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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhanping Zhong Zhuoning Dong Xiaoming Duan Jianping He The School of Automation Science and Electrical Engineering Beihang University Beijing China The Department of Automation Ministry of Education of China Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We investigate a pursuit-evasion game taking place in an unbounded three-dimensional space, where a flexible pursuer with hybrid dynamics collaborates with a fast pursuer and aims to capture a flexible evader within a finite time. The key feature of this problem lies in the hybrid dynamics of the flexible pursuer, which can change its dynamics once during the game and switch to a fast pursuer with increased speed but lower maneuverability. To address this challenge, we devise a hybrid strategy based on the soft actor-critic framework, tailored specifically for the flexible pursuer, which encompasses both maneuvering and switch tactics. We introduce a switch factor to the input of the actor network and incorporate switch actions to further expand the action space. These additions enable the flexible pursuer to execute maneuvering actions and determine a moment to switch to a fast pursuer. The reward function is designed to account for related angle, altitude, speed, and sparse reward. Through extensive ablation experiments conducted in a simulated environment, we demonstrate the efficacy of our algorithm in facilitating the learning of hybrid strategies for the flexible pursuer, resulting in significantly improved capture rates compared to alternative methods.

关键词： Solid modeling Three-dimensional displays Heuristic algorithms Collaboration Switches Games Deep reinforcement learning Vectors Intelligent robots

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Structured Sparse Coding With the Group Log-regularizer for key Frame Extraction

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1818-1830页

作者： Zhenni Li Yujie Li Benying Tan Shuxue Ding Shengli Xie the School of Automation Guangdong University of TechnologyGuangzhou 510006 the Guangdong-Hong Kong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangdong University of Technology(GDUT)Guangzhou 510006China the School of Artificial Intelligence Guilin University of Electronic TechnologyGuilin 541004China the National Institute of Advanced Industrial Science and Technology TsukubaIbaraki 305-8560Japan IEEE the Key Laboratory of Intelligent Information Processing and System Integration of Io T(GDUT) Ministry of Education Guangdong Key Laboratory of IoT Information Technology(GDUT) Guangzhou 510006China

key frame extraction based on sparse coding can reduce the redundancy of continuous frames and concisely express the entire ***,how to develop a key frame extraction algorithm that can automatically extract a few frames with a low reconstruction error remains a *** this paper,we propose a novel model of structured sparse-codingbased key frame extraction,wherein a nonconvex group log-regularizer is used with strong sparsity and a low reconstruction *** automatically extract key frames,a decomposition scheme is designed to separate the sparse coefficient matrix by *** rows enforced by the nonconvex group log-regularizer become zero or nonzero,leading to the learning of the structured sparse coefficient *** solve the nonconvex problems due to the log-regularizer,the difference of convex algorithm(DCA)is employed to decompose the log-regularizer into the difference of two convex functions related to the l1 norm,which can be directly obtained through the proximal ***,an efficient structured sparse coding algorithm with the group log-regularizer for key frame extraction is developed,which can automatically extract a few frames directly from the video to represent the entire video with a low reconstruction *** results demonstrate that the proposed algorithm can extract more accurate key frames from most Sum Me videos compared to the stateof-the-art ***,the proposed algorithm can obtain a higher compression with a nearly 18% increase compared to sparse modeling representation selection(SMRS)and an 8% increase compared to SC-det on the VSUMM dataset.

关键词： Difference of convex algorithm(DCA) group logregularizer key frame extraction structured sparse coding

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Few-Reference Image Quality Assessment with Multiple information Measurement Fusion 9th

Few-Reference Image Quality Assessment with Multiple Inform...

