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33rd British Machine Vision Conference Proceedings, BMVC 2022

作者： Yu, Yinfeng Cao, Lele Sun, Fuchun Liu, Xiaohong Wang, Liejun Department of Computer Science and Technology State Key Lab on Intelligent Technology and Systems Tsinghua University Beijing China Motherbrain EQT Stockholm Sweden College of Information Science and Engineering Xinjiang University Urumqi China

Audio-visual embodied navigation, as a hot research topic, aims training a robot to reach an audio target using egocentric visual (from the sensors mounted on the robot) and audio (emitted from the target) input. The audio-visual information fusion strategy is naturally important to the navigation performance, but the state-of-the-art methods still simply concatenate the visual and audio features, potentially ignoring the direct impact of context. Moreover, the existing approaches requires either phase-wise training or additional aid (e.g. topology graph and sound semantics). Up till this date, the work that deals with the more challenging setup with moving target(s) is still rare. As a result, we propose an end-to-end framework FSAAVN (feature self-attention audio-visual navigation) to learn chasing after a moving audio target using a context-aware audio-visual fusion strategy implemented as a self-attention module. Our thorough experiments validate the superior performance (both quantitatively and qualitatively) of FSAAVN in comparison with the state-of-the-arts, and also provide unique insights about the choice of visual modalities, visual/audio encoder backbones and fusion patterns. © 2022. The copyright of this document resides with its authors.

关键词： Robots

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Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 146-159页

作者： Yinlong Zhang Wei Liang Mingze Yuan Hongsheng He Jindong Tan Zhibo Pang Key Laboratory of Networked Control Systems Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Computing Wichita State UniversityWichita 67260 USA Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeTN 37996 USA Department of Automation Technology ABB Corporate Research SwedenVasteras 72178Sweden Department of Intelligent Systems Royal Institute of Technology(KTH)Stockholm 11428Sweden

Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment ***,traditional calibrations suffer inaccuracy and *** address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying *** our method,the spatial relationship is geometrically correlated between the sensing units and robotic *** decoupled estimations on rotation and translation could reduce the coupled errors during the ***,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and *** calibration has been evaluated on our developed *** the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,*** comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.

关键词： Calibration inertial measurement unit(IMU) monocular camera robotic arm spiral moving trajectory

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Design a Compliant Pivot with Nearly Zero Axial Drift and High Radial Stiffness 24th

Design a Compliant Pivot with Nearly Zero Axial Drift and Hi...

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24th IFToMM China International Conference on Mechanism and Machine Science and Engineering, IFToMM CCMMS 2024

作者： Bai, Ruiyu Ma, Fulei Li, Bo Chen, Guimin State Key Laboratory for Manufacturing Systems Engineering and Shaanxi Key Lab of Intelligent Robots Xi’an Jiaotong University Shaanxi Xi’an710049 China School of Electro-Mechanical Engineering Xidian University Shaanxi Xi’an710071 China

ISBN: (纸本)9789819614639

Compliant pivots are widely used in mechanical systems to provide accurate and repeatable rotations. However, the significant axial drift and low radial stiffness during the rotation of compliant pivots pose great challenges in the design and control of compliant pivot-based mechanisms. To mitigate these difficulties, this paper proposes a novel compliant pivot with nearly zero axial drift and high radial stiffness based on the rigid-body replacement method and symmetric arrangement. By designing a series of symmetric rigid linkages with one degree of freedom and substituting the rigid joints in them with compliant elements, several compliant building blocks are obtained. When arranging these building blocks in a circle, compliant pivots with zeros axial drift are obtained. By discussing the source of compliance in the radial direction, a pivot with high radial stiffness is obtained. The modeling of the pivot using a chained beam constraint model and a nonlinear finite element model demonstrates the kinetostatic properties of the pivot. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Machine design

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Chaining Simultaneous Thoughts for Numerical Reasoning

Chaining Simultaneous Thoughts for Numerical Reasoning

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2022 Findings of the Association for Computational Linguistics: EMNLP 2022

作者： Shao, Zhihong Huang, Fei Huang, Minlie The CoAI Group DCST Tsinghua University Institute for Artificial Intelligence State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

Given that rich information is hidden behind ubiquitous numbers in text, numerical reasoning over text should be an essential skill of AI systems. To derive precise equations to solve numerical reasoning problems, previous work focused on modeling the structures of equations, and has proposed various structured decoders. Though structure modeling proves to be effective, these structured decoders construct a single equation in a pre-defined autoregressive order, potentially placing an unnecessary restriction on how a model should grasp the reasoning process. Intuitively, humans may have numerous pieces of thoughts popping up in no pre-defined order;thoughts are not limited to the problem at hand, and can even be concerned with other related problems. By comparing diverse thoughts and chaining relevant pieces, humans are less prone to errors. In this paper, we take this inspiration and propose CANTOR, a numerical reasoner that models reasoning steps using a directed acyclic graph where we produce diverse reasoning steps simultaneously without pre-defined decoding dependencies, and compare and chain relevant ones to reach a solution. Extensive experiments demonstrated the effectiveness of CANTOR under both fully-supervised and weakly-supervised settings. © 2022 Association for Computational Linguistics.

