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Extremum seeking control for UAV close formation flight via improved pigeon-inspired optimization

Science China(Technological Sciences) 2024年第2期67卷 435-448页

作者： YUAN GuangSong DUAN HaiBin State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100083China

This paper proposes a comprehensive design scheme for the extremum seeking control(ESC)of the unmanned aerial vehicle(UAV)close formation *** proposed design scheme combines a Newton-Raphson method with an extended Kalman filter(EKF)to dynamically estimate the optimal position of the following UAV relative to the leading *** reflect the wake vortex effects reliably,the drag coefficient induced by the wake vortex is considered as a performance ***,the performance function is parameterized by the first-order and second-order terms of its Taylor series *** the excellent performance of nonlinear estimation,the EKF is used to estimate the gradient and the Hessian matrix of the parameterized performance *** output feedback of the proposed scheme is determined by iterative calculation of the Newton-Raphson *** with the traditional ESC and the classic ESC,the proposed design scheme avoids the slow continuous time integration of the *** allows a faster convergence of relative position ***,the proposed method can provide a smoother command during the seeking process as the second-order term of the performance function is taken into *** convergence analysis of the proposed design scheme is accomplished by showing that the output feedback is a supermartingale *** improve estimation performance of the EKF,a improved pigeon-inspired optimization(IPIO)is proposed to automatically tune the noise covariance *** Carlo simulations for a three-UAV close formation show that the proposed design scheme is robust to the initial position of the following UAV.

关键词： unmanned aerial vehicle close formation extremum seeking control Newton-Raphson method improved pigeon-inspired optimization

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AR assistance for efficient dynamic target search

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Computational Visual Media 2023年第1期9卷 177-194页

作者： Zixiang Zhao Jian Wu Lili Wang State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina

When searching for a dynamic target in an unknown real world scene,search efficiency is greatly reduced if users lack information about the spatial structure of the *** target search studies,especially in robotics,focus on determining either the shortest path when the target’s position is known,or a strategy to find the target as quickly as possible when the target’s position is ***,the target’s position is often known intermittently in the real world,e.g.,in the case of using surveillance *** goal is to help user find a dynamic target efficiently in the real world when the target’s position is intermittently *** order to achieve this purpose,we have designed an AR guidance assistance system to provide optimal current directional guidance to users,based on searching a prediction *** assume that a certain number of depth cameras are fixed in a real scene to obtain dynamic target’s *** system automatically analyzes all possible meetings between the user and the target,and generates optimal directional guidance to help the user catch up with the target.A user study was used to evaluate our method,and its results showed that compared to free search and a top-view method,our method significantly improves target search efficiency.

关键词： augmented reality(AR) search guidance

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Multi-granularity sequence generation for hierarchical image classification

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Computational Visual Media 2024年第2期10卷 243-260页

作者： Xinda Liu Lili Wang State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Peng Cheng Laboratory Shengzhen 518000China

Hierarchical multi-granularity image classification is a challenging task that aims to tag each given image with multiple granularity labels *** methods tend to overlook that different image regions contribute differently to label prediction at different granularities,and also insufficiently consider relationships between the hierarchical multi-granularity *** introduce a sequence-to-sequence mechanism to overcome these two problems and propose a multi-granularity sequence generation(MGSG)approach for the hierarchical multi-granularity image classification ***,we introduce a transformer architecture to encode the image into visual representation ***,we traverse the taxonomic tree and organize the multi-granularity labels into sequences,and vectorize them and add positional *** proposed multi-granularity sequence generation method builds a decoder that takes visual representation sequences and semantic label embedding as inputs,and outputs the predicted multi-granularity label *** decoder models dependencies and correlations between multi-granularity labels through a masked multi-head self-attention mechanism,and relates visual information to the semantic label information through a crossmodality attention *** this way,the proposed method preserves the relationships between labels at different granularity levels and takes into account the influence of different image regions on labels with different *** on six public benchmarks qualitatively and quantitatively demonstrate the advantages of the proposed *** project is available at https://***/liuxindazz/mgs.

