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arXiv 2019年

作者： Zheng, Yunfei Chen, Badong Wang, Shiyuan Wang, Weiqun Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an710049 China College of Electronic and Information Engineering Southwest University Chongqing400715 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

As an effective and efficient discriminative learning method, Broad Learning System (BLS) has received increasing attention due to its outstanding performance in various regression and classification problems. However, the standard BLS is derived under the minimum mean square error (MMSE) criterion, which is, of course, not always a good choice due to its sensitivity to outliers. To enhance the robustness of BLS, we propose in this work to adopt the maximum correntropy criterion (MCC) to train the output weights, obtaining a correntropy based broad learning system (C-BLS). Thanks to the inherent superiorities of MCC, the proposed C-BLS is expected to achieve excellent robustness to outliers while maintaining the original performance of the standard BLS in Gaussian or noise-free environment. In addition, three alternative incremental learning algorithms, derived from a weighted regularized least-squares solution rather than pseudoinverse formula, for C-BLS are developed. With the incremental learning algorithms, the system can be updated quickly without the entire retraining process from the beginning, when some new samples arrive or the network deems to be expanded. Experiments on various regression and classification datasets are reported to demonstrate the desirable performance of the new methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Learning algorithms

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Efficient Planar Pose Estimation via UWB Measurements

arXiv

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arXiv 2022年

作者： Jiang, Haodong Wang, Wentao Shen, Yuan Li, Xinghan Ren, Xiaoqiang Mu, Biqiang Wu, Junfeng China School of Data Science The Chinese University of HongKong Shenzhen China College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China School of Mechatronic Engineering and Automation Shanghai University Shanghai China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

state estimation is an essential part of autonomous systems. Integrating the Ultra-Wideband (UWB) technique has been shown to correct the long-term estimation drift and bypass the complexity of loop closure detection. However, few works on robotics treat UWB as a stand-alone state estimation solution. The primary purpose of this work is to investigate planar pose estimation using only UWB range measurements. We prove the excellent property of a two-step scheme, which says we can refine a consistent estimator to be asymptotically efficient by one step of Gauss-Newton iteration. Grounded on this result, we design the GN-ULS estimator, which reduces the computation time significantly compared to previous methods and presents the possibility of using only UWB for real-time state estimation. Copyright © 2022, The Authors. All rights reserved.

关键词： state estimation

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SheetCopilot: bringing software productivity to the next level through large language models 23

SheetCopilot: bringing software productivity to the next lev...

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Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Hongxin Li Jingran Su Yuntao Chen Qing Li Zhaoxiang Zhang School of Artificial Intelligence University of Chinese Academy of Sciences (UCAS) and State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences Center for Artificial Intelligence and Robotics HKISI CAS and The Hong Kong Polytechnic University Center for Artificial Intelligence and Robotics HKISI CAS The Hong Kong Polytechnic University School of Artificial Intelligence University of Chinese Academy of Sciences (UCAS) and State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences and Center for Artificial Intelligence and Robotics HKISI CAS and Shanghai Artificial Intelligence Laboratory

Computer end users have spent billions of hours completing daily tasks like tabular data processing and project timeline scheduling. Most of these tasks are repetitive and error-prone, yet most end users lack the skill to automate these burdensome works. With the advent of large language models (LLMs), directing software with natural language user requests become a reachable goal. In this work, we propose a SheetCopilot agent that takes natural language task and control spreadsheet to fulfill the requirements. We propose a set of atomic actions as an abstraction of spreadsheet software functionalities. We further design a state machine-based task planning framework for LLMs to robustly interact with spreadsheets. We curate a representative dataset containing 221 spreadsheet control tasks and establish a fully automated evaluation pipeline for rigorously benchmarking the ability of LLMs in software control tasks. Our SheetCopilot correctly completes 44.3% of tasks for a single generation, outperforming the strong code generation baseline by a wide margin. Our project page: https://***/.

