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Time-Optimal Trajectory Planning With Clearly Defined Initial Guess for Aerial Suspended Payload Throwing

IEEE Transactions on Automation Science and Engineering 2025年 22卷 12406-12417页

作者： Cao, Rui Fang, Yongchun Liang, Xiao Nankai University Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Haihe Laboratory of ITAI Tianjin300450 China

Autonomous Aerial Vehicles (AAVs), particularly quadrotors, have gained substantial attention in recent years due to their high agility, substantial convenience, and significant potential in hazardous missions such as military surveillance and disaster relief. This paper focuses on the aerial throwing problem, aiming to develop a time-optimal method for air-dropping cable-suspended payloads. The contributions of the paper are: 1) a fast approach is presented to streamline the quadrotor’s state management by directly mapping and planning at the quadrotor state space (position, velocity, acceleration);2) a clearly defined initial guess is provided for aerial suspended throwing tasks, which speeds up the planning process. This methodology not only enhances the convenience of quadrotor navigation, but also fosters a more direct and efficient control scheme. The efficacy and feasibility of the proposed method are validated through both numerical simulations and practical experiments, demonstrating the potential for rapid and accurate payload throwing with cable-suspended systems. © 2004-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Delving into Feature Space: Improving Adversarial Robustness by Feature Spectral Regularization 27th

Delving into Feature Space: Improving Adversarial Robustness...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Cheng, Zhen Zhu, Fei Zhang, Xu-Yao Liu, Cheng-Lin State Key Laboratory of Multimodal Artificial Intelligence Systems CASIA Beijing China School of Artificial Intelligence UCAS Beijing China Centre for Artificial Intelligence and Robotics HKISI-CAS Hong Kong

ISBN: (纸本)9783031783944

The study of adversarial examples in deep neural networks has attracted great attention. Numerous methods improve adversarial robustness via shrinking the gap of features between natural examples and adversarial examples. Nevertheless, the role of individual features in adversarial robustness has not been explored adequately. In this paper, we delve into this problem from the perspective of spectral analysis in feature space. We find that while standardly trained deep models have features distributed dominantly along eigenvectors with large eigenvalues, eigenvectors with smaller eigenvalues are more sensitive to adversarial attacks. We attribute this phenomenon to the dominance of the top eigenvalues, linked to the concept of intrinsic dimensionality. The extracted features possess a small intrinsic dimensionality, enhancing generalization but resulting in the model overlooking diverse features. We propose a method called Feature Spectral Regularization (FSR) to penalize the largest eigenvalue, so as to spread the distribution of eigenvalues. Comprehensive experiments demonstrate that FSR is effective to alleviate the dominance of larger eigenvalues, increase the intrinsic dimensionality, and improve adversarial robustness on multiple datasets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

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Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1237-1250页

作者： Guangli Ren Jierui Liu Mengyao Wang Peiyu Guan Zhiqiang Cao Junzhi Yu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics Peking UniversityBeijing 100871China

Few-shot object detection receives much attention with the ability to detect novel class objects using limited annotated *** transfer learning-based solution becomes popular due to its simple training with good accuracy,however,it is still challenging to enrich the feature diversity during the training *** fine-grained features are also insufficient for novel class *** deal with the problems,this paper proposes a novel few-shot object detection method based on dual-domain feature fusion and patch-level *** original base domain,an elementary domain with more category-agnostic features is superposed to construct a two-stream backbone,which benefits to enrich the feature *** better integrate various features,a dual-domain feature fusion is designed,where the feature pairs with the same size are complementarily fused to extract more discriminative ***,a patch-wise feature refinement termed as patch-level attention is presented to mine internal relations among the patches,which enhances the adaptability to novel *** addition,a weighted classification loss is given to assist the fine-tuning of the classifier by combining extra features from FPN of the base training *** this way,the few-shot detection quality to novel class objects is *** on PASCAL VOC and MS COCO datasets verify the effectiveness of the method.

关键词： few-shot object detection dual-domain feature fusion patch-level attention

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Event-enhanced synthetic aperture imaging

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Science China(Information Sciences) 2025年第3期68卷 388-390页

作者： Siqi LI Shaoyi DU Jun-Hai YONG Yue GAO Beijing National Research Center for Information Science and Technology School of SoftwareTsinghua University Institute for Brain and Cognitive Sciences Beijing Laboratory of Brain and Cognitive IntelligenceTsinghua University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and ApplicationsInstitute of Artificial Intelligence and Robotics Xi'an Jiaotong University

Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field ima...

