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Accelerated Distributed Aggregative Optimization

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arXiv 2023年

作者： Liu, Jiaxu Chen, Song Cai, Shengze Xu, Chao The School of Mathematical Sciences Zhejiang University Zhejiang Hangzhou310027 China The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang Hangzhou310027 China Huzhou Institute of Zhejiang University Zhejiang Huzhou313000 China

In this paper, we investigate a distributed aggregative optimization problem in a network, where each agent has its own local cost function which depends not only on the local state variable but also on an aggregated function of state variables from all agents. To accelerate the optimization process, we combine heavy ball and Nesterov’s accelerated methods with distributed aggregative gradient tracking, and propose two novel algorithms named DAGT-HB and DAGT-NES for solving the distributed aggregative optimization problem. We analyse that the DAGT-HB and DAGT-NES algorithms can converge to an optimal solution at a global R−linear convergence rate when the objective function is smooth and strongly convex, and when the parameters (e.g., step size and momentum coefficients) are selected within certain ranges. A numerical experiment on the optimal placement problem is given to verify the effectiveness and superiority of our proposed algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Optimization

NF-Atlas: Multi-Volume Neural Feature Fields for Large Scale LiDAR Mapping

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arXiv 2023年

作者： Yu, Xuan Liu, Yili Mao, Sitong Zhou, Shunbo Xiong, Rong Liao, Yiyi Wang, Yue The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Huawei Cloud Computing Technologies Co. Ltd. Shenzhen China

LiDAR Mapping has been a long-standing problem in robotics. Recent progress in neural implicit representation has brought new opportunities to robotic mapping. In this paper, we propose the multi-volume neural feature fields, called NF-Atlas, which bridge the neural feature volumes with pose graph optimization. By regarding the neural feature volume as pose graph nodes and the relative pose between volumes as pose graph edges, the entire neural feature field becomes both locally rigid and globally elastic. Locally, the neural feature volume employs a sparse feature Octree and a small MLP to encode the signed distance function (SDF) of the submap with an option of semantics. Learning the map using this structure allows for end-to-end solving of maximum a posteriori (MAP) based probabilistic mapping. Globally, the map is built volume by volume independently, avoiding catastrophic forgetting when mapping incrementally. Furthermore, when a loop closure occurs, with the elastic pose graph based representation, only updating the origin of neural volumes is required without remapping. Finally, these functionalities of NF-Atlas are validated. Thanks to the sparsity and the optimization based formulation, NF-Atlas shows competitive performance in terms of accuracy, efficiency and memory usage on both simulation and real-world datasets. The project page is: https://***/NFAtlas/ Copyright © 2023, The Authors. All rights reserved.

关键词： Mapping

The Novel Adaptive Fractional Order Gradient Decent Algorithms Design Via Robust control

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arXiv 2023年

作者： Liu, Jiaxu Chen, Song Cai, Shengze Xu, Chao School of Mathematical Sciences Zhejiang University Zhejiang Hangzhou310027 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang Hangzhou310027 China Huzhou Institute of Zhejiang University Zhejiang Huzhou313000 China

The vanilla fractional order gradient descent may oscillatorily converge to a region around the global minimum instead of converging to the exact minimum point, or even diverge, in the case where the objective function is strongly convex. To address this problem, a novel adaptive fractional order gradient descent (AFOGD) method and a novel adaptive fractional order accelerated gradient descent (AFOAGD) method are proposed in this paper. Inspired by the quadratic constraints and Lyapunov stability analysis from robust control theory, we establish a linear matrix inequality to analyse the convergence of our proposed algorithms. We prove that the proposed algorithms can achieve R-linear convergence when the objective function is L-smooth and m-strongly-convex. Several numerical simulations are demonstrated to verify the effectiveness and superiority of our proposed algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Robust control

A Comb-Shaped Microfluidic Aptasensor for Rapid and Sensitive On-Site Simultaneous Detection of Aflatoxin B1 and Deoxynivalenol

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SSRN

SSRN 2024年

作者： Wu, Jinlei Yuan, Haojun Yang, Yunhua Yang, Ping Yan, Xinxin Mu, Ying Yang, Panhui Gao, Wanlei Jin, Qinghui College of Information Science and Engineering Ningbo University Zhejiang Ningbo315211 China Mechanical and Electrical Engineering School Zhejiang Fashion Institute of Technology Zhejiang Ningbo315211 China Research Center for Analytical Instrumentation Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology Zhejiang University Zhejiang Hangzhou310007 China State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China