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9th International Forum on Digital Multimedia Communication, IFTC 2022

作者： Shi, Shuang Wang, Simeng Liu, Yuchen Zhou, Chengxu Gu, Ke Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China School of Electronic and Information Engineering Liaoning University of Technology Liaoning Jinzhou China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China

ISBN: (纸本)9789819908554

In the era of media information explosion, there is an urgent need for a fast and reliable image quality assessment (IQA) model to improve the actual application effect of images. To this end, we propose the multiple information measurement fusion metric (MMFM), which innovatively combines two types of information measures (IMs), i.e., local IM and global IM, using only a small number of references for IQA. First, inspired by the free energy theory, we combine 2-dimensional autoregressive model with sparse random sampling method as an inference engine on an input image to generate its associated predicted image. Second, by the inspiration of pixel-wise measurement, we obtain the local IM by calculating the information entropy of the residual error between the input image and its corresponding predicted one. Third, motivated by the histogram-based measurement, we acquire the global IM by computing the two kinds of divergences between the input image and its predicted one. Fourth, we systematically fuse three components, independently including one distance of local IM between the reference and corrupted images and two distances of global IMs between the reference and corrupted images, based on a linear function to derive the final IQA result. The results of experiment on the most popular LIVE database show that our designed algorithm with only one number used as few reference has achieved well performance as compared with several mainstream IQA models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Data-Driven Bayesian Nonparametric Wasserstein Distributionally Robust Optimization

arXiv

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arXiv 2023年

作者： Ning, Chao Ma, Xutao Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

In this work, we develop a novel data-driven Bayesian nonparametric Wasserstein distributionally robust optimization (BNWDRO) framework for decision-making under uncertainty. The proposed framework unifies a Bayesian nonparametric method and the Wasserstein metric to decipher the global-local features of uncertainty data and encode these features into a novel data-driven ambiguity set. By establishing the theoretical connection between this data-driven ambiguity set and the conventional Wasserstein ambiguity set, we prove that the proposed framework enjoys the finite sample guarantee and asymptotic consistency. To efficiently solve the resulting distributionally robust optimization problem under the BNWDRO framework, we derive for this optimization problem an equivalent reformulation, which is kept tractable for many practical scenarios. Numerical experiments on a unit commitment problem verify the effectiveness of the proposed BNWDRO framework compared with existing methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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Terahertz Refractive Index Sensor Based on Tunable Graphene Metamaterial Absorber

Terahertz Refractive Index Sensor Based on Tunable Graphene ...

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Sensor Technology and control (ISSTC), International Symposium on

作者： Maixia Fu Tiantian Zhang Zhonghao Liu Mengyi Liu Dongdong Wang Key Laboratory of Grain Information Processing and Control Ministry of Education (Henan University of Technology) Zhengzhou China College of Information Science and Engineering Henan University of Technology Zhengzhou China

ISBN: (数字)9798331541637

ISBN: (纸本)9798331541644

A terahertz refractive index sensor constructed with graphene metamaterial absorber has been proposed. The sensor features a patterned graphene structure, consisting of an independent circular ring and a special structure formed by intersecting cross and square patterns. Under normal incidence of TM and TE polarized light, the sensor exhibits a low-frequency peak at 1.55 THz with maximum absorption rates of $\mathbf{9 9. 4 5 \%}$ and a high-frequency peak at 3.83 THz with maximum absorption rates of $\mathbf{9 9. 5 0 \%}$. The quality factors (Q factor) of the two peaks are 31 and 65, respectively. Unlike traditional metal sensors, the absorption peaks of this sensor can achieve dynamic tunability through adjusting the graphene’s Fermi level. By varying the analyte’s thickness and refractive index, the maximum sensitivity of the two absorption peaks can reach $495 \mathrm{GHz} / \mathrm{RIU}$ and 895 $\mathrm{GHz} /$ RIU. The corresponding figures of merit (FOM) are 9.9 and 15.2, respectively. The sensor proposed here are applied to detect hemoglobin biomolecule content and has shown excellent sensing performance in our simulations. Therefore, the present work has broad potential for applications in biomedical and medical diagnostic fields.

