检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Sun, Yang Poskitt, Christopher M. Wang, Kun Sun, Jun School of Computing and Information Systems Singapore Management University Singapore State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

Autonomous Vehicles (AVs) are advancing rapidly, with Level-4 AVs already operating in real-world conditions. Current AVs, however, still lag behind human drivers in adaptability and performance, often exhibiting overly conservative behaviours and occasionally violating traffic laws. Existing solutions, such as runtime enforcement, mitigate this by automatically repairing the AV’s planned trajectory at runtime, but such approaches lack transparency and should be a measure of last resort. It would be preferable for AV repairs to generalise beyond specific incidents and to be interpretable for users. In this work, we propose FIXDRIVE, a framework that analyses driving records from near-misses or law violations to generate AV driving strategy repairs that reduce the chance of such incidents occurring again. These repairs are captured in µDrive, a high-level domain-specific language for specifying driving behaviours in response to event-based triggers. Implemented for the state-of-the-art autonomous driving system Apollo, FIXDRIVE identifies and visualises critical moments from driving records, then uses a Multimodal Large Language Model (MLLM) with zero-shot learning to generate µDrive programs. We tested FIXDRIVE on various benchmark scenarios, and found that the generated repairs improved the AV’s performance with respect to following traffic laws, avoiding collisions, and successfully reaching destinations. Furthermore, the direct costs of repairing an AV—15 minutes of offline analysis and $0.08 per violation—are reasonable in practice. Copyright © 2025, The Authors. All rights reserved.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

In Situ Surface Restructuring of γ-Mo2N for Enhanced Reverse Water-GasShift Reaction

引用

ACS Catalysis 2025年第10期15卷 8337-8344页

作者： Gong, Yeteng Jing, Yaxuan Liu, Xiaohui Wang, Yanqin Guo, Yong State Key Laboratory of Green Chemical Engineering and Industrial Catalysis School of Chemistry and Molecular Engineering East China University of Science and Technology Shanghai200237 China State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University Nanjing210023 China School of Chemistry and Chemical Engineering Shihezi University Shihezi832003 China Institute for the Environment and Health Nanjing University Suzhou Campus Suzhou215163 China

In heterogeneous catalytic systems, catalyst activation induced by reactants or products, often attributed to surface restructuring, represents a compelling phenomenon. The catalytic nature and reaction mechanism of the molybdenum nitride system in the reverse water-gas shift reaction (RWGS) remain subjects of ongoing debate, with no consensus reached to date. In this work, we demonstrate that γ-Mo2N can be effectively activated via in situ treatment under the RWGS reaction atmosphere at 500 °C, leading to a significant enhancement of its catalytic activity. A deep investigation revealed that surface restructuring is the underlying mechanism responsible for the activation of γ-Mo2N. During the RWGS process, Mo6+ species on the surface of γ-Mo2N are converted into Mo4+ under the induction of the reaction atmosphere, thereby enhancing the activation of H2 and improving the catalytic activity. Notably, the surface restructuring effect enables γ-Mo2N to achieve catalytic activity and stability comparable to those of metal-based catalysts reported in the literature. This work provides significant insight into the real active site and the pivotal role of γ-Mo2N in RWGS reactions. © 2025 American Chemical Society.

关键词： Water gas shift

来源：评论

学校读者我要写书评

暂无评论

Human-Robot Pose Tracking Based on CNN with Color and Geometry Aggregation 16th

Human-Robot Pose Tracking Based on CNN with Color and Geo...

引用

16th International Conference on Social Robotics, ICSR + InnoBiz 2024

作者： Xu, Yue Zhang, Yinlong Liu, Shuai Liu, Yuanhao Liang, Wei He, Hongsheng Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9789819611508

