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第41届中国控制会议

作者： Han Sun Yongqiang Bai Wenbo Zhang State Key Lab of Intelligent Control and Decision of Complex Systems and School of Automation Beijing Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In recent years,the introduction of Siamese network has brought new vitality to the object tracking ***,high-performance Siamese trackers cannot run at a real-time speed on mobile devices due to their complex and huge *** distillation is a common and effective model compression method,but it is difficult to be applied to the challenging task like object *** find out the fundamental cause is that the imbalance between the foreground and background in the object tracking task,which aggravates the problem of insufficient feature extraction ability of small ***,we propose the attention mask distillation(AMD) to help the student tracker focus on the foreground area faster and more *** attention mask can be easily obtained from the feature maps and brings fine-granularity to the traditional binary *** experimental results on OTB100 and VOT2018 show that our method enables the student tracker perform as well as the teacher *** the same time,it's able to run on the CPU at a hyper-real-time of 66 fps and achieves nearly 9 times model compression *** low computational and storage costs make it possible to deploy high-performance trackers on resource-constrained platforms.

关键词： Object Tracking Siamese Network Knowledge Distillation Attention Mask

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Learning to Solve Multi-AGV Scheduling Problem with Pod Repositioning Optimization in RMFS 25

Learning to Solve Multi-AGV Scheduling Problem with Pod Repo...

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25th IEEE International Conference on Industrial technology, ICIT 2024

作者： Zhou, Xuan Shi, Xiang Chu, Wenqing Jiang, Jingchen Zhang, Lele Deng, Fang School Of Automation Beijing Institute Of Technology State Key Lab Of Autonomous Intelligent Unmanned Systems Beijing100081 China Beijing Institute Of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798350340266

This paper studies a novel non-deterministic polynomial-hard (NP-hard) warehouse optimization problem, the multi-automated guided vehicle (multi-AGV) scheduling problem with pod repositioning optimization (MAS-PR), in a robotic mobile fulfillment system (RMFS). A major challenge in MAS-PR is that the storage assignment of pods and the task allocation decision of AGVs are closely coupled. To address this problem, an end-to-end Problem-Specific Mask-based Deep Reinforcement Learning (PSMDRL) method is proposed in this paper. In PSMDRL, we transform the MAS-PR into a Markov Decision Process (MDP) model, and then use an attention-based network model to learn the efficient allocation and retrieval policy. A mask strategy with problem-specific knowledge and a model structure with decoder embedding are designed to further improve the efficiency and effectiveness. Experimental results demonstrate that the proposed PSMDRL is more effective and efficient than the representative algorithms in solving the MAS-PR problem. © 2024 IEEE.

关键词： Reinforcement learning

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Parameter Estimation and Tracking Control of MIMO Linear systems Without Prior Knowledge of Control Signs and Parameter Bounds

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IEEE Transactions on Automatic Control 2024年第6期70卷 3695-3710页

作者： Xu, Yuchun Zhang, Yanjun Zhang, Ji-Feng Chinese Academy of Sciences Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Beijing100190 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology State Key Lab of Automation Intelligent Unmanned Systems Beijing100081 China University of Chinese Academy of Sciences School of Mathematics Sciences Beijing100149 China Zhongyuan University of Technology School of Automation and Electrical Engineering Zhengzhou450007 China Chinese Academy of Sciences Academy of Mathematics and Systems Science Beijing100190 China

Dealing with the uncertain high-frequency gain matrix, denoted as Kp, is a fundamental problem in multivariable adaptive control systems. In this paper, we propose a new solution for parameter estimation and adaptive control for a general class of multi-input multi-output discrete-time linear time-invariant systems. The proposed scheme does not require any prior knowledge of the sign or bound information of Kp, and thus, significantly relaxes the design conditions in traditional multivariable adaptive control systems. Compared with the commonly used Nussbaum gain or multi-model techniques for addressing the unknown signs of Kp, the proposed scheme does not rely on any additional design conditions or any switching mechanism, while still ensuring closed-loop stability and asymptotic output tracking. Specifically, an output feedback adaptive control law is developed based on a matrix decomposition technique, which leads to derivation of a modified estimation error model. Subsequently, a gradient-based parameter update law is formulated only relying on the non-zero condition of the leading principle minors of Kp. Through designing gain functions and stable filters, the controller is always non-singular and does not involve any causal contradiction problem. Simulation study showcases the design process and demonstrates the effectiveness of the proposed scheme. © 1963-2012 IEEE.