关键词： Q-factor Structural rings Sensitivity Absorption Fermi level Graphene Refractive index Metamaterials Surface plasmon resonance Biomedical imaging

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Cross-Modality Guided Multi-Scale Feature Representation Based Image Compression for Industrial Scene Understanding

Cross-Modality Guided Multi-Scale Feature Representation Bas...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Jingzheng Tu Yan Yan Ying Lu Cailian Chen Shiru Zhou China Academy of Aerospace Science and Innovation Beijing China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Industrial surveillance videos capture subsequent video frames and deliver them to processing servers for video analytics. In such a case, image compression is a promising technology in industrial scene understanding due to its reduced transmission burden. Existing works focus on establishing macroscopic visual feature maps that contain compact image information. In this article, a cross-modality guided multi-scale feature representation based image compression method is proposed for understanding industrial scenes. Firstly, an image compressing framework with multi-grained representation (MGRIC) is proposed for industrial scene understanding, which builds image patch, structure, semantic, and signal levels feature maps. Secondly, an encoder-decoder architecture is designed for image compression with diverse granularities. Thirdly, an interaction policy between different levels is developed to ensure the subsequent level's decoding. Experiments on the CUB-200-2011 dataset demonstrate that the proposed MGRIC method achieves competitive performance, which verifies its effectiveness.

关键词： Image coding Visual analytics Surveillance Semantics Video compression Decoding Servers Informatics Image reconstruction Videos

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River Turbidity Monitoring Based on Semi-supervised Transfer Learning 9th

River Turbidity Monitoring Based on Semi-supervised Transfe...

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9th International Forum on Digital Multimedia Communication, IFTC 2022

作者： Xie, Shuangyi Liao, Xin Bai, Ruxue Zhou, Chengxu Gu, Ke Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China School of Electronic and Information Engineering Liaoning University of Technology Liaoning China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China

ISBN: (纸本)9789819908554

River turbidity is an important index to evaluate the quality of water environment, which is of great significance to environmental monitoring. Most of the existing monitoring methods rely on turbidity labels measured by river water quality monitoring stations. However, due to the limitation of spatial distribution of water quality monitoring stations, those turbidity data outside the monitoring range are difficult to obtain and the correlation of turbidity data between monitoring stations is poor. Using such data directly might weaken the generalization ability that the model has. In this paper, we propose a new river turbidity monitoring model based on semi-supervised transfer learning (RTMM-SSTL) to solve these problems. First, in the pre-training stage, we innovatively propose a semi-supervised training method combined with big data with pseudo labels for river turbidity monitoring to solve the problem of weakened model generalization ability. Then, the model is fine-tuned using GEE hyper spectral data with ground truth to further improve the monitoring capability of the model. Experiments conducted on the river turbidity monitoring task demonstrate that the proposed model is superior to the advanced learning models, and further proves that our semi-supervised transfer learning method performs better than the state-of-the-art supervision models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rivers

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Comprehensive study of the ultrafast photoexcited carrier dynamics in Sb_(2)Te_(3)–GeTe superlattices

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Chinese Physics B 2024年第7期33卷 381-387页

作者：叶之江金钻明蒋叶昕卢琦贾梦辉钱冬黄夏敏李舟彭滟朱亦鸣 Terahertz Technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation CenterShanghai Key Laboratory of Modern Optical SystemUniversity of Shanghai for Science and TechnologyShanghai 200093China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China Key Laboratory of Artificial Structures and Quantum Control(Ministry of Education) Shenyang National Laboratory for Materials ScienceSchool of Physics and AstronomyShanghai Jiao Tong UniversityShanghai 200240China Tsung-Dao Lee Institute Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Precision Spectroscopy East China Normal UniversityShanghai 200062China GBA Branch of Aerospace Information Research Institute Chinese Academy of SciencesGuangzhou 510700China Guangdong Provincial Key Laboratory of Terahertz Quantum Electromagnetics Guangzhou 510700China University of Chinese Academy of Sciences Beijing 100039China