关键词： Directed graphs

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Adhesion strength of tetrahydrofuran hydrates is dictated by substrate stiffness

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Petroleum Science 2024年第1期21卷 667-673页

作者： Yan-Wen Lin Tong Li Yi Zhang Wei-Wei Yan Xiao-Ming Chen Zhi-Sen Zhang Jian-Yang Wu Department of Physics Research Institute for Biomimetics and Soft MatterJiujiang Research Institute and Fujian Provincial Key Laboratory for Soft Functional Materials ResearchXiamen UniversityXiamen361005FujianChina Key Laboratory of Marine Materials and Related Technologies Zhejiang Key Laboratory of Marine Materials and Protective TechnologiesNingbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo315201ZhejiangChina Key Laboratory of Icing and Anti/De-icing China Aerodynamics Research and Development CenterMianyang621000SichuanChina Micro-and Nano-technology Research Center State Key Laboratory for Manufacturing Systems EngineeringXi’an Jiaotong UniversityXi’an710049ShaanxiChina Electronic Materials Research Lab Key Laboratory of the Ministry of EducationXi’an Jiaotong UniversityXi’an710049ShaanxiChina NTNU Nanomechanical Lab Norwegian University of Science and Technology(NTNU)Trondheim7491Norway

Understanding the hydrate adhesion is important to tackling hydrate accretion in ***,the relationship between the Tetrahydrofuran(THF)hydrate adhesion strength(AS)and surface stiffness on elastic coatings is systemically examined by experimental shear force measurements and theoretical *** mechanical factor-elastic modulus of the coatings greatly dictates the hydrate AS,which is explained by the adhesion mechanics theory,beyond the usual factors such as wettability and structural ***,the hydrate AS increases with reducing the thickness of the elastic coatings,resulted from the decrease of the apparent surface elastic *** effect of critical thickness for the elastic materials with variable elastic modulus on the hydrate AS is also *** study provides deep perspectives on the regulation of the hydrate AS by the elastic modulus of elastic materials,which is of significance to design anti-hydrate surfaces for mitigation of hydrate accretion in petro-pipelines.

关键词： Hydrate Adhesion strength Elastic modulus Coatings

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Efficient learning of robust quadruped bounding usingpretrained neural networks

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IET Cyber-systems and Robotics 2022年第4期4卷 331-338页

作者： Zhicheng Wang Anqiao Li Yixiao Zheng Anhuan Xie Zhibin Li Jun Wu Qiuguo Zhu Institute of Cyber-Systems and Control Zhejiang UniversityZhejiangChina Intelligent Robot Research Center Zhejiang LabZhejiangChina Department of Computer Science University College LondonLondonUK State Key Laboratory of Industrial Control Technology Zhejiang UniversityZhejiangChina

Bounding is one of the important gaits in quadrupedal locomotion for negotiating *** authors proposed an effective approach that can learn robust bounding gaits more efficiently despite its large variation in dynamic body *** authors first pretrained the neural network(NN)based on data from a robot operated by conventional model-based controllers,and then further optimised the pretrained NN via deep reinforcement learning(DRL).In particular,the authors designed a reward function considering contact points and phases to enforce the gait symmetry and periodicity,which improved the bounding *** NN-based feedback controller was learned in the simulation and directly deployed on the real quadruped robot Jueying Mini successfully.A variety of environments are presented both indoors and outdoors with the authors’*** authors’approach shows efficient computing and good locomotion results by the Jueying Mini quadrupedal robot bounding over uneven *** cover image is based on the Research Article Efficient learning of robust quadruped bounding using pretrained neural networks by Zhicheng Wang et al.,https://***/10.1049/csy2.12062.

关键词： legged locomotion reinforcement learning robot learning

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AMOR: a recipe for building adaptable modular knowledge agents through process feedback 24

AMOR: a recipe for building adaptable modular knowledge agen...

