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arXiv 2025年

作者： Huang, Heye Li, Zheng Cheng, Hao Wang, Haoran Jiang, Junkai Li, Xiaopeng Zgonnikov, Arkady Department of Civil and Environmental Engineering University of Wisconsin-Madison WI53706 United States School of Vehicle and Mobility Tsinghua University Beijing100084 China Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai200092 China Department of Cognitive Robotics Delft University of Technology Delft2628 Netherlands

Ensuring safe interactions between autonomous vehicles (AVs) and human drivers in mixed traffic systems remains a major challenge, particularly in complex, high-risk scenarios. This paper presents a cognition-decision framework that integrates individual variability and commonalities in driver behavior to quantify risk cognition and model dynamic decision-making. First, a risk sensitivity model based on a multivariate Gaussian distribution is developed to characterize individual differences in risk cognition. Then, a cognitive decision-making model based on the drift diffusion model (DDM) is introduced to capture common decision-making mechanisms in high-risk environments. The DDM dynamically adjusts decision thresholds by integrating initial bias, drift rate, and boundary parameters, adapting to variations in speed, relative distance, and risk sensitivity to reflect diverse driving styles and risk preferences. By simulating high-risk scenarios with lateral, longitudinal, and multidimensional risk sources in a driving simulator, the proposed model accurately predicts cognitive responses and decision behaviors during emergency maneuvers. Specifically, by incorporating driver-specific risk sensitivity, the model enables dynamic adjustments of key DDM parameters, allowing for personalized decision-making representations in diverse scenarios. Comparative analysis with IDM, Gipps, and MOBIL demonstrates that DDM more precisely captures human cognitive processes and adaptive decision-making in high-risk scenarios. These findings provide a theoretical basis for modeling human driving behavior and offer critical insights for enhancing AV-human interaction in real-world traffic environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Gaussian distribution

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Generalized Kernel Maximum Correntropy Criterion with Variable Center: Formulation and Performance Analysis

SSRN

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SSRN 2023年

作者： Hou, Xinyan Zhao, Haiquan Long, Xiaoqiang Chen, Badong Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle Ministry of Education School of Electrical Engineering Southwest Jiaotong University Chengdu610031 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China

Recently, the kernel adaptive filtering algorithm based on the generalized maximum correntropy criterion (GMCC) has attracted a lot of attention due to its excellent nonlinear modeling ability and robustness to non-Gaussian noise. However, since the default center of the GMCC is located at zero, it leads to a significant deterioration of the algorithm performance in the non-zero mean noise environment. To overcome the above-mentioned problem, this paper proposes a kernel adaptive filtering algorithm based on the GMCC with variable center (GMCC-VC) called generalized kernel maximum correntropy criterion with variable center (GKMCC-VC). The center of the proposed algorithm can be located at any position, which reduces the impact of non-zero mean noise on the performance of the *** addition, the online vector quantization (VQ) method is introduced to the GKMCC-VC algorithm for suppressing the increasing network size. The probability of divergence, the mean-square steady-state behavior, and the convergence condition of the GKMCC-VC algorithm is also obtained under some assumptions. The potential relationship between the GMCC-VC and the generalized minimum error entropy (GMEE) criteria is discussed in the paper. Finally, the simulation results verify the superiority of the proposed algorithm in modeling nonlinear systems and the correctness of the theoretical model. © 2023, The Authors. All rights reserved.

关键词： Adaptive filtering

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Mechanism Design and Motion Analysis of Heavy⁃Load Transfer Robot with Parallel Four⁃Bar Mechanism

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Transactions of Nanjing University of Aeronautics and Astronautics 2022年第5期39卷 606-618页

作者： ZHANG Jing WANG Dongbao WU Guangping GUO Hongwei LIU Rongqiang College of Mechanical and Vehicle Engineering Taiyuan University of TechnologyTaiyuan 030024P.R.China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240P.R.China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001P.R.China

Heavy-load transfer robots are widely used in automobile production and machinery manufacturing to improve production *** order to meet the needs of large billet transfer,a 4-DOF transfer robot is designed in this paper,which consists of parallel four-bar *** Jacobian matrix referring to the mapping matrix from the joint velocity to the operating space velocity of the transfer robot can be solved by the differential-vector *** mean value of the Jacobian matrix condition number in the workspace is used as the global performance index of the robot velocity and the optimization *** constraint condition is established based on the actual working *** the linkage length optimization is carried out to decrease the length of the linkage and to increase the global performance index of *** total length of robot rods is reduced by 6.12%.The global performance index of velocity is improved by 45.15%.Taking the optimized rod length as the mechanism parameter,the distribution of the motion space of the transfer robot is ***,the results show that the proposed method for establishing the Jacobian matrix of the lower-mobility robot and for the optimization of the rods based on the velocity global performance index is accurate and *** workspace distribution of the robot meets the design requirements.