关键词： hierarchical multi-granularity classification vision and text transformer sequence generation fine-grained image recognition cross-modality attenti

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FDCPNet:feature discrimination and context propagation network for 3D shape representation

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虚拟现实与智能硬件(中英文) 2025年第1期7卷 83-94页

作者： Weimin SHI Yuan XIONG Qianwen WANG Han JIANG Zhong ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation *** methods for extracting features from mesh edges or faces struggle with complex 3D models because edge-based approaches miss global contexts and face-based methods overlook variations in adjacent areas,which affects the overall *** address these issues,we propose the Feature Discrimination and Context Propagation Network(FDCPNet),which is a novel approach that synergistically integrates local and global features in mesh *** FDCPNet is composed of two modules:(1)the Feature Discrimination Module,which employs an attention mechanism to enhance the identification of key local features,and(2)the Context Propagation Module,which enriches key local features by integrating global contextual information,thereby facilitating a more detailed and comprehensive representation of crucial areas within the mesh *** Experiments on popular datasets validated the effectiveness of FDCPNet,showing an improvement in the classification accuracy over the baseline ***,even with reduced mesh face numbers and limited training data,FDCPNet achieved promising results,demonstrating its robustness in scenarios of variable complexity.

关键词： 3D shape representation Mesh model MeshNet Feature discrimination Context propagation

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Skinned Motion Retargeting with Preservation of Body Part Relationships

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IEEE Transactions on Visualization and Computer Graphics 2024年 PP卷 1-13页

作者： Zhang, Jia-Qi Wang, Miao Zhang, Fu-Cheng Zhang, Fang-Lue State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China School of Engineering and Computer Science Victoria University of Wellington New Zealand

Motion retargeting is an active research area in computer graphics and animation, allowing for the transfer of motion from one character to another, thereby creating diverse animated character data. While this technology has numerous applications in animation, games, and movies, current methods often produce unnatural or semantically inconsistent motion when applied to characters with different shapes or joint counts. This is primarily due to a lack of consideration for the geometric and spatial relationships between the body parts of the source and target characters. To tackle this challenge, we introduce a novel spatially-preserving Skinned Motion Retargeting Network (SMRNet) capable of handling motion retargeting for characters with varying shapes and skeletal structures while maintaining semantic consistency. By learning a hybrid representation of the character's skeleton and shape in a rest pose, SMRNet transfers the rotation and root joint position of the source character's motion to the target character through embedded rest pose feature alignment. Additionally, it incorporates a differentiable loss function to further preserve the spatial consistency of body parts between the source and target. Comprehensive quantitative and qualitative evaluations demonstrate the superiority of our approach over existing alternatives, particularly in preserving spatial relationships more effectively IEEE

关键词： Semantics

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Offline Reinforcement Learning with Constrained Hybrid Action Implicit Representation Towards Wargaming Decision-Making

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Tsinghua Science and technology 2024年第5期29卷 1422-1440页

作者： Liwei Dong Ni Li Guanghong Gong Xin Lin School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191ChinaState Key Laboratory of Virtual Reality Technology and SystemsBeihang UniversityBeijing 100191Chinaand also with Zhongguancun LaboratoryBeijing 100191China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191Chinaand also with State Key Laboratory of Virtual Reality Technology and SystemsBeihang UniversityBeijing 100191China

Reinforcement Learning(RL)has emerged as a promising data-driven solution for wargaming ***,two domain challenges still exist:(1)dealing with discrete-continuous hybrid wargaming control and(2)accelerating RL deployment with rich offline *** RL methods fail to handle these two issues simultaneously,thereby we propose a novel offline RL method targeting hybrid action space.A new constrained action representation technique is developed to build a bidirectional mapping between the original hybrid action space and a latent space in a semantically consistent *** allows learning a continuous latent policy with offline RL with better exploration feasibility and scalability and reconstructing it back to a needed hybrid ***,a novel offline RL optimization objective with adaptively adjusted constraints is designed to balance the alleviation and generalization of out-of-distribution *** method demonstrates superior performance and generality across different tasks,particularly in typical realistic wargaming scenarios.

关键词： offline Reinforcement Learning(RL) wargaming decision-making hybrid action space

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Multiplayer Reach-Avoid Differential Games in 3D Space Inspired by Harris'Hawks'Cooperative Hunting Tactics

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Research 2024年第2期2023卷 41-54页

作者： Wanying Ruan Haibin Duan Yongbin Sun Wanmai Yuan Jie Xia State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijingChina Peng Cheng Laboratory ShenzhenChina Information Science Academy of CETC BeijingChina