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The effects of 17β-trenbolone and bisphenol A on sexual behavior and social dominance via the hypothalamic-pituitary-gonadal axis in male mice

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Journal of Environmental Sciences 2025年第5期151卷 54-67页

作者： Xiang Zuo Minghe Sun Huijuan Bai Shuhui Zhang Jialu Luan Qian Yu Zhenhua Fu Qili Zhao Mingzhu Sun Xin Zhao Xizeng Feng College of Life Science State Key Laboratory of Medicinal Chemical BiologyThe Key Laboratory of Bioactive MaterialsMinistry of EducationNankai UniversityTianjin 300071China Institute of Robotics&Automatic Information System College of Artificial IntelligenceNankai UniversityTianjin 300071China

17β-Trenbolone(17-TB)is well documented as an environmental endocrine disruptor in aquatic biological studies,but its effects on mammals remain poorly ***,17-TB acts as a hormone with properties similar to testosterone,and the consequences of juvenile exposure on adult social behavior remain *** A(BPA)acts as an estrogen-like hormone,compared to ***-week-old male Balb/c mice were exposed orally to 17-TB(100μg/(kg·day))and BPA(4 mg/(kg·day))for 28 *** of social interactions and a three-chamber test showed that 17-TB increased virility in male mice,intensified both male and female sexual behavior,and attracted and accepted female *** also increased social dominance through tube tests inmalemice and markedly activated the c-Fos^(+)immune response in themedial prefrontal cortex(mPFC)and basal amygdala(BLA).ELISA data showed that 17-TB and BPA exposure significantly affected serum gonadotropin-releasing hormone(GnRH),growth hormone(GH),estradiol(E2),and luteinizing hormone(LH)levels,as well as testicular lesions and androgen receptor(ARβ)and estrogen receptor(ERα)*** transcriptomic analysis further confirmed that could disrupt steroid synthesis and linoleic acid-related biometabolic *** findings suggest the influence of 17-TB and BPA exposure on sexual behavior and fertility in male mice,possibly through modulation of the hypothalamic-pituitary-gonadal *** study provides insights relevant to human reproductive health and neuro-social behavioral research,and the potential risk of environmental disturbances should not be overlooked.

关键词： 17β-Trenbolone(17-TB) Bisphenol A(BPA) hypothalamic-pituitary-gonadal axis(HPG) Sex hormones Social dominance Sexual behavior

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Towards Autonomous Cardiac Ultrasound Scanning: Combining Physician Expertise and Machine intelligence

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical robotics and Bionics 2025年第2期7卷 782-792页

作者： Hao, Mingrui Zhang, Pengcheng Hou, Xilong Gu, Xiaolin Zhou, Xiao-Hu Hou, Zeng-Guang Chen, Chen Wang, Shuangyi Chinese Academy of Sciences National Key Laboratory for Multi-modal Artificial Intelligence Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100043 China Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Hong Kong Hong Kong Lingshu Medical Company Suzhou215123 China

Echocardiography serves as a prevalent modality for both heart disease diagnosis and procedural guidance in medical applications. Nevertheless, the conventional echocardiography examination heavily relies on the manual dexterity of the sonographer, leading to the suboptimal repeatability. Despite the extensive exploration of robot-assisted ultrasound systems, achieving a heightened level of automation in examinations and enhancing the practicality of these robotic platforms for primary utilization remain formidable challenges within the field. In this study, we introduce an innovative automatic acquisition method for cardiac views using a novel ultrasound robot. The method is designed to autonomously traverse and scan target positions and angular ranges to search and identify the target cardiac views. First, the target positions and angular ranges were derived from a professional sonographer’s practice on 14 cases. Then, an automatic traversal scanning method is designed integrating visual guidance, human-machine collaboration, and path planning within the framework of a novel parallel mechanism-based ultrasound robot. Finally, we explore deep metric learning to search for target ultrasound images in the traversed ultrasound video. Experiments on the test set to evaluate the target ultrasound view searching algorithm achieved a mAP of 98.8% and a Rank-1 accuracy of 98.23%. Our method has been successfully validated by data from five subjects, achieving the acquisition of standard parasternal long-axis and short-axis cardiac views essential for diagnosis, demonstrating the effectiveness of the proposed method. © 2018 IEEE.

关键词： Motion planning

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Bridging the Gap Between Semantics and Geometry in SLAM: A Semantic-Geometric Tight-Coupling Monocular Visual Object SLAM System

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IEEE Transactions on robotics 2025年 41卷 3078-3098页

作者： Zhu, Wenbin Yuan, Jing Zhang, Xuebo Chen, Fei Nankai University College of Artificial Intelligence Tianjin300350 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Nankai University Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Tianjin300350 China

Existing object-level SLAM methods often overlook the correspondence between semantic information and geometric features, resulting in a significant gap between them within SLAM frameworks. To tackle this issue, this paper proposes TiMoSLAM, a semantic-geometric tight-coupling monocular visual object SLAM system, which considers a rigorous correspondence between semantics and geometry across all steps of SLAM. Initially, a general Semantic Relation Graph (SRG) is developed to consistently represent semantic information alongside geometric features. Detailed analyses on complete constraints of the geometric feature combinations on estimation of 3D cuboid model are performed. Subsequently, a Compound Hypothesis Tree (CHT) is proposed to incrementally construct the object-specific SRG and concurrently estimate the 3D cuboid model of an object, ensuing semantic-geometric consistency in object representation and estimation. Special attention is given to the matching errors between geometric features and objects during the optimization of camera poses and object parameters. The effectiveness of this method is validated on various datasets, as well as in real-world environments. © 2004-2012 IEEE.