关键词： parameter optimization motion analysis mechanism design transfer robot heavy-load

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A Soft Robotic System Imitating the Multimodal Sensory Mechanism of Human Fingers for Intelligent Grasping and Recognition

SSRN

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SSRN 2024年

作者： Xu, Jinsui Xu, Boyi Zhan, Hao Xie, Zhijie Tian, Zhen Lu, Yifan Wang, Zheping Yue, Honghao Yang, Fei South China University of Technology China State Key Laboratory of Robotics and System School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China Wu Xianming School of Intelligent Engineering South China University of Technology Guangzhou510641 China College of Mechanical and Electrical Engineering Northeast Forestry University Harbin150042 China Science and Technology on Space Physics Laboratory China Academy of Launch Vehicle Technology Beijing100000 China

The sensory function is crucial for achieving precise feedback control and environmental interaction in soft robots. Therefore, the multimodal sensory capabilities that mimic human fingers have always been a research hotspot. This study proposes a design method for a soft robotic gripper that can emulate the multimodal perception mechanism of human fingers and achieve high-precision recognition of grasped objects using machine learning algorithms. In addition, a finger texture structure inspired by human fingerprints is designed using a negative pressure-induced buckling method to enhance the soft gripper's ability to perceive minute surface textures. Inspired by slow adapting (SA) receptors and fast adapting (FA) receptors of human fingers, this study designs a capacitive curvature sensor (CS) and a triboelectric texture sensor (TS) to detect the size, material, and texture of objects. Furthermore, a non-contact medium identification sensor (MIS), having a sensitivity of more than 1300 times higher compared to the traditional MISs, is fabricated using the principle of electromagnetic resonance. It is shown that by employing a deep learning-based multi-channel feature fusion network, the soft grasping system with multimodal sensing can achieve an object recognition accuracy of 98.43%. This work provides an innovative approach for the application of soft robots in various fields, such as logistics sorting and food safety. © 2024, The Authors. All rights reserved.

关键词： Textures

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

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Collaborative Perception Datasets for Autonomous Driving: A Review

arXiv

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arXiv 2025年

作者： Wang, Naibang Shang, Deyong Gong, Yan Hu, Xiaoxi Song, Ziying Yang, Lei Huang, Yuhan Wang, Xiaoyu Lu, Jianli Beijing100083 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China State Key Laboratory of Intelligent Green Vehicle and Mobility Tsinghua University Beijing100084 China Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence School of Computer Science and Technology Beijing Jiaotong University China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore School of Mechatronics Engineering Harbin Institute of Technology 92 West Dazhi St. Harbin China Department of Electronic & Electrical Engineering University of Bath United Kingdom

Collaborative perception has attracted growing interest from academia and industry due to its potential to enhance perception accuracy, safety, and robustness in autonomous driving through multi-agent information fusion. With the advancement of vehicle-to-Everything (V2X) communication, numerous collaborative perception datasets have emerged, varying in cooperation paradigms, sensor configurations, data sources, and application scenarios. However, the absence of systematic summarization and comparative analysis hinders effective resource utilization and standardization of model evaluation. As the first comprehensive review focused on collaborative perception datasets, this work reviews and compares existing resources from a multi-dimensional perspective. We categorize datasets based on cooperation paradigms, examine their data sources and scenarios, and analyze sensor modalities and supported tasks. A detailed comparative analysis is conducted across multiple dimensions. We also outline key challenges and future directions, including dataset scalability, diversity, domain adaptation, standardization, privacy, and the integration of large language models. To support ongoing research, we provide a continuously updated online repository of collaborative perception datasets and related literature: https://***/frankwnb/Collaborative-Perceptio n-Datasets-for-Autonomous-Driving. © 2025, CC BY-SA.

关键词： Sensor data fusion

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Design of a Passive Gait‑based Ankle‑foot Exoskeleton with Self‑adaptive Capability

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Chinese Journal of Mechanical engineering 2020年第3期33卷 86-96页

作者： Xiangyang Wang Sheng Guo Bojian Qu Majun Song Haibo Qu Robotics Institute School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control TechnologyMinistry of EducationBeijing Jiaotong UniversityBeijing 100044China School of Engineering Science KTH Royal Institute of Technology10044 StockholmSweden.

Propulsion during push-off is the key to realizing human *** have evolved a way of walking with high energy utilization,but it can be further *** inspiration from the muscle-tendon unit,a passive spring-actuated ankle-foot exoskeleton is designed to assist with human walking and to lengthen walking duration by mechanically enhancing walking *** of the gait events is realized using a smart clutch,which is designed to detect the contact states between the shoe sole and the ground,and automatically switch its working *** engagement of a suspended spring behind the human calf muscles is hence controlled and is in synchrony with *** device is completely passive and contains no external power *** is stored and returned passively using the *** our walking trials,the soleus electromyography activity is reduced by as much as 72.2%when the proposed ankle-foot exoskeleton is worn on the human *** influence of the exoskeleton on walking habits is also *** results show the potential use of the exoskeleton in humans’daily life.

