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IEEE International Conference on Robotics and Biomimetics

作者： Muyang Hou Zhenya Lei Haidong Hu Zhong Wang Yong Wang Le Xie Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Beijing Institute of Control Engineering Beijing China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant; on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A* which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion.

关键词： Hands Trajectory tracking Trajectory planning Service robots Stability analysis Safety Mobile robots Resource management Splines (mathematics) Trajectory optimization

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Short-Term Load Forecasting for Buildings Based on Dynamic Weighted edRVFL Model

Short-Term Load Forecasting for Buildings Based on Dynamic W...

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Chinese Automation Congress (CAC)

作者： Junwei Xie Meng Yuan Zhezhuang Xu Chi Liu Yuxiong Xia Department of Fujian Province College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Fuzhou China Fujian Huading Intelligent Manufacturing Technology Co. Ltd Fuzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Short-term load forecasting of buildings plays a key role in demand management, however, when dealing with massive data, the prevalent practice of training and testing the system as a whole overlooks pattern variations inside data and potentially limits predictive performance. To address this issue, this paper proposes an ensemble deep random vector functional link (edRVFL) model that combines adaptive ensemble clustering and dynamic weighting strategy for load forecasting of an industrial building. Firstly, the adaptive ensemble clustering that combines ordering points to identify the clustering structure and K nearest neighbor is employed to determine the electricity load usage patterns. Subsequently, the improved particle swarm optimization algorithm is applied to adjust the weights of load curves in different typical day scenarios. Finally, a dynamic weighting strategy is designed to dynamically assign model weights to two clusters, where one matches the type of predicted load pattern for the day being forecasted and another for the cluster of the previous day. The experiment in a real building verifies the effectiveness of the proposed algorithm, which has higher prediction accuracy than other comparison algorithms including one-week interval and different ensemble clustering.

关键词： Adaptation models Load forecasting Heuristic algorithms Buildings Clustering algorithms Predictive models Prediction algorithms Vectors Forecasting Load modeling

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CA-MLIF: Cross-Attention and Multimodal Low-Rank Interaction Fusion Framework for Tumor Prognostic Prediction 39

CA-MLIF: Cross-Attention and Multimodal Low-Rank Interaction...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： An, Yajun Chen, Jiale Lin, Huan Liu, Zhenbing Feng, Siyang Zhang, Hualong Lan, Rushi Liu, Zaiyi Pan, Xipeng School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China School of Artificial Intelligence and Big Data Chongqing College of Finance and Economics Chongqing402160 China Southern Medical University Guangzhou510080 China Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangzhou510080 China

ISBN: (纸本)157735897X

Cancer is a leading cause of death worldwide due to its aggressive nature and complex variability. Accurate prognosis is therefore challenging but essential for guiding personalized treatment and follow-up. Previous research often relied on single data sources, missing the opportunity to combine various types of patient information for more comprehensive survival predictions. To address these challenges, we propose a two-stage fusion method named Cross-Attention and Multimodal Low-Rank Interaction Fusion Framework (CA-MLIF). In the first stage, we propose a CA mechanism for real-time feature updates and cross-modal mutual learning to capture rich semantic information. In the second stage, we design a novel multimodal low-rank interaction fusion method for survival prediction. Specifically, we present modal attention mechanism (MAM) for feature filtration, low-rank multimodal fusion (LMF) for model complexity reduction, and optimal weight concatenation (OWC) for maximizing feature integration. Extensive experiments on two public datasets TCGA-GBMLGG and TCGA-KIRC, as well as a multi-center in-house lung adenocarcinoma (LUAD) dataset validate the effectiveness of CA-MLIF, which demonstrate that our method outperforms existing approaches in survival prediction under both pathology-gene fusion and CT-pathology fusion scenarios. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Learning to rank

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Research of Microstructure,Phase,and Mechanical Properties of Aluminum-Dross-Based Porous Ceramics

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Journal of Renewable Materials 2023年第7期11卷 3057-3072页

作者： Liang Yu Yuan Liu Xiuling Cao Yulong Yan Chen Zhang Yanli Jiang Key Laboratory of New Processing Technology for Nonferrous Metals&Materials Guilin University of TechnologyGuilin541004China Guangxi Scientific Experiment Center of Mining Metallurgy and EnvironmentGuilin University of TechnologyGuilin541004China Collaborative Innovation Center for Exploration of Nonferrous Metal Deposits and Efficient Utilization of Resources Guilin University of TechnologyGuilin541004China Hebei Technology Innovation Center for Intelligent Development and Control of Underground Built Environment School of Exploration Technology and EngineeringHebei GEO UniversityShijiazhuang050031China