Mycotoxins are widely co-contaminating agricultural products and their derivatives, and on-site monitoring of multiple mycotoxins remains a challenge. Here, we present a novel electrochemical aptasensor for the simultaneous detection of aflatoxin B1 (AFB1) and deoxynivalenol (DON). The sensor is equipped with dual working electrode microelectrodes and comb-shaped polydimethylsiloxane (PDMS) microfluidic chip, quantification of toxin concentrations using differential pulse voltammetry (DPV) detection methods. Moreover, no additional modification of the signal amplification probes is required, and label-free detection of both toxins can be accomplished in less than 20 minutes, achieving limits of detection of 7.74 pg/mL for AFB1 and 0.172 ng/mL for DON. The sensor has demonstrated excellent specificity and stability in standard toxin solutions and example corn assays. In summary, this electrochemical aptasensor with an integrated comb-shaped microchannel offers the possibility of rapid and highly sensitive on-site detection of AFB1 and DON. © 2024, The Authors. All rights reserved.

关键词： Aflatoxins

Indirect Adaptive Robust Trajectory Tracking control of Hard Rock TBM with Load Variation of Tunneling Face

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Chinese Journal of Mechanical Engineering 2019年第2期32卷 168-179页

作者： Chengjun Shao Jianfeng Liao Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Fluid Power Transmission and Control Zhejiang University

Posture adjustment of open-type hard rock tunnel boring machine(TBM) can be achieved by properly adjusting the hydraulic pressure of gripper cylinder and torque cylinders. However, the time-varying inhomogeneous load acting on tunneling face of TBM and complex stratum working condition can cause the trajectory deviation. In this paper,the position and posture rectification kinematics and dynamics models of TBM have been established in order to track the trajectory. Moreover, there are uncertain parameters and uncertain loads from complex working conditions in the dynamic model. An indirect adaptive robust control strategy is applied to achieve precise position and posture trajectory tracking control. Simulation results show when the position deviation only occurs in Y-axis and the current orientation is parallel with the designed axis, the deviation can be corrected by controlling the pressure of gripper cylinder and the actual trajectory meets the designed axis when TBM is pushed forward 0.14 m in X-axis. If the deviation only occurs in Z-axis, then the deviation can be corrected by controlling torque cylinders. If the position deviation occurs both in Y-axis and Z-axis at the same time, the pressure of gripper cylinder and torque cylinders should be controlled at the same time to rectify the deviation. Simulation results are shown to illustrate the e ectiveness and robustness of the proposed controller. This research proposes an indirect adaptive robust controller that can track the planned tracking trajectory smoothly and rapidly.

关键词： Open type hard rock TBM Inhomogeneous load Position and posture rectification Indirect adaptive robust control

Consistent and Asymptotically Statistically-Efficient Solution to Camera Motion Estimation

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arXiv 2024年

作者： Zeng, Guangyang Zeng, Qingcheng Li, Xinghan Mu, Biqiang Chen, Jiming Shi, Ling Wu, Junfeng The School of Data Science Chinese University of Hong Kong Shenzhen Shenzhen518172 China The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

Given 2D point correspondences between an image pair, inferring the camera motion is a fundamental issue in the computer vision community. The existing works generally set out from the epipolar constraint and estimate the essential matrix, which is not optimal in the maximum likelihood (ML) sense. In this paper, we dive into the original measurement model with respect to the rotation matrix and normalized translation vector and formulate the ML problem. We then propose a two-step algorithm to solve it: In the first step, we estimate the variance of measurement noises and devise a consistent estimator based on bias elimination;In the second step, we execute a one-step Gauss-Newton iteration on manifold to refine the consistent estimate. We prove that the proposed estimate owns the same asymptotic statistical properties as the ML estimate: The first is consistency, i.e., the estimate converges to the ground truth as the point number increases;The second is asymptotic efficiency, i.e., the mean squared error of the estimate converges to the theoretical lower bound - Cramer-Rao bound. In addition, we show that our algorithm has linear time complexity. These appealing characteristics endow our estimator with a great advantage in the case of dense point correspondences. Experiments on both synthetic data and real images demonstrate that when the point number reaches the order of hundreds, our estimator outperforms the state-of-the-art ones in terms of estimation accuracy and CPU time. Copyright © 2024, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

I2EKF-LO: A Dual-Iteration Extended Kalman Filter Based LiDAR Odometry

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I2EKF-LO: A Dual-Iteration Extended Kalman Filter Based LiDA...