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MARS: Multi-Agent Deep Reinforcement Learning for Real-Time Workflow Scheduling in Hybrid Clouds with Privacy Protection

MARS: Multi-Agent Deep Reinforcement Learning for Real-Time ...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Long Cheng Haoyang He Yan Gu Qingzhi Liu Zhiming Zhao Fang Fang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing China Information Technology Group Wageningen University and Research Netherlands Research Group of Multi-Scale Networked Systems University of Amsterdam Netherlands

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Scheduling workflows in hybrid cloud environments presents significant challenges due to the inherent complexity of workflows and the dynamic nature of cloud resources. This complexity is further increased when attempting to balance workflow performance with privacy protection. Recent efforts have leveraged deep reinforcement learning (DRL) to address these challenges. However, most of these approaches rely on single-agent models, which can lead to security issues and scalability problems due to their centralized processing. Specifically, the properties of workflows are transferred to the single agent, which risks leaking privacy information. Our paper addresses these issues by introducing MARS, a real-time workflow scheduling method that prioritizes privacy protection in hybrid clouds. MARS leverages multi-agent deep reinforcement learning (MADRL) to optimize the workflow scheduling of cloud virtual machines (VMs). The benefit of our solution is that it relies on the collaborative learning of multi-agents on multiple VMs, which could assign user data to specific cloud servers for privacy protection while sharing training experiences between agents. In our implementation, MARS aims to reduce workflow completion time and operational costs while complying with strict privacy protection guidelines. The experimental results demonstrate that MARS can significantly surpass existing methods, reducing makespan by an average of $53.18 \%$ and costs by $61.98 \%$ compared to basic techniques, and achieving $20.26 \%$ and $25.71 \%$ improvements over the latest advanced methods, respectively.

关键词： Training Cloud computing Privacy Costs Scalability Deep reinforcement learning Dynamic scheduling Real-time systems Complexity theory Protection

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Enhancing Robot Teleoperation in Remote Automation Production through an Event-Triggered control Strategy

Enhancing Robot Teleoperation in Remote Automation Productio...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Mengke Wang Honghao Lv Ruohan Wang Haiteng Wu Lipeng Chen Yi Chen Haihui Yuan Geng Yang State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou Shenhao Technology Hangzhou China Robotics X Tencent Shenzhen China Intelligent Manufacturing Center DongFang Electric Corporation Academy of Science and Technology Co Chengdu China China South Industries Group Corporation Hangzhou Automation Research Insititute Co. Ltd. China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

With the advancement of intelligent manufacturing, an increasing number of industrial production processes are transforming unmanned operations. This trend is particularly evident in factories that involve potential safety hazards, where the demand for unmanned production is becoming increasingly urgent. Teleoperation, as a core technology for achieving unmanned factories, holds tremendous importance in keeping workers safe from danger. However, traditional teleoperation strategies encounter challenges due to mismatches between master and slave workspaces, making it difficult to achieve both high precision and operation across large workspaces simultaneously. To address this issue, this paper proposes an event-triggered control strategy for a teleoperated robot system. By introducing a foot pedal as the event-triggered switch, the enablement and termination of teleoperation are associated with the activation of the pedal. Through resetting the start position, fine-grained teleoperation is achieved throughout the entire workspace of the robot. To demonstrate the advantages of the proposed control strategy, a mimicked wiring operation task scenario is constructed for experimental verification, and the teleoperation tasks are completed successfully and efficiently.

关键词： Wiring Accuracy Service robots Switches Market research Production facilities Main-secondary

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Redistributing controller Orders to Increase Positioning Bandwidth in Nanopositioners

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IFAC-PapersOnLine 2021年第21期54卷 97-102页

作者： Adedayo K. Babarinde Linlin Li Jakub Kuncak LiMin Zhu Sumeet S. Aphale Artificial Intelligence Robotics and Mechatronic Systems Group School of Engineering University of Aberdeen Aberdeen AB24 3UE UK State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China

Integer-order damping and tracking controllers are typically used in tandem to overcome resonance and hysteresis induced positioning errors in piezo-actuated nanopositioners. This paper takes a novel approach of strategically redistributing the controller orders to achieve significant positioning bandwidth improvement, without any significant increase in the design complexity. The Positive Position Feedback (PPF) controller combined with a suitably gained Integral tracking controller is used as a candidate to demonstrate the efficacy of the proposed technique. The resulting fractional-order PPF damping and Integral tracking controllers result in increasing the overall positioning bandwidth of the closed-loop system by 37%; and subsequent improvement in positioning accuracy while tracking high-frequency triangular trajectories.