关键词： MIMO systems

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Instruction Pre-Training: Language Models are Supervised Multitask Learners

Instruction Pre-Training: Language Models are Supervised Mul...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Cheng, Daixuan Gu, Yuxian Huang, Shaohan Bi, Junyu Huang, Minlie Wei, Furu Microsoft Research United States 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 China

ISBN: (纸本)9798891761643

Unsupervised multitask pre-training has been the critical method behind the recent success of language models (LMs). However, supervised multitask learning still holds significant promise, as scaling it in the post-training stage trends towards better generalization. In this paper, we explore supervised multitask pretraining by proposing Instruction Pre-Training, a framework that scalab.y augments massive raw corpora with instruction-response pairs to pre-train LMs. The instruction-response pairs are generated by an efficient instruction synthesizer built on open-source models. In our experiments, we synthesize 200M instruction-response pairs covering 40+ task categories to verify the effectiveness of Instruction Pre-Training. In pre-training from scratch, Instruction Pre-Training not only consistently enhances pre-trained base models but also benefits more from further instruction tuning. In continual pre-training, Instruction Pre-Training enables Llama3-8B to be comparable to or even outperform Llama3-70B. Our model, code, and data are availab.e at https://***/microsoft/LMOps. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Recent Developments in Metallic Degradable Micromotors for Biomedical and Environmental Remediation Applications

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Nano-Micro Letters 2024年第3期16卷 1-35页

作者： Sourav Dutta Seungmin Noh Roger Sanchis Gual Xiangzhong Chen Salvador Pané Bradley J.Nelson Hongsoo Choi Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988Republic of Korea DGIST‑ETH Microrobotics Research Center DGISTDaegu 42988Republic of Korea Multi‑Scale Robotics Lab Institute of Robotics and Intelligent SystemsETH Zurich8092 ZurichSwitzerland Institute of Optoelectronics State Key Laboratory of Photovoltaic Science and TechnologyShanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionFudan UniversityShanghai 200433People’s Republic of China

Synthetic micromotor has gained substantial attention in biomedicine and environmental ***-based degradable micromotor composed of magnesium(Mg),zinc(Zn),and iron(Fe)have promise due to their nontoxic fuel-free propulsion,favorable biocompatibility,and safe excretion of degradation products Recent advances in degradable metallic micromotor have shown their fast movement in complex biological media,efficient cargo delivery and favorable biocompatibility.A noteworthy number of degradable metal-based micromotors employ bubble propulsion,utilizing water as fuel to generate hydrogen *** novel feature has projected degradable metallic micromotors for active in vivo drug delivery *** addition,understanding the degradation mechanism of these micromotors is also a key parameter for their design and *** propulsion efficiency and life span govern the overall performance of a degradable metallic *** we review the design and recent advancements of metallic degradable ***,we describe the controlled degradation,efficient in vivo drug delivery,and built-in acid neutralization capabilities of degradable micromotors with versatile biomedical ***,we discuss micromotors’efficacy in detecting and destroying environmental ***,we address the limitations and future research directions of degradable metallic micromotors.

关键词： Magnesium Zinc Iron Biodegradable microrobot Biomedical Environmental

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Flight Simulator Column Force Modeling by System Identification 23

Flight Simulator Column Force Modeling by System Identificat...

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15th International Conference on Computer Modeling and Simulation, ICCMS 2023

作者： Cai, Xiangqun Lei, Xiaoyong Dai, Shuling Li, Weiqi State Key Lab. of Virtual Reality Technology and Systems Beihang University China School of Automation Science and Electrical Engineering Beihang University China

ISBN: (纸本)9798400707919

In this work, a modeling method of aircraft control column force based on system identification is proposed. Using the data of "lever force displacement"and "lever release"tests, the column force model of the longitudinal channel of the control system is established, and least square method is used to identify the model parameters. The acquired model is used for the simulation of the irreversible hydraulic control system, and the simulation results are compared with test results. It is indicated that the simulation accuracy meets the requirements of CCAR 60 for the column force model of the simulator control system. The proposed model has a simple structure and high computational efficiency. The identification method is independent of the original design parameters of the control system and has good robustness. © 2023 ACM.

关键词： Flight simulators

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Learning to Grasp through World Models with Backward Prediction

Learning to Grasp through World Models with Backward Predict...

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第43届中国控制会议

作者： Shuze Wang Yetian Yuan Yunpeng Mei Jian Sun Gang Wang State Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the era of the fourth industrial revolution, the paradigm of intelligent manufacturing has ascended as a pivotal driver for future advancements. The combination of intelligent manufacturing with reinforcement learning offers significant benefits and opportunities. However, applying reinforcement learning in practical settings faces challenges due to sampling ***, model-based reinforcement learning algorithms have demonstrated higher sample efficiency. In this research, we introduce an enhanced version of the Dreamer algorithm and devise a system dedicated to mastering the tasks of picking and placing through the limited data collected. The improved algorithm addresses the issue of low sample efficiency and proves to be exceptionally effective in pixel-based tasks associated with high-dimensional state spaces. To corroborate the efficacy of the proposed algorithm, we evaluate the algorithm on a simulation environment of a production line for robotic arm operations developed in Coppeliasim. The merits of the augmented algorithm are further corroborated through its performance in complex DeepMind control tasks.