关键词： Ankle-foot exoskeleton Energy cost Self-adaptiveness Human augmentation

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Resilient Control of DC Microgrids Against FDI Attacks on Communication Links

Resilient Control of DC Microgrids Against FDI Attacks on Co...

引用

IEEE Conference on Decision and Control

作者： Qifen Liu Hongwei Zhang Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle Ministry of Education School of Electrical Engineering Southwest Jiaotong University Chengdu Sichuan P.R. China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Guangdong P.R. China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen Guangdong P.R. China

The intrusion of cyber attacks on communication network in microgrids will deteriorate the control performance. And it is even more difficult to effectively extract unknown attacks to obtain correct transmitted information for a direct current (DC) microgrid. In this paper, a resilient controller is designed to mitigate the adverse effects of false data injection (FDI) attacks, where the DC microgrids could restore their control objectives, including current sharing and voltage regulation. Furthermore, the restriction on the number of healthy neighbors is relaxed in this proposed control scheme compared with related researches on mitigating FDI attacks on communication links. The effectiveness of this resilient controller is illustrated by numerical examples.

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The consistent behavior of negative Poisson's ratio with interlayer interactions

arXiv

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arXiv 2022年

作者： Wang, Yancong Yu, Linfeng Zhang, Fa Chen, Qiang Zhan, Yuqi Zheng, Xiong Wang, Huimin Qin, Zhenzhen Qin, Guangzhao State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle Engineering Hunan University Changsha410082 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Hunan Key Laboratory for Micro-Nano Energy Materials & Device School of Physics and Optoelectronics Xiangtan University Hunan Xiangtan411105 China School of Physics and Microelectronics Zhengzhou University Zhengzhou450001 China

Negative Poisson's ratio (NPR) is of great interest due to the novel applications in lots of fields. Films are the most commonly used form in practical applications, which involves multiple layers. However, the effect of interlayer interactions on the NPR is still unclear. In this study, based on first principles calculations, we systematically investigate the effect of interlayer interactions on the NPR by comparably studying single-layer graphene, few-layer graphene, h-BN, and graphene-BN heterostructure. It is found that they almost have the same geometry-strain response. Consequently, the NPR in bilayer graphene, triple-layer graphene, and graphene-BN heterostructure are consistent with that in single-layer graphene and h-BN. The fundamental mechanism lies in that the response to strain of the orbital coupling are consistent under the effect of interlayer interactions. The deep understanding of the NPR with the effect of interlayer interactions as achieved in this study is beneficial for the future design and development of micro-/nanoscale electromechanical devices with novel functions based on nanostructures. © 2022, CC BY-NC-SA.

关键词： Graphene

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Fluorine Ions Assist Titanium-Based Perylene Diimide to Achieve Over 500h Photocatalytic Stability

SSRN

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SSRN 2025年

作者： Li, Junqiang Fang, Jiongchong Liang, Huiqiang Wei, Zhenghao Fang, Jun Qiu, Longbin Lu, Xinxin Yang, Fuyuan Zeng, Guosong Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Southern University of Science and Technology Shenzhen518055 China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China PetroChina Shenzhen New Energy Research Institute Co. Ltd. Shenzhen518055 China School of Vehicle and Mobility Tsinghua University Beijing100084 China SUSTech Energy Institute for Carbon Neutrality Southern University of Science and Technology Shenzhen518055 China

Photocatalytic water splitting using semiconductor catalysts for green hydrogen production is a critical step toward global carbon neutrality. However, the rapid decline in catalytic activity due to unstable molecular structure and photo-corrosion limits the practical application of many organic semiconductors. In this study, two titanium-coordinated perylene diimide catalysts (TiF-PDI and TiC-PDI) were synthesized via a wet chemical approach, demonstrating impressive hydrogen evolution reaction (HER) activities of 584 and 510 μmol·g−1·h−1 under near-atmospheric conditions,respectively, representing a 7-8-fold enhancement compared to H2PDI. Particularly, TiF-PDI retained ~80% of its initial catalytic activity after 500 hours of continuous illumination under room temperature and near atmospheric pressure, demonstrating the highest HER long-term stability of perylene-based semiconductors to date. The introduction of Ti4+ ions facilitated charge separation and transfer, while F- ions played a vital role in further enhancing system polarization, stabilizing photogenerated excitons, and mitigating Ti4+ ions leaching by intercalating into the molecular lattice. This cooperative regulation of dual ions improved both photocatalytic performance and durability. This work provides valuable insights into structural modification and charge stabilization in designing high-performance and long-lived photocatalysts for sustainable energy applications. © 2025, The Authors. All rights reserved.

关键词： Atmospheric corrosion

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