ER), covering all the modules needed to avoid static obstacles, perform active overtakes, and reach speeds above 75m/s (270km/h). In addition to the most common modules related to perception, planning, and control, we discuss the approaches used for vehicle dynamics modeling, simulation, telemetry, and safety. Overall results and the performance of each module are described, as well as the lessons learned during the first two events of the competition on oval tracks, where the team placed second and third, respectively.

关键词： Automobiles Cameras Laser radar Autonomous vehicles Location awareness Safety Planning Vehicle dynamics Testing Sports Motion planning Environmental monitoring

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications

arXiv

引用

arXiv 2024年

作者： Ibrahim, Sinan Mostafa, Mostafa Jnadi, Ali Salloum, Hadi Osinenko, Pavel Skolkovo Institute of Science and Technology Moscow121205 Russia Institute of Robotics and Computer Vision Innopolis University Innopolis420500 Russia Research Center for Artificial Intelligence Innopolis University Innopolis420500 Russia

Reinforcement Learning (RL) seeks to develop systems capable of autonomous decision-making by learning through interaction with their environment. Central to this process are reward engineering and reward shaping, which are essential for enhancing the efficiency and effectiveness of RL algorithms. These techniques guide agents toward desired behaviors, improve learning stability, and accelerate convergence by addressing challenges such as sparse and delayed rewards. However, the complexity of real-world environments and the computational demands of RL algorithms remain significant obstacles to broader adoption. Recent advancements in deep learning have enabled RL to handle high-dimensional state and action spaces, facilitating applications in robotics, autonomous driving, and complex decision-making tasks. In response to these developments, this paper provides one of the first comprehensive reviews of reward design in RL, with a focus on the methodologies and techniques underpinning reward engineering and shaping. By introducing a detailed taxonomy, critically analyzing current approaches, and highlighting their limitations, this work fills an important gap in the literature, offering insights into how reward structures can be optimized to meet the growing demands of modern AI systems. © 2024, CC BY.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Stiffness-based Offline Toolpath Error Compensation for Robotized Incremental Forming

Stiffness-based Offline Toolpath Error Compensation for Robo...

引用

Automation, Control and Robots (ICACR), International Conference on

作者： Walid K. Shaker Alexandr Klimchik Institute of Robotics and Computer Vision Innopolis University Innopolis Russia Lincoln Centre for Autonomous Systems Research (L-CAS) School of Computer Science University of Lincoln Lincoln United Kingdom

This paper addresses the challenge of the poor accuracy and the toolpath deviation in Incremental Sheet Forming (ISF) caused by the forming forces applied to the workpiece. The paper proposes an offline toolpath error compensation approach based on stiffness analysis. A truncated cone was used as a test case and the numerical simulation of the ISF process was conducted on Abaqus CAE software to extract forming forces corresponding to toolpath points. The compensation algorithm is based on the Virtual Joint Method (VJM) and is implemented on a FANUC R-2000iC/165F robot using RoboDK API for MATLAB. The results show that the deviation of the robot tool due to the forming forces may reach up to 20 mm which can be handled by the compensated toolpath. Finally, the study proposes an overall process for the stiffness-based correction algorithm.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Springback Compensation for Various Profiles in Incremental Forming

Comparative Analysis of Springback Compensation for Various ...

引用

International Russian Automation Conference (RusAutoCon)

Incremental forming encounters a common challenge known as the springback effect, wherein the workpiece undergoes elastic deformation and deviates slightly from the desired shape once the forming tool is released. This discrepancy between the intended and obtained shape results in reduced geometric accuracy, making incremental forming less precise compared to conventional methods. This research presents a novel springback effect compensation model for sheet forming processes. The main objective is to evaluate the model's performance across various profiles, with a focus on enhancing precision and accuracy in the formed shapes. The proposed model demonstrates an impressive ability to compensate for approximately 60% of the springback effect, offering a practical solution for offline springback compensation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

LiCAR: pseudo-RGB LiDAR image for CAR segmentation

arXiv

引用

arXiv 2025年

作者： de Loyola Páez-Ubieta, Ignacio Velasco-Sánchez, Edison P. Puente, Santiago T. AUtomatics RObotics and Artificial Vision Lab IUII: University Institute for Computer Research University of Alicante Crta. San Vicente s/n San Vicente del Raspeig AlicanteE-03690 Spain