In this study,the effect of sintering temperature and the addition of kaolin,a sintering agent,on the microscopic,phase,and mechanical properties of ceramics were investigated using secondary aluminum dross(SAD)as the main component in the manufacturing of *** basic phases of the ceramics were Al_(2)O_(3),MgAl_(2)O_(4),NaAl_(11)O_(17),and SiO_(2)without the addition of *** diffraction peaks of MgAl_(2)O_(4),NaAl_(11)O_(17),and SiO_(2)kept decreasing while those of Al_(2)O_(3)kept increasing with an increase in *** addition,the increase in temperature promoted the growth of the *** grains were uniform in size and regular in distribution,with a shrinkage of 2.2%,porosity of 72.5%,bulk density of 1.076 g/cm^(3),and compressive strength of 1.12 *** the sintering temperature was 1450°C,the basic phases of the ceramic after the addition of kaolin were Al_(2)O_(3),MgAl_(2)O_(4),NaAl_(11)O_(17),and SiO_(2).With the increase of kaolin,the diffraction peaks of NaAl_(11)O_(17)and SiO_(2)decreased until they disappeared,while the diffraction peaks of Al_(2)O_(3)increased *** kaolin was added at 30 wt.%,the ceramics obtained had shrinkage of 18%,a porosity of 47.26%,a bulk density of 1.965 g/cm^(3),and compressive strength of 31.9 *** existed inside the ceramics without the addition of kaolin,while the addition of kaolin significantly changed this *** is shown that SAD can obtain porous ceramics with good properties at a sintering temperature of 1450°C and a kaolin addition of 30 wt.%.

关键词： Secondary aluminum dross porous ceramics microstrure phase mechanical properties

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Multi-objective capacity configuration optimization of a grid-connected SOFC/LB microgrid

Multi-objective capacity configuration optimization of a gri...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Beibei Wang Zishan Yin Jingxuan Peng Shiwei Zeng Zhonghua Deng Xi Li School of Artificial Intelligence and Automation Key Laboratory of Imaging Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Wuhan China Wuhan Huamao Automation Co. Ltd Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

The solid Oxide Fuel Cell (SOFC) technique with electric to gas technique is an investment-worthy way to enhance the consumption of renewable energy in microgrids. Moreover, SOFC’s high fuel adaptability and efficient cogeneration are ideal for stationary power generation. However, due to SOFC’s slow load response and high cost, the capacity configuration designation of microgrid with SOFC system is significant. To enhance energy utilization and reduce cost, in this paper, a microgrid connected with an upper grid, containing SOFC, wind turbine (WT), photovoltaics (PV), electrolyzer, a hydrogen storage system (HSS), and lithium battery (LB), is built. Considering the dynamic characteristics of SOFC’s load response, transient and steady-stage’s energy management strategies assisted by LB are proposed. Capacity configuration parameters of microgrid’s components are selected as decision variables and minimal life cycle cost (LCC) and minimal curtailment rate of wind and PV are selected as objective functions. Using proposed strategies to process microgrids, the NSGA-II algorithm is used to optimize. An actual case is studied and appropriate capacity configuration is solved, with 2112 120W PVs,315 500W WTs, 5 10kW • h LBs,5 SOFCs,98.73kW electrolyzer and 38.94kg *** reaches $4.268 × 10 5 and wind &PV’s curtailment rate reaches 5.71%. The result’s rationality is proved by analyzing the detailed cost and operation.

关键词： Photovoltaic systems Renewable energy sources Costs Power demand Fuel cells Microgrids Solids

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CondNet: Conditional classifier for scene segmentation

arXiv

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arXiv 2021年

作者： Yu, Changqian Shao, Yuanjie Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

—The fully convolutional network (FCN) has achieved tremendous success in dense visual recognition tasks, such as scene segmentation. The last layer of FCN is typically a global classifier (1×1 convolution) to recognize each pixel to a semantic label. We empirically show that this global classifier, ignoring the intra-class distinction, may lead to sub-optimal results. In this work, we present a conditional classifier to replace the traditional global classifier, where the kernels of the classifier are generated dynamically conditioned on the input. The main advantages of the new classifier consist of: (i) it attends on the intra-class distinction, leading to stronger dense recognition capability;(ii) the conditional classifier is simple and flexible to be integrated into almost arbitrary FCN architectures to improve the prediction. Extensive experiments demonstrate that the proposed classifier performs favourably against the traditional classifier on the FCN architecture. The framework equipped with the conditional classifier (called CondNet) achieves new state-of-the-art performances on two datasets. The code and models are available at https://***/CondNet. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Generating Natural Language adversarial examples through an improved beam search algorithm

arXiv

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arXiv 2021年

作者： Zhao, Tengfei Ge, Zhaocheng Hu, Hanping Shi, Dingmeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education