关键词： World Model Reinforcement Learning Robot Arm

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Detection of Stealthy False Data Injection Attacks Against Cyber-Physical systems:A Stochastic Coding Scheme

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Journal of systems Science & Complexity 2022年第5期35卷 1668-1684页

作者： GUO Haibin PANG Zhonghua SUN Jian LI Jun State Key Lab of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongging Innovation Center Chongqing 401120China Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China

This paper,from the view of a defender,addresses the security problem of cyber-physical systems(CPSs)subject to stealthy false data injection(FDI)attacks that cannot be detected by a residual-based anomaly detector without other defensive *** detect such a class of FDI attacks,a stochastic coding scheme,which codes the sensor measurement with a Gaussian stochastic signal at the sensor side,is proposed to assist an anomaly detector to expose the FDI *** order to ensure the system performance in the normal operational context,a decoder is adopted to decode the coded sensor measurement when received at the controller *** this detection scheme,the residual under the attack can be significantly different from that in the normal situation,and thus trigger an *** design condition of the coding signal covariance is derived to meet the constraints of false alarm rate and attack detection *** minimize the trace of the coding signal covariance,the design problem of the coding signal is converted into a constraint non-convex optimization problem,and an estimation-optimization iteration algorithm is presented to obtain a numerical solution of the coding signal covariance.A numerical example is given to verify the effectiveness of the proposed scheme.

关键词： Attack detection cyber-physical systems(CPSs) stealthy FDI attacks stochastic coding

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GazeSwipe: Enhancing Mobile Touchscreen Reachability through Seamless Gaze and Finger-Swipe Integration 25

GazeSwipe: Enhancing Mobile Touchscreen Reachability through...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing systems

作者： Zhuojiang Cai Jingkai Hong Zhimin Wang Feng Lu State Key Lab. of VR Technology and Systems Beihang University Beijing China

ISBN: (纸本)9798400713941

Smartphones with large screens provide users with increased display and interaction space but pose challenges in reaching certain areas with the thumb when using the device with one hand. To address this, we introduce GazeSwipe, a multimodal interaction technique that combines eye gaze with finger-swipe gestures, enabling intuitive and low-friction reach on mobile touchscreens. Specifically, we design a gaze estimation method that eliminates the need for explicit gaze calibration. Our approach also avoids the use of additional eye-tracking hardware by leveraging the smartphone's built-in front-facing camera. Considering the potential decrease in gaze accuracy without dedicated eye trackers, we use finger-swipe gestures to compensate for any inaccuracies in gaze estimation. Additionally, we introduce a user-unaware auto-calibration method that improves gaze accuracy during interaction. Through extensive experiments on smartphones and tablets, we compare our technique with various methods for touchscreen reachability and evaluate the performance of our auto-calibration strategy. The results demonstrate that our method achieves high success rates and is preferred by users. The findings also validate the effectiveness of the auto-calibration strategy. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Interaction Technique

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GazeSwipe: Enhancing Mobile Touchscreen Reachability through Seamless Gaze and Finger-Swipe Integration

arXiv

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arXiv 2025年

作者： Cai, Zhuojiang Hong, Jingkai Wang, Zhimin Lu, Feng State Key Lab. of VR Technology and Systems Beihang University Beijing China

Smartphones with large screens provide users with increased display and interaction space but pose challenges in reaching certain areas with the thumb when using the device with one hand. To address this, we introduce GazeSwipe, a multimodal interaction technique that combines eye gaze with finger-swipe gestures, enabling intuitive and low-friction reach on mobile touchscreens. Specifically, we design a gaze estimation method that eliminates the need for explicit gaze calibration. Our approach also avoids the use of additional eye-tracking hardware by leveraging the smartphone’s built-in front-facing camera. Considering the potential decrease in gaze accuracy without dedicated eye trackers, we use finger-swipe gestures to compensate for any inaccuracies in gaze estimation. Additionally, we introduce a user-unaware auto-calibration method that improves gaze accuracy during interaction. Through extensive experiments on smartphones and tablets, we compare our technique with various methods for touchscreen reachability and evaluate the performance of our auto-calibration strategy. The results demonstrate that our method achieves high success rates and is preferred by users. The findings also validate the effectiveness of the auto-calibration strategy. © 2025, CC BY.

关键词： Smartphones

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