关键词： Object detection

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Real-Time Optimal Charging Strategy for Battery Swapping Stations Under Time-of-Use Pricing

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IEEE Transactions on Network Science and Engineering 2025年第3期12卷 2043-2056页

作者： Yan, Huanyu Sun, Chenxi Liao, Huanxin Tang, Xiaoying School of Science and Engineering Chinese University of Hong Kong Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518129 China Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network Shenzhen518172 China

Battery Swapping Stations (BSSs), the emerging infrastructure for electric vehicles (EVs), are swiftly proliferating facilities bridging energy and transportation networks. As the power grid's demand-side-management approach evolves, the optimal charging strategy for competitive BSSs needs further investigation. This paper proposes a real-time optimal charging strategy for each non-cooperative BSS operating under a unified power grid that implements Time-of-use (TOU) pricing. We construct a non-cooperative game model to encapsulate the competition among BSSs under the EV reservation mechanism. To resolve the game, we prove the existence of a unique Nash Equilibrium under any number of players and swapping prices, and design an algorithm to solve the equilibrium. Additionally, we suggest strategies for EVs without reservations. Specifically, we demonstrate the conditions under which the BSS profit diminishes when serving directly drive-in EVs. We also establish that the potential cost arising from no-show reserved EVs is limited by a constant. Simulations validate that our proposed battery charging strategy significantly enhances the profits of a 12-station BSS system. Moreover, the real-time optimal charging strategy also accomplishes peak-shaving over multiple time periods. © 2013 IEEE.

关键词： Charging stations

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Efficient Matrix-Based Multi-view Projection Features Combined for Multi-modal 3D Semantic Segmentation 21st

Efficient Matrix-Based Multi-view Projection Features Combin...

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21st Pacific Rim International Conference on artificial intelligence, PRICAI 2024

作者： Zhao, Jiayu Wei, Fei-Fei Liang, Anqi Mei, Kuizhi College of Artificial Intelligence Xi’an Jiaotong University Xi’an China National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center of Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China

ISBN: (纸本)9789819601219

This paper introduces BFVTModel, an efficient 3D semantic segmentation Model. Multi-modal segmentators, which employ LiDAR and Camera sensors as input, have gained popularity owing to their capacity to leverage the semantic information in image data and complementary details in point cloud data. However, the segmentation model using multi-modal input faces some problems, such as the modal consistency problem and the model complexity problem. In this paper, we propose utilizing the idea of an Occupancy-based multi-view feature combination method to obtain the 3D information of the features of the two modalities independently. We also design a projection structure to obtain the three-axis features in different modalities according to the information, including the main view, side view, and top view features. We construct a module called Feature View Transform (FVT) that combines three-axis plane features with bias. The CNN neural network is used to replace attention mechanisms, reducing the dimensionality of the original three-dimensional space matrix, thereby reducing the parameter count and increasing the model’s speed. We used a bilinear mapping structure to fuse LiDAR and Camera features and complete the 3D semantic segmentation task. We validate the model on the NuScenes dataset and obtain competitive accuracy results while leading the way in efficiency evaluation metrics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Semantic Segmentation

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Thin and Flexible Breeze-Sense Generators for Non-Contact Haptic Feedback in Virtual Reality

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Nano-Micro Letters 2025年第6期17卷 397-410页

作者： Kaijun Zhang Zhe Liu Yexi Zhou Zhaoyang Li Dazhe Zhao Xiao Guan Tianjun Lan Yanting Gong Bingpu Zhou Junwen Zhong Department of Electromechanical Engineering and Centre for Artificial Intelligence and Robotics University of MacaoMacao SAR 999078People’s Republic of China Joint Key Laboratory of the Ministry of Education Institute of Applied Physics and Materials EngineeringUniversity of MacaoMacao SAR 999078People’s Republic of China

In the realm of virtual reality(VR),haptic feedback is integral to enhance the immersive experience;yet,existing wearable devices predominantly rely on skin contact feedback,lacking options for compact and non-contact breeze-sense ***,we propose a compact and non-contact working model piezoelectret actuator for providing a gentle and safe breeze *** easy-fabricated and flexible breeze-sense generator with thickness around 1 mm generates air flow pressure up to~163 Pa,which is significantly sensed by human *** a typical demonstration,the breeze-sense generators array showcases its versatility by employing multiple coded modes for non-contact information *** thin thinness and good flexibility facilitate seamless integration with wearable VR setups,and the wearable arrays empower volunteers to precisely perceive the continuous and sudden breeze senses in the virtual *** work is expected to inspire developing new haptic feedback devices that play pivotal roles in human-machine interfaces for VR applications.

关键词： Virtual reality Wearable electronics Non-contact haptic feedback Breeze-sense Piezoelectret actuator

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