关键词： Nanopositioners piezoelectric actuator positive position feedback tracking control fractional-order control

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Disturbance Observer-based control of Quadrotors with Motor Response Delay and Throttle Nonlinearity

Disturbance Observer-based Control of Quadrotors with Motor ...

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Yansui Song Xi Liu Bin Xu Yu Zhang Chenguang Yang School of Automation Northwestern Polytechnical University Xi’an China Unit 36485 of the Chinese people’s Liberation Army HaiKou City State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Bristol Robotics Laboratory University of the West of England Bristol UK

The following topics are dealt with: autonomous aerial vehicles; mobile robots; aircraft control; helicopters; control system synthesis; multi-robot systems; path planning; position control; robot vision; collision av... 详细信息

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

关键词： Delays Mathematical model Brushless motors Propellers Attitude control Torque

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Flow Sensing-Based Underwater Target Detection Using Distributed Mobile Sensors

Flow Sensing-Based Underwater Target Detection Using Distrib...

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IEEE Conference on Decision and control

作者： Jun Wang Tongsheng Shen Dexin Zhao Feitian Zhang Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China National Innovation Institute of Defense Technology Beijing China Department of Advanced Manufacturing and Robotics and the State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing China

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper presents a novel bioinspired underwater target detection method with distributed mobile sensors. Inspired by the fish's lateral line system, distributed mobile sensors are proposed to measure their respective local flow pressure and collectively estimate the parameters (e.g., position and dimension) of underwater targets with dynamic sensor trajectory planning. This paper formulates an optimal trajectory planning problem for a group of mobile sensors using information entropy as the cost function, with an aim to maximize the confidence level in the estimated target parameters. This paper in particular investigates the detection of a circular target in a uniform flow. A Bayesian filter is adopted to assimilate the distributed pressure measurements dynamically to estimate the position and radius of given circular targets. To verify the effectiveness of the proposed method, simulation is conducted with both fixed and moving circular targets in uniform flow. Simulation results are presented and analyzed.

关键词： Trajectory planning Simulation Object detection Robot sensing systems Sensor systems Entropy Sensors

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Phase-Amplitude Reduction and Optimal Phase Locking of Collectively Oscillating Networks

arXiv

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arXiv 2023年

作者： Mircheski, Petar Zhu, Jinjie Nakao, Hiroya Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China

We present a phase-amplitude reduction framework for analyzing collective oscillations in networked dynamical systems. The framework, which builds on the phase reduction method, takes into account not only the collective dynamics on the limit cycle but also deviations from it by introducing amplitude variables and using them with the phase variable. The framework allows us to study how networks react to applied inputs or coupling, including their synchronization and phase-locking, while capturing the deviations of the network states from the unperturbed dynamics. Numerical simulations are used to demonstrate the effectiveness of the framework for networks composed of FitzHugh-Nagumo elements. The resulting phase-amplitude equation can be used in deriving optimal periodic waveforms or introducing feedback control for achieving fast phase locking while stabilizing the collective oscillations. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamical systems

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Spatial-nonlocality-induced non-Markovian electromagnetically induced transparency in a single giant atom

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Physical Review A 2022年第4期106卷 043710-043710页

作者： Y. T. Zhu S. Xue R. B. Wu W. L. Li Z. H. Peng M. Jiang Department of Automation Shanghai Jiao Tong University Shanghai 200240 People's Republic of China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 People's Republic of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 People's Republic of China Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing 100084 People's Republic of China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan Province Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha 410081 People's Republic of China School of Electronics and Information Engineering Soochow University Suzhou 215006 People's Republic of China

The nonlocal waveguide coupling of giant atoms can bring up novel physics and applications. In this paper, we find unconventional electromagnetically induced transparency in giant atoms that has not been reported so far. We present a consistent theory for describing the unconventional EIT which includes a real-space scattering method and a time-delayed master equation. Our analysis shows this phenomenon is a full quantum effect led by a quantized interaction between the atom and the waveguide. Our theory shows that it can be observed when the time delay between two neighboring coupling points is comparable to the relaxation time of the atom. This phenomenon results from the inherent nonlocality of the giant atom, which physically forces propagating fields to be standing waves in space and the atom exhibiting retardations in time.

关键词： Quantum optics with artificial atoms Scattering theory Quantum master equation

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