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： Jian Guan Wei Wu Zujie Wen Peng Xu Hongning Wang Minlie Huang The CoAI group DCST Institute for Artificial Intelligence State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China and Ant Group Ant Group The CoAI group DCST Institute for Artificial Intelligence State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9798331314385

The notable success of large language models (LLMs) has sparked an upsurge in building language agents to complete various complex tasks. We present AMOR, an agent framework based on open-source LLMs, which reasons with external knowledge bases and adapts to specific domains through human supervision to the reasoning process. AMOR builds reasoning logic over a finite state machine (FSM) that solves problems through autonomous executions and transitions over disentangled modules. This allows humans to provide direct feedback to the individual modules, and thus naturally forms process supervision. Based on this reasoning and feedback framework, we develop AMOR through two-stage fine-tuning: warm-up and adaptation. The former fine-tunes the LLM with examples automatically constructed from various public datasets, enabling AMoR to generalize across different knowledge environments, while the latter tailors AMOR to specific domains using process feedback. Extensive experiments across multiple domains demonstrate the advantage of AMoR to strong baselines, thanks to its FSM-based reasoning and process feedback mechanism. The code and data are publicly available at https://***/JianGuanTHU/AMOR.

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Fusing Data-and Model-driven Methods for RUL Prediction in Smart Manufacturing systems

Fusing Data-and Model-driven Methods for RUL Prediction in S...

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第43届中国控制会议

作者： Hongjie Cao Wei Xiao Jian Sun Ming-Gang Gan Gang Wang National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Remaining useful life(RUL) is of significance in prognostic and health management(PHM) of machinery equipment. The state-of-the-art RUL prediction methods, including data-driven, model-based, and hybrid approaches, suffer from constraints like incomplete/imprecise physical models, uncertainties in degradation processes, and measurement data noise. To address these constraints, a novel hybrid model-and data-driven RUL prediction approach is proposed in this paper, which leverage the strengths of data-based and model-driven approaches. The proposed method integrates an extended Kalman filter to estimate stochastic degradation model parameters and a multi-head attention transformer to extract information from sensor data. A regression token is introduced to seamlessly fuse the deep learning model and the stochastic filtering method. Numerical experiments conducted with real-world rolling bearing degradation datasets underscore the superiority of the proposed approach compared to competing methodologies.

关键词： Hybrid driven method Remaining useful life prediction Extended Kalman filter Multi-head attention mechanism

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Trajectory Planning Method for Tractor-trailer System Based on Nonlinear Model Predictive Control

Trajectory Planning Method for Tractor-trailer System Based ...

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第43届中国控制会议

作者： Bobo Jia Liang Gao Daiwei Li Yi Yang Mengyin Fu Shanshan Xie National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology School of Automation Nanjing University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The tractor-trailer system has the characteristics of high state dimension,complex constraints and poor internal stability in trajectory ***,this paper proposed a trajectory planning method for tractor-trailer system based on nonlinear model predictive control(NMPC) in static and dynamic ***,an NMPC optimization problem is formulated by constructing performance indicators and integrating the constraints of the ***,an approximate optimal path is found as a reference solution for the warm start of the optimization problem by RRT* sampling in high dimensional state ***,the NMPC problem is solved by Optimization Engine(OpEn) ***,simulation in different scenarios demonstrated the effectiveness and efficiency of the proposed method.

关键词： Tractor-trailer System Trajectory Planning Nonlinear Model Predictive Control

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Fabrication and characterization of high-sensitivity,wide-range,and flexible MEMS thermal flow velocity sensors

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Microsystems & Nanoengineering 2024年第4期10卷 139-151页

作者： Min Li Guangzhao Qin Chen Jia Danyu Zhang Zhikang Li Xiangguang Han Shusheng Xu Libo Zhao Guoxi Luo Cunlang Liu Ping Yang Qijing Lin State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemXi’an Jiaotong UniversityXi’an 710049China School of Instrument Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai Yantai 264000China Brightstone Innovation(Yantai)Research Institute for Micronano Sensing Technology Yantai 264006China Xi’an Jingwei Sensing Technology Co. Ltd.Xi’an 712000China

With the rapid development of various fields,including aerospace,industrial measurement and control,and medical monitoring,the need to quantify flow velocity measurements is *** is difficult for traditional flow velocity sensors to fulfill accuracy requirements for velocity measurements due to their small ranges,susceptibility to environmental impacts,and ***,to optimize sensor performance,a flexible microelectromechanical system(MEMS)thermal flow sensor is proposed that combines the working principles of thermal loss and thermal temperature difference and utilizes a flexible cavity substrate made of a low-thermal-conductivity polyimide/SiO_(2)(PI/SiO_(2))composite porous film to broaden the measurement range and improve the *** measurement results show that the maximum measurable flow velocity can reach 30 m/s with a resolution of 5.4mm/*** average sensitivities of the sensor are 59.49 mV/(m s−1)in the medium-to-low wind velocity range of 0–2 m/s and 467.31 mV/(m s^(−1))in the wind velocity range of 2–30 m/*** sensor proposed in this work can enable new applications of flexible flow sensors and wearable devices.

关键词： flow thermal utilize

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