检索结果-内蒙古大学图书馆

A tethered quadrotor UAV-buoy system for marine locomotion

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Kourani, Ahmad Daher, Naseem Vision and Robotics Lab Department of Mechanical Engineering American University of Beirut Beirut Lebanon Vision and Robotics Lab Department of Electrical and Computer Engineering

Unmanned aerial vehicles (UAVs) are finding their way into offshore applications. In this work, we postulate an original system that entails a marine locomotive quadrotor UAV that manipulates the velocity of a floating buoy by means of a cable. By leveraging the advantages of UAVs relative to high speed, maneuverability, ease of deployment, and wide field of vision, the proposed UAV-buoy system paves the way in front of a variety of novel applications. The dynamic model that couples the buoy, UAV, cable, and water environment is presented using the Euler-Lagrange method. A stable control system design is proposed to manipulate the forward-surge speed of the buoy under two constraints: maintaining the cable in a taut state, and keeping the buoy in contact with the water surface. Polar coordinates are used in the controller design process to attain correlated effects on the tracking performance, whereby each control channel independently affects one control parameter. This results in improved performance over traditional Cartesian-based velocity controllers, as demonstrated via numerical simulations in wave-free and wavy seas. Copyright © 2021, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

Restoration of video frames from a single blurred image with motion understanding

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Argaw, Dawit Mureja Kim, Junsik Rameau, Francois Zhang, Chaoning Kweon, In So Kaist Robotics and Computer Vision Lab. Daejeon Korea Republic of

We propose a novel framework to generate clean video frames from a single motion-blurred image. While a broad range of literature focuses on recovering a single image from a blurred image, in this work, we tackle a more challenging task i.e. video restoration from a blurred image. We formulate video restoration from a single blurred image as an inverse problem by setting clean image sequence and their respective motion as latent factors, and the blurred image as an observation. Our framework is based on an encoder-decoder structure with spatial transformer network modules to restore a video sequence and its underlying motion in an end-to-end manner. We design a loss function and regularizers with complementary properties to stabilize the training and analyze variant models of the proposed network. The effectiveness and transferability of our network are highlighted through a large set of experiments on two different types of datasets: camera rotation blurs generated from panorama scenes and dynamic motion blurs in high speed videos. © 2021, CC BY.

关键词： Restoration

Leveraging PID gain selection towards adaptive backstepping control for a class of second-order systems

学校读者我要写书评

暂无评论

arXiv 2021年

—In this work, we establish a convenient similarity between an adaptive backstepping control law and a standard proportional-integral-derivative (PID) controller for a class of second-order systems. The extracted similarity provides a deeper understanding of the adaptive backstepping design from a performance perspective via an intuitive method to select its otherwise abstract controller gains, on top of its traditional stability perspective. Such a similarity analysis opens the door for researchers to use well-established PID tuning methods to predict the performance of Lyapunov stability-based controllers. At the same time, the obtained formulation reveals how the corresponding PID control law can be linked to Lyapunov stability theory. The proposed scheme is applied to a quadrotor unmanned aerial vehicle (UAV) carrying a payload with the presence of a wind gust as an external disturbance, in simulation and experimentally. Copyright © 2021, The Authors. All rights reserved.

关键词： Proportional control systems

Optical flow estimation from a single motion-blurred image

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Argaw, Dawit Mureja Kim, Junsik Rameau, Francois Cho, Jae Won Kweon, In So KAIST Robotics and Computer Vision Lab. Daejeon Korea Republic of

In most of computer vision applications, motion blur is regarded as an undesirable artifact. However, it has been shown that motion blur in an image may have practical interests in fundamental computer vision problems. In this work, we propose a novel framework to estimate optical flow from a single motion-blurred image in an end-to-end manner. We design our network with transformer networks to learn globally and locally varying motions from encoded features of a motion-blurred input, and decode left and right frame features without explicit frame supervision. A flow estimator network is then used to estimate optical flow from the decoded features in a coarse-to-fine manner. We qualitatively and quantitatively evaluate our model through a large set of experiments on synthetic and real motion-blur datasets. We also provide in-depth analysis of our model in connection with related approaches to highlight the effectiveness and favorability of our approach. Furthermore, we showcase the applicability of the flow estimated by our method on deblurring and moving object segmentation tasks. © 2021, CC BY.