Accurately tracking the robotic arm and human joints is crucial to ensure safety during human-robot interaction. However, traditional pose tracking methods often exhibit insufficient performance and robustness in complex environments. The variations in the robotic arm’s environment and posture make it challenging for traditional methods to accurately capture the positions and posture of its joints. Specifically, when addressing challenges such as high similarity, occlusion, background complexity, and joint recognition failures, they often struggle to provide reliable and accurate results. To address these challenges, this paper proposes a human-robot pose tracking algorithm based on a new convolutional neural network model. To enhance detection accuracy, an improved color detection module is introduced to resolve joint misclassification. A geometric perception module is designed to accurately locate joints even under occlusion. Additionally, innovative iEMA and DBB modules are incorporated. The iEMA module employs edge detection technology to dynamically adjust thresholds for correct matching by improving the edge matching process. The DBB module refines the boundary box parameters for precise localization by introducing adaptive bounding box updates in real-time. This algorithm also integrates human pose recognition, enabling real-time pose recognition, thereby facilitating more intelligent and natural human-robot interaction. The algorithm has been rigorously evaluated on a custom-designed robotic arm platform. Experimental results validate the algorithm’s effectiveness and feasibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

来源：评论

学校读者我要写书评

暂无评论

A Velocity Tracking Approach Based on Neural Networks for a Multimodal Wheel-Legged Composite Gait on a Parallel Structure Robot

引用

IEEE/ASME Transactions on Mechatronics 2025年

作者： Xue, Junfeng Wang, Shoukun Xu, Yongkang Wang, Junzheng Beijing Institute of Technology School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

Parallel-legged robots are favored by many researchers due to their potent environmental adaptability and load capacity. However, the work efficiency of the parallel leg structure is always confined due to its uptight workspace and extremely uneven force distributed among actuators. Therefore, this article proposes a new type of wheel-legged composite gait for the parallel structure, inspired by the characteristic of variation in the pitch angle of the foot-end when a human walks. First, the kinematic inverse solution of the wheel-legged composite gait is derived, where the reverse rotation of the wheel alleviates the slipping phenomenon of the foot-end on stance stage in humanoid gait from the kinematic level. Meanwhile, numerical simulation and experiments have verified that the proposed gait can enlarge the workspace of a single leg for 25.4% and alleviate the maximum force on the actuators for 16.4% minimizing actuator wear. Besides, a legged motion speed tracking approach is implemented for dynamics of the wheel-legged composite gait. Among them, a whole body dynamics model is constructed to adjust the neural network weights enabling real-time adjustment of incremental proportion–integration–differentiation control parameters based on the foot longitudinal force, to scale up its control efficiency. Finally, to ameliorate the issue of limited contact friction between the robot and the ground, an encoding approach to identify the sliding state of the robot's foot-end in the X-Y plane has been proposed. This approach adaptively modifies both the longitudinal force threshold of the foot-end and the desired linear velocity of the robot body. These adjustments are guided by specific control rules, which aim to enhance the accuracy of speed tracking during legged motion across varying terrains. The resulting linear and yaw velocity steady errors are constrained to 0.05 m/s and 0.012 rad/s, respectively. © 1996-2012 IEEE.

关键词： Anthropomorphic robots

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous Gateway Planning for Semantic Communication in industrial Networks

引用

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Sun, Yuyi Xing, Fangyuan Guo, Zhenwei Chen, Huimin He, Shibo Hangzhou Normal University School of Information Science and Technology Hangzhou China Southeast University School of Cyber Science and Engineering Nanjing China Hangzhou Innovation Institute of Beihang University Research Center of Cyber Science and Technology Hangzhou China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China

Semantic Communication (SemCom) has become a promising approach to transmit the information entropy instead of the raw data, which can increase the transmission efficiency and robustness. SemCom recently attracts more attention on the research of Internet of Things (IoT). Previous work focused more on new SemCom framework for IoT applications or lightweight SemCom models which can be easily deployed at IoT end-devices. However, the adaptation of SemCom in industrial networks still remains to be explored. In this article, we focus on gateway planning for SemCom in industrial networks. Specifically, in order to meet the different requirements of various nodes in industrial networks, we build a heterogeneous architecture of gateway planning for SemCom. Then, the Structure-Similarity-Index-Measure (SSIM) model in SemCom is introduced to illustrate the Signal-to-Noise Ratio (SNR) and compression ratio. Based on this, we build the bridge between the SSIM and the number of gateways to analyze our problem. To apply minimum gateways to cover the heterogeneous nodes and meet the SemCom transmission conditions, we formulate the problem as an NP-hard problem and simplify the problem to find the solution. Greedy-Based Algorithm (GBA) and Heuristic-Deep Q Network (H-DQN) algorithm are designed to solve this problem, and simulations are demonstrated to compare H-DQN, Q-learning, GBA and Branch and Bound (BB). The experimental results show that H-DQN outperforms other algorithms, deploying less gateways and saving over 50% of operation time. Besides, the throughput of our system is 1.3× larger than that of the single coverage system with less gateways. © 2015 IEEE.