The research of adversarial attacks in the text domain attracts many interests in the last few years, and many methods with a high attack success rate have been proposed. However, these attack methods are inefficient as they require lots of queries for the victim model when crafting text adversarial examples. In this paper, a novel attack model is proposed, its attack success rate surpasses the benchmark attack methods, but more importantly, its attack efficiency is much higher than the benchmark attack methods. The novel method is empirically evaluated by attacking WordCNN, LSTM, BiLSTM, and BERT on four benchmark datasets. For instance, it achieves a 100% attack success rate higher than the state-of-the-art method when attacking BERT and BiLSTM on IMDB, but the number of queries for the victim models only is 1/4 and 1/6.5 of the state-of-the-art method, respectively. Also, further experiments show the novel method has a good transferability on the generated adversarial examples. © 2021, CC BY.

关键词： Long short-term memory

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Predictor-Based Active Anti-Disturbance control for Multi-Rate control Systems with Delayed Sampled-Data

Predictor-Based Active Anti-Disturbance Control for Multi-Ra...

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第40届中国控制会议

作者： Jiankun Sun Zhigang Zeng the School of Artificial Intelligence and Automation Huazhong University of Science and Technology the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China

In this paper, we consider the problem of sampleddata active anti-disturbance control design for multi-rate control system subject to delayed sampled-data output. The plant considered in this paper is equipped with a slow-rate sensor and a fastrate actuator. In the presence of non-vanishing disturbance, a new output predictor-based observer is first proposed by only using the delayed sampled-data output, so as to effectively estimate system state and disturbance in the inter-sample time interval.A new sampled-data controller that updates at a fast-rate is then designed with the help of active anti-disturbance *** to prediction and active anti-disturbance techniques, the proposed sampled-data control method can effectively reject the influence of non-vanishing disturbance despite slow-rate sampling and delay of sensor. Finally, the effectiveness of the proposed control method is demonstrated via simulation results of a practical example of the visual servoing control for an inertially stabilized platform.

关键词： Sample-data active anti-disturbance control output delay multi-rate control system

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An Active Landing Recovery Method for Quadrotor UAV: Localization, Tracking and Buffering Landing

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IFAC-PapersOnLine 2023年第2期56卷 3366-3372页

作者： Yongkang Xu Zhihua Chen Shoukun Wang Junzheng Wang National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing CO 100081 P.R.China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology School of Information Engineering Nanchang Hangkong University Nanchang CO 330063 P.R. China

This paper proposes a principle of fully autonomous ground mobile landing recovery of Unmanned Aerial Vehicles (UAV) for the problems of relatively fixed landing point, passive recovery, poor flexibility, and environmental adaptability, which mainly includes localization, landing point tracking, and buffering landing for quadrotor UAV. Firstly, aiming at the problem that it is difficult to accurately obtain the position of a UAV in dynamic mobile landing recovery, a target location method based on Asynchronous Multisensor Information Fusion(AMIF) and servo turntable focus tracking is proposed. Secondly, to achieve fast and high-precision tracking of UAVs, a tracking control strategy of an independently driven landing recovery system and a Stewart six-degree of freedom platform is proposed. Then, to solve the problems of large impact force and center of gravity instability in the landing process of UAV, a stationarity control algorithm based on model prediction and a compliance control algorithm based on adaptive variable impedance are designed to achieve active compliance control while adjusting the position and attitude of the receiving surface in real-time. Finally, a quadrotor unmanned landing and recovery experimental platform is built to verify the feasibility of the ground mobile landing and recovery strategy proposed in this paper and the effectiveness of the control algorithm.

关键词： Quadrotor UAV Mobile Autonomous recovery Target localization Falling point tracking Buffering landing

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Nonlinear Active Disturbance Rejection control for Vehicle Active Suspension System

Nonlinear Active Disturbance Rejection Control for Vehicle A...

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Electronic Information Engineering and Computer Science (EIECS), 2021 International Conference on

作者： Xianglian Dai Chunzhe Zhao Rong Xu School of Electronics and Information Engineering Chongqing Three Gorges University Wanzhou China Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Key Laboratory of Intelligent Information Processing and Control of Chongqing Municipal Institutions of Higher Education Chongqing Three Gorges University Wanzhou China

Nonlinear active disturbance rejection control (ADRC) is designed for the suspension system of the quarter vehicle model with the two-degree freedom. It is compared with other active suspension systems based on PID and linear ADRC scheme. The variance of the errors reveals that the nonlinear ADRC suspension system promotes the vehicle acceleration, the suspension dynamic disturbance, and wheel dynamic load.

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