Chalcogenide superlattices Sb_(2)Te_(3)-GeTe is a candidate for interfacial phase-change memory(iPCM) data storage *** employing terahertz emission spectroscopy and the transient reflectance spectroscopy together,we investigate the ultrafast photoexcited carrier dynamics and current transients in Sb_(2)Te_(3)-GeTe *** orientation and excitation polarization dependences of the THz emission confirm that ultrafast thermo-electric,shift and injection currents contribute to the THz generation in Sb_(2)Te_(3)-GeTe *** decreasing the thickness and increasing the number of GeTe and Sb_(2)Te_(3) layer,the interlayer coupling can be enhanced,which significantly reduces the contribution from circular photo-galvanic effect(CPGE).A photo-induced bleaching in the transient reflectance spectroscopy probed in the range of~1100 nm to~1400 nm further demonstrates a gapped state resulting from the interlayer *** demonstrates play an important role in the development of iPCM-based high-speed optoelectronic devices.

关键词： Sb_(2)Te_(3)/GeTe superlattices ultrafast carrier dynamics interfacial phase change memory THz emission spectroscopy transient reflectance spectroscopy

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Sliding Mode-based Two-Dimensional Iterative Learning control for systems with Uncertainties and External Disturbances

Sliding Mode-based Two-Dimensional Iterative Learning Contro...

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International Conference on control and Automation (ICCA)

作者： Y. Yaru L. Dewei M. Aoyun Furong Gao Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai Department of Chemical and Biological Engineering Hong Kong University of Science and Technology HongKong

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper proposes a sliding mode-based two-dimensional (2D) iterative learning control (ILC) strategy for discrete- time batch process systems challenged by uncertainties and external disturbances. Considering the repetitive nature of batch process systems, the ILC method shows significant advantages. Given the presence of non-repetitive uncertainties and external disturbances in practical systems, this paper integrates the sliding mode control (SMC) scheme into the ILC design framework to ensure system robustness. A novel aspect of this study is the development of an augmented 2D model that captures the dynamic evolution in both batch and sampling time directions. Based on this 2D model, a corresponding 2D sliding mode surface and a 2D iterative learning sliding mode controller are designed, preserving the learning capabilities of ILC and the robustness of SMC against uncertainties and external disturbances. The method proposed in this paper enables the controlled system to maintain a high tracking capability in the face of non-repetitive uncertainties and external disturbances. Particularly, the stability conditions derived from this 2D model provide a broad feasible solution space, which improves the applicability. Furthermore, the correctness of the proposed method is proven and its effectiveness is validated through a simulation example.

关键词： Uncertainty system dynamics Two-dimensional displays Simulation Batch production systems Robustness Stability analysis

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ColorDynamic: Generalizable, Scalable, Real-time, End-to-end Local Planner for Unstructured and Dynamic Environments

arXiv

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arXiv 2025年

作者： Xin, Jinghao Liang, Zhichao Zhang, Zihuan Wang, Peng Li, Ning Department of Automation Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Deep Reinforcement Learning (DRL) has demonstrated potential in addressing robotic local planning problems, yet its efficacy remains constrained in highly unstructured and dynamic environments. To address these challenges, this study proposes the ColorDynamic framework. First, an end-to-end DRL formulation is established, which maps raw sensor data directly to control commands, thereby ensuring compatibility with unstructured environments. Under this formulation, a novel network, Transqer, is introduced. The Transqer enables online DRL learning from temporal transitions, substantially enhancing decision-making in dynamic scenarios. To facilitate scalable training of Transqer with diverse data, an efficient simulation platform E-Sparrow, along with a data augmentation technique leveraging symmetric invariance, are developed. Comparative evaluations against state-of-the-art methods, alongside assessments of generalizability, scalability, and real-time performance, were conducted to validate the effectiveness of ColorDynamic. Results indicate that our approach achieves a success rate exceeding 90% while exhibiting real-time capacity (1.2–1.3 ms per planning). Additionally, ablation studies were performed to corroborate the contributions of individual components. Building on this, the OkayPlan-ColorDynamic (OPCD) navigation system is presented, with simulated and real-world experiments demonstrating its superiority and applicability in complex scenarios. The codebase and experimental demonstrations have been open-sourced on our website1 to facilitate reproducibility and further research. Copyright © 2025, The Authors. All rights reserved.

关键词： Decision making

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