关键词： Gateways (computer networks)

来源：评论

学校读者我要写书评

暂无评论

SEB-Naver: A SE(2)-based Local Navigation Framework for Car-like Robots on Uneven Terrain

arXiv

引用

arXiv 2025年

作者： Li, Xiaoying Xu, Long Huang, Xiaolin Xue, Donglai Zhang, Zhihao Han, Zhichao Xu, Chao Cao, Yanjun Gao, Fei State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

Autonomous navigation of car-like robots on uneven terrain poses unique challenges compared to flat terrain, particularly in traversability assessment and terrain-associated kinematic modelling for motion planning. This paper introduces SEB-Naver, a novel SE(2)-based local navigation framework designed to overcome these challenges. First, we propose an efficient traversability assessment method for SE(2) grids, leveraging GPU parallel computing to enable real-time updates and maintenance of local maps. Second, inspired by differential flatness, we present an optimization-based trajectory planning method that integrates terrain-associated kinematic models, significantly improving both planning efficiency and trajectory quality. Finally, we unify these components into SEB-Naver, achieving real-time terrain assessment and trajectory optimization. Extensive simulations and real-world experiments demonstrate the effectiveness and efficiency of our approach. The code is at https://***/ZJU-FAST-Lab/seb_naver. Copyright © 2025, The Authors. All rights reserved.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Real-time Spatial-temporal Traversability Assessment via Feature-based Sparse Gaussian Process

arXiv

引用

arXiv 2025年

作者： Tan, Senming Hou, Zhenyu Zhang, Zhihao Xu, Long Zhang, Mengke He, Zhaoqi Xu, Chao Gao, Fei Cao, Yanjun Huzhou Institute of Zhejiang University Huzhou313000 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China

Terrain analysis is critical for the practical application of ground mobile robots in real-world tasks, especially in outdoor unstructured environments. In this paper, we propose a novel spatial-temporal traversability assessment method, which aims to enable autonomous robots to effectively navigate through complex terrains. Our approach utilizes sparse Gaussian processes (SGP) to extract geometric features (curvature, gradient, elevation, etc.) directly from point cloud scans. These features are then used to construct a high-resolution local traversability map. Then, we design a spatial-temporal Bayesian Gaussian kernel (BGK) inference method to dynamically evaluate traversability scores, integrating historical and real-time data while considering factors such as slope, flatness, gradient, and uncertainty metrics. GPU acceleration is applied in the feature extraction step, and the system achieves real-time performance. Extensive simulation experiments across diverse terrain scenarios demonstrate that our method outperforms SOTA approaches in both accuracy and computational efficiency. Additionally, we develop an autonomous navigation framework integrated with the traversability map and validate it with a differential driven vehicle in complex outdoor environments. Our code will be open-source for further research and development by the community,https://*** /ZJU-FAST-Lab/FSGP_BGK. Copyright © 2025, The Authors. All rights reserved.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

Tracailer: An Efficient Trajectory Planner for Tractor-Trailer Vehicles in Unstructured Environments

arXiv

引用

arXiv 2025年

作者： Xu, Long Chai, Kaixin An, Boyuan Gan, Jiaxiang Wang, Qianhao Zhou, Yuan Li, Xiaoying Lin, Junxiao Han, Zhichao Xu, Chao Cao, Yanjun Gao, Fei State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