With the advancement of computing resources, an increasing number of Neural Networks (NNs) are appearing for image detection and segmentation appear. However, these methods usually accept as input a RGB 2D image. On the other side, Light Detection And Ranging (LiDAR) sensors with many layers provide images that are similar to those obtained from a traditional low resolution RGB camera. Following this principle, a new dataset for segmenting cars in pseudo-RGB images has been generated. This dataset combines the information given by the LiDAR sensor into a Spherical Range Image (SRI), concretely the reflectivity, near infrared and signal intensity 2D images. These images are then fed into instance segmentation NNs. These NNs segment the cars that appear in these images, having as result a Bounding Box (BB) and mask precision of 88% and 81.5% respectively with You Only Look Once (YOLO)-v8 large. By using this segmentation NN, some trackers have been applied so as to follow each car segmented instance along a video feed, having great performance in real world experiments. © 2025, CC BY.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

A single 2D pose with context is worth hundreds for 3D human pose estimation 23

A single 2D pose with context is worth hundreds for 3D human...

引用

Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Qitao Zhao Ce Zheng Mengyuan Liu Chen Chen Robotics Institute Carnegie Mellon University Center for Research in Computer Vision University of Central Florida Key Laboratory of Machine Perception Peking University Shenzhen Graduate School

The dominant paradigm in 3D human pose estimation that lifts a 2D pose sequence to 3D heavily relies on long-term temporal clues (i.e., using a daunting number of video frames) for improved accuracy, which incurs performance saturation, intractable computation and the non-causal problem. This can be attributed to their inherent inability to perceive spatial context as plain 2D joint coordinates carry no visual cues. To address this issue, we propose a straightforward yet powerful solution: leveraging the readily available intermediate visual representations produced by off-the-shelf (pre-trained) 2D pose detectors - no finetuning on the 3D task is even needed. The key observation is that, while the pose detector learns to localize 2D joints, such representations (e.g., feature maps) implicitly encode the joint-centric spatial context thanks to the regional operations in backbone networks. We design a simple baseline named Context-Aware PoseFormer to showcase its effectiveness. Without access to any temporal information, the proposed method significantly outperforms its context-agnostic counterpart, PoseFormer [74], and other state-of-the-art methods using up to hundreds of video frames regarding both speed and precision. Project page: ***/ContextAware-PoseFormer

关键词：

来源：评论

学校读者我要写书评

暂无评论

Testing autonomous underwater vehicle compatibility with bidirectional acoustic tags for biotelemetry

Testing autonomous underwater vehicle compatibility with bid...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Gerard Batet David Sarria Marta Real Spartacus Gomariz Joaquin Del Rio Narcis Palomeras Ivan Masmitja SARTI Research Group EEL Universitat Politècnica de Catalunya Computer Vision and Robotics Institute Universitat de Girona Institut de Ciencies del Mar Consejo Superior de Investigaciones Científicas

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Few advancements in underwater species tracking have occurred in recent years. For instance, acoustic biotelemetry systems were initially employed in the late ’70s, and since then, only minimum improvements have been made in terms of range and battery life. The development of a bidirectional acoustic tag, combined with other technologies such as autonomous surface and underwater vehicles, promises a significant leap forward in the field, offering enhanced data precision at a reduced operational cost.

关键词： Biomedical telemetry Working environment noise Noise Receivers Marine ecosystems Acoustics Underwater tracking Batteries Monitoring Testing

来源：评论

学校读者我要写书评

暂无评论

Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping

arXiv

引用

arXiv 2024年

作者： Lin, Qinliang Luo, Cheng Niu, Zenghao He, Xilin Xie, Weicheng Hou, Yuanbo Shen, Linlin Song, Siyang Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China Guangdong Key Laboratory of Intelligent Information Processing China WAVES Research Group Ghent University Belgium University of Leicester United Kingdom

Adversarial examples generated by a surrogate model typically exhibit limited transferability to unknown target systems. To address this problem, many transferability enhancement approaches (e.g., input transformation and model augmentation) have been proposed. However, they show poor performances in attacking systems having different model genera from the surrogate model. In this paper, we propose a novel and generic attacking strategy, called Deformation-Constrained Warping Attack (DeCoWA), that can be effectively applied to cross model genus attack. Specifically, DeCoWA firstly augments input examples via an elastic deformation, namely Deformation-Constrained Warping (DeCoW), to obtain rich local details of the augmented input. To avoid severe distortion of global semantics led by random deformation, DeCoW further constrains the strength and direction of the warping transformation by a novel adaptive control strategy. Extensive experiments demonstrate that the transferable examples crafted by our DeCoWA on CNN surrogates can significantly hinder the performance of Transformers (and vice versa) on various tasks, including image classification, video action recognition, and audio recognition. Code is made available at https://***/LinQinLiang/DeCoWA. © 2024, CC BY-NC-SA.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：