关键词： Optical flows

HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Zeng, Yu Zhang, Yang Liu, Jiachen Shen, Linlin Deng, Kaijun He, Weizhao Wang, Jinbao Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using text descriptions or reference images, while preserving irrelevant attributes (e.g., identity, background, cloth). Many existing methods are based on StyleGAN to address this task. However, due to the limited spatial distribution of StyleGAN, it struggles with multiple hair color editing and facial preservation. Considering the advancements in diffusion models, we utilize Latent Diffusion Models (LDMs) for hairstyle editing. Our approach introduces Multi-stage Hairstyle Blend (MHB), effectively separating control of hair color and hairstyle in diffusion latent space. Additionally, we train a warping module to align the hair color with the target region. To further enhance multi-color hairstyle editing, we fine-tuned a CLIP model using a multi-color hairstyle dataset. Our method not only tackles the complexity of multi-color hairstyles but also addresses the challenge of preserving original colors during diffusion editing. Extensive experiments showcase the superiority of our method in editing multi-color hairstyles while preserving facial attributes given textual descriptions and reference images. © 2024, CC BY.

关键词： Color image processing

Segment-Based Trajectory Prediction and Risk Assessment for RSU-assisted CAVs at Signalized Intersections

学校读者我要写书评

暂无评论

IEEE Transactions on Intelligent Vehicles

IEEE Transactions on Intelligent Vehicles 2024年 1-19页

作者： Cao, Yue Shangguan, Wei Visser, Arnoud Chen, Junjie Chai, Linguo Cai, Baigen School of Automation and Intelligence Beijing Jiaotong University Beijing China School of Automation and Intelligence and State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Intelligent Robotics and Computer Vision Lab of the Informatics Institute Faculty of Science University of Amsterdam The Netherlands

Detecting surrounding situations and reacting accordingly to avoid collisions remains a challenging task for autonomous driving. This task requires predicting the trajectories of surrounding agents and assessing the potential risk of future situations, which can be difficult to achieve solely through onboard vehicle devices. Therefore, this paper proposes a cooperative architecture for trajectory prediction and risk assessment conducted on roadside devices (RSUs) to assist Connected and Autonomous Vehicles (CAVs). Firstly, we develop a segmentbased prediction model (SegNet) tailored to hub signalized intersections. Intersections are divided into multiple segments, and the Curvilinear coordinates are utilized to indicate the geometric road features. The model leverages individual interaction cues in the ego segment and group features in the merging segments, while also incorporating traffic signal information to generate multimodal prediction results. In terms of risk assessment, we utilize the prediction results to provide hierarchical assistance, such as risk values, risk maps, and reference trajectories. Offline experimental results demonstrate that our SegNet model achieves competitive and well-balanced performance compared to stateof-the-art methods on the CitySim Database, with more accurate and smooth prediction trajectories. Through real-time CARLA and SUMO co-simulation, the performance of assisted CAVs indicates that they can safely and effectively navigate with the support of the proposed architecture. IEEE

关键词： Real time systems

Hardware-Agnostic Behavior Trees:Towards Generic Robot Behavior Design

学校读者我要写书评

暂无评论

SSRN

SSRN 2022年

作者： El-Ariss, Wafic Daher, Naseem Elhajj, Imad H. Logistics Robotics BMW Group Petuelring 130 Munich80809 Germany Vision and Robotics Lab Department of Mechanical Engineering American University of Beirut Riad El-Solh Beirut1107 Lebanon Vision and Robotics Lab Department of Electrical and Computer Engineering American University of Beirut Riad El-Solh Beirut1107 Lebanon