The tractor-trailer vehicle (robot) consists of a drivable tractor and one or more non-drivable trailers connected via hitches. Compared to typical car-like robots, the addition of trailers provides greater transportation capability. However, this also complicates motion planning due to the robot’s complex kinematics, high-dimensional state space, and deformable structure. To efficiently plan safe, time-optimal trajectories that adhere to the kinematic constraints of the robot and address the challenges posed by its unique features, this paper introduces a lightweight, compact, and high-order smooth trajectory representation for tractor-trailer robots. Based on it, we design an efficiently solvable spatio-temporal trajectory optimization problem. To deal with deformable structures, which leads to difficulties in collision avoidance, we fully leverage the collision-free regions of the environment, directly applying deformations to trajectories in continuous space. This approach not requires constructing safe regions from the environment using convex approximations through collision-free seed points before each optimization, avoiding the loss of the solution space, thus reducing the dependency of the optimization on initial values. Moreover, a multi-terminal fast path search algorithm is proposed to generate the initial values for optimization. Extensive simulation experiments demonstrate that our approach achieves several-fold improvements in efficiency compared to existing algorithms, while also ensuring lower curvature and trajectory duration. Real-world experiments involving the transportation, loading and unloading of goods in both indoor and outdoor scenarios further validate the effectiveness of our method. The source code is accessible at https://***/ZJU-FAST-Lab/tracailer/. Copyright © 2025, The Authors. All rights reserved.

关键词： Tractors (truck)

来源：评论

学校读者我要写书评

暂无评论

SIMSE: a contrastive learning method combining sample importance metric and semantic enhancement

引用

Expert systems with Applications 2025年 286卷

作者： Gao, Yangyang Zheng, Zhi Huang, Wenjun Lin, Xiaomin College of Computer and Cyber Security Fujian Normal University Fuzhou350117 China College of Control Science and Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China

In complex application scenarios, the lack of accurate labels for training samples has positioned contrastive learning a key focus in self-supervised learning. This approach effectively extracts meaningful representations from unlabeled data. A significant challenge lies in identifying high-value samples and exploring their semantic features to improve performance. Most existing self-supervised learning methods do not focus much on mining or augmenting valuable samples, relying mainly on contrastive learning between original samples. As a result, performance suffers in cases with limited or sparse data. To address this, we propose a contrastive learning method that combines sample importance measurement and semantic enhancement, overcoming the limitations of traditional methods that only use original samples. First, we generate additional valuable samples using interpolation and apply a similarity-based strategy to better distinguish positive and negative samples, refining the sample partitioning process. Second, we design a semantic enhancement mechanism to better capture and strengthen shared high-level semantic features between samples. Third, we introduce a new metric to evaluate sample value by measuring oscillations in the learning model caused by gradients, determining the importance of each sample. We also use confidence learning to identify and correct mislabeled samples. Extensive evaluations conduct on multiple benchmark datasets demonstrate that our method improves linear classification accuracy by 2.23 %, 4.3 %, 1.6 %, 3.73 %, and 4.69 % on ImageNet-100, ImageNet-10, CIFAR-10, CIFAR-100, and STL-10, respectively. Additionally, accelerates convergence speed by 1.5x and effectively detects mislabeled samples. © 2025 Elsevier Ltd

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Adaptive Power Regulation control for Floating Wind Turbines with Guaranteed Transient Performance

引用

IEEE Transactions on Automation Science and Engineering 2025年 22卷 15588-15598页

作者： Gong, Yingjie Meng, Wenchao Geng, Hua Yang, Qinmin Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Automation Beijing100084 China Huzhou Industrial Control Technology Research Institute Huzhou313000 China

Floating offshore wind turbines (FOWTs) hold significant potential for developing wind energy in deep-sea areas. However, they are prone to additional motions, heavy workloads, and undesirable fluctuations under combined wind-wave loads. To tackle these issues, this paper presents a novel adaptive blade pitch control strategy with guaranteed transient performance for FOWTs operating in above-rated wind speed regions. This strategy effectively suppresses platform pitch motion to enhance system stability while maintaining the power output at its rated value. Specifically, this method initiates by defining a filtered regulation error to solve the non-affine nature of its model. An adaptive blade pitch controller is subsequently proposed, integrating an online learning approximator to cope with the unknown dynamics caused by unmeasurable external environmental inputs and model uncertainties. To further mitigate approximation errors, a nonlinear robust control law with adaptive gains is employed, enhancing the robustness and adaptive capabilities of the controller. Superior to the traditional adaptive controllers, a significant advantage of this strategy is its ability to quantify and ensure regulatory performance within predefined constraints during both transient and steady-state stages, thereby achieving high-performance control in power regulation. Finally, simulation studies are conducted using the OpenFAST software to show the capability of the presented blade pitch controller, which guarantees stable power generation with guaranteed transient performance. © 2004-2012 IEEE.

关键词： Robust control

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：