This paper investigates a multiplayer reach-avoid differential game in 3-dimensional(3D)space,which involves multiple pursuers,multiple evaders,and a designated target *** evaders aim to reach the target region,while the pursuers attempt to guard the target region by capturing the *** class of research holds significant practical ***,the complexity of the problem escalates substantially with the growing number of players,rendering its solution extremely *** this paper,the multiplayer game is divided into many subgames considering the cooperation among pursuers,reducing the computational burden,and obtaining numerically tractable strategies for ***,the Apollonius sphere,a fundamental geometric tool for analyzing the 3D differential game,is formulated,and its properties are *** on this,the optimal interception point for the pursuer to capture the evader is derived and the winning conditions for the pursuer and evader are ***,based on the Apollonius sphere,the optimal state feedback strategies of players are designed,and simultaneously,the optimal one-to-one pairings are ***,the Value function of the multiplayer reach-avoid differential game is explicitly given and is proved to satisfy Hamilton-Jacobi-Isaacs(HJI)***,the matching algorithm for the case with pursuers outnumbered evaders is provided through constructing a weighted bipartite graph,and the cooperative tactics for multiple pursuers are proposed,inspired by the Harris'Hawks intelligent cooperative hunting ***,numerical simulations are conducted to illustrate the effectiveness of the theoretical results for both cases where the number of adversary players is equal and unequal between the 2 groups.

关键词： holds satisfy rendering

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Web-based mixed reality video fusion with remote rendering

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virtual reality & Intelligent Hardware 2023年第2期5卷 188-199页

作者： Qiang ZHOU Zhong ZHOU State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China

Background Mixed reality(MR)video fusion systems merge video imagery with 3D scenes to make the scene more realistic and help users understand the video content and temporal–spatial correlation between them,reducing the user′s cognitive *** video fusion are used in various applications;however,video fusion systems require powerful client machines because video streaming delivery,stitching,and rendering are computationally ***,huge bandwidth usage is another critical factor that affects the scalability of video-fusion *** Our framework proposes a fusion method for dynamically projecting video images into 3D models as *** Several experiments on different metrics demonstrate the effectiveness of the proposed *** The framework proposed in this study can overcome client limitations by utilizing remote ***,the framework we built is based on ***,the user can test the MR video fusion system with a laptop or tablet without installing any additional plug-ins or application programs.

关键词： Mixed reality Video fusion WebRTC Remote rendering

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Parsing Objects at a Finer Granularity: A Survey

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Machine Intelligence Research 2024年第3期21卷 431-451页

作者： Yifan Zhao Jia Li Yonghong Tian School of Computer Science Peking UniversityBeijing100871China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing100191China

Fine-grained visual parsing, including fine-grained part segmentation and fine-grained object recognition, has attracted considerable critical attention due to its importance in many real-world applications, e.g., agriculture, remote sensing, and space technologies. Predominant research efforts tackle these fine-grained sub-tasks following different paradigms, while the inherent relations between these tasks are neglected. Moreover, given most of the research remains fragmented, we conduct an in-depth study of the advanced work from a new perspective of learning the part relationship. In this perspective, we first consolidate recent research and benchmark syntheses with new taxonomies. Based on this consolidation, we revisit the universal challenges in fine-grained part segmentation and recognition tasks and propose new solutions by part relationship learning for these important challenges. Furthermore, we conclude several promising lines of research in fine-grained visual parsing for future research.

关键词： Finer granularity visual parsing part segmentation fine-grained object recognition part relationship

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Drogue detection for autonomous aerial refueling via hybrid pigeon-inspired optimized color opponent and saliency aggregation

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Chinese Journal of Aeronautics 2024年第5期37卷 27-38页

作者： Tongyan WU Haibin DUAN Yanming FAN State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China AVIC Shenyang Aircraft Design and Research Institute Shenyang 110035China

Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and *** detection based on image intrinsic cues can achieve fast detection,but with poor *** studies reveal that optimization-based methods provide accurate and quick solutions for saliency *** paper presents a hybrid pigeon-inspired optimization method,the optimized color opponent,that aims to adjust the weight of color opponent channels to detect the drogue *** can optimize the weights in the selected aerial refueling scene offline,and the results are applied for drogue detection in the scene.A novel algorithm aggregated by the optimized color opponent and robust background detection is presented to provide better precision and *** results on benchmark datasets and aerial refueling images show that the proposed method successfully extracts the saliency region or drogue and exhibits superior performance against the other saliency detection methods with intrinsic *** algorithm designed in this paper is competent for the drogue detection task of autonomous aerial refueling.

关键词： Autonomous aerial refueling Drones Hybrid pigeon-inspired optimization Color opponent Saliency detection Saliency aggregation

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