Decision-Making (DM) algorithms are an essential component of autonomous agents that control the behavior of Non-Player Characters (NPCs) in computer games, as well as the behavior of autonomous robots. Behavior Trees (BTs) have gained significant traction in recent years for having facilitated the development of complex behaviors for autonomous robots and NPCs, by offering a simple, yet powerful, task-switching architecture that relies on composing modular and reusable unit behaviors to achieve the overall desired *** is well understood how to design BT leaves, the unit behavior of BTs, for them to be reused across the behavior of a single robot system, however, there is a need for these leaves to generalize across systems of differing hardware, thus achieving hardware abstraction, and producing what we call Hardware-Agnostic Behavior Tree Leaves that would reduce the development time and costs of new *** this paper, we address this goal by first presenting a new formulation for BTs that incorporates parameterization. Subsequently, we propose a method to specify DM behaviors in a hardware-agnostic manner. Then, we apply object-oriented design methods to specify BTs. We combine the three techniques to define Hardware-Agnostic Behavior Tree Leaves , and propose a method to design them so that these unit behaviors can be reused across systems of differing hardware. We demonstrate the applicability of our proposed method by designing a completely hardware-agnostic, and thus reusable, BT software that we then apply on two real robotic systems with differing hardware used at the BMW Group, and we show that the BT software developed using our methods leads to higher reusability (as per Chidamber and Kemerer metrics) by conducting a comparison against a benchmark BT software built using state-of-the-art methods. Four out of the five used Chidamber and Kemerer metrics indicated that our method increased reusability, it resulted in software that is 7.7% shorter

关键词： Industrial robots

Perspective Phase Angle Model for Polarimetric 3D Reconstruction

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Chen, Guangcheng He, Li Guan, Yisheng Zhang, Hong Guangdong University of Technology Guangzhou China Southern University of Science and Technology Shenzhen China Shenzhen Key Laboratory of Robotics and Computer Vision China

Current polarimetric 3D reconstruction methods, including those in the well-established shape from polarization literature, are all developed under the orthographic projection assumption. In the case of a large field of view, however, this assumption does not hold and may result in significant reconstruction errors in methods that make this assumption. To address this problem, we present the perspective phase angle (PPA) model that is applicable to perspective cameras. Compared with the orthographic model, the proposed PPA model accurately describes the relationship between polarization phase angle and surface normal under perspective projection. In addition, the PPA model makes it possible to estimate surface normals from only one single-view phase angle map and does not suffer from the so-called π-ambiguity problem. Experiments on real data show that the PPA model is more accurate for surface normal estimation with a perspective camera than the orthographic model. Copyright © 2022, The Authors. All rights reserved.

关键词： Image reconstruction

Adaptive Generalized Social Space Delimitation for Human-Robot Interaction Tasks

学校读者我要写书评

暂无评论

Adaptive Generalized Social Space Delimitation for Human-Rob...

IEEE Latin American robotics Symposium, LARS

作者： Manuela M. F. Silva Aline F. F. Silva Douglas G. Macharet Department of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Laboratório de Inteligência Computacional e Robótica (LICRo) Instituto Federal do Triângulo Mineiro (IFTM) Campus Patrocínio Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

Human-Robot Interaction (HRI) research is of paramount importance as it addresses the rapidly evolving landscape where robots are increasingly integrated into everyday life. Social spaces refer to the invisible zones that individuals maintain around themselves, dictating appropriate distances for various types of interactions. This concept is pivotal in HRI, as it ensures that robots engage with humans in ways that are both comfortable and respectful of personal boundaries. In this paper, we propose a novel social space delimitation approach based on deformable elastic bands. Our method leverages the flexibility and adaptability of elastic band theory to dynamically define and adjust social spaces around individuals and groups. The results, based on both static and dynamic cases as well as a real-world dataset, show that our approach achieves a responsive and accurate representation of social spaces, that can accommodate varying group configurations and environmental conditions.

关键词： Accuracy Human-robot interaction Robots