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

作者： Wenlu Yu Jie Xu Chengwei Zhao Lijun Zhao Thien-Minh Nguyen Shenghai Yuan Mingming Bai Lihua Xie State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Hangzhou Guochen Robot Technology Company Limited Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

LiDAR odometry is a pivotal technology in the fields of autonomous driving and autonomous mobile robotics. However, most of the current works focus on nonlinear optimization methods, and still existing many challenges in using the traditional Iterative Extended Kalman Filter (IEKF) framework to tackle the problem: IEKF only iterates over the observation equation, relying on a rough estimate of the initial state, which is insufficient to fully eliminate motion distortion in the input point cloud; the system process noise is difficult to be determined during state estimation of the complex motions; and the varying motion models across different sensor carriers. To address these issues, we propose the Dual-Iteration Extended Kalman Filter (I 2 EKF) and the LiDAR odometry based on I 2 EKF (I 2 EKF-LO). This approach not only iterates over the observation equation but also leverages state updates to iteratively mitigate motion distortion in LiDAR point clouds. Moreover, it dynamically adjusts process noise based on the confidence level of prior predictions during state estimation and establishes motion models for different sensor carriers to achieve accurate and efficient state estimation. Comprehensive experiments demonstrate that I 2 EKF-LO achieves outstanding levels of accuracy and computational efficiency in the realm of LiDAR odometry. Additionally, to foster community development, our code is open-sourced. 1

关键词： Point cloud compression Laser radar Accuracy Nonlinear distortion Noise Robot sensing systems Mathematical models Odometry Kalman filters state estimation

Learning to Compensate for the Drift and Error of Gyroscope in Vehicle Localization 31

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Learning to Compensate for the Drift and Error of Gyroscope ...

31st IEEE Intelligent Vehicles Symposium, IV 2020

作者： Zhao, Xiangrui Deng, Chunfang Kong, Xin Xu, Jinhong Liu, Yong Institute of Cyber-Systems and Control Zhejiang University Zhejiang310027 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang310027 China

Self-localization is an essential technology for autonomous vehicles. Building robust odometry in a GPS-denied environment is still challenging, especially when LiDAR and camera are uninformative. In this paper, We propose a learning-based approach to cure the drift of gyroscope for vehicle localization. For consumer-level MEMS gyroscope (stability ?10° /h), our GyroNet can estimate the error of each measurement. For high-precision Fiber optics Gyroscope (stability ?0.05° /h), we build a FoGNet which can obtain its drift by observing data in a long time window. We perform comparative experiments on publicly available datasets. The results demonstrate that our GyroNet can get higher precision angular velocity than traditional digital filters and static initialization methods. In the vehicle localization, the FoGNet can effectively correct the small drift of the Fiber optics Gyroscope (FoG) and can achieve better results than the state-of-the-art method. © 2020 IEEE.

关键词： Gyroscopes

A new flexible multi-AGVs scheduling model with pre-waiting time in an intelligent manufacturing system

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A new flexible multi-AGVs scheduling model with pre-waiting ...

IEEE International Conference on Networking, Sensing and control

作者： Haoyi Niu Zichao Xing Xingkai Wang Weimin Wu Tao Zhang State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665440493

This paper studies a flexible flow-shop scheduling problem with limited resources (FFSP-LR) which is based on an actual air-conditioning production line in an intelligent manufacturing system. It extends the classical flexible flow-shop scheduling problem by considering practical constraints of the number of the AGVs (automated guided vehicles) on the transportation resources. The problem aims to determine the optimal scheduling results that minimizes the idle waiting time and pick-up waiting time of the workstations. To solve this problem, a pre-waiting scheduling model (PWSM) is proposed by taking into account the advance waiting time of AGVs. The experimental results show that the proposed PWSM is able to reduce idle waiting time and pick-up waiting time up to 425.01 and 414.25 comparing to traditional FCFS (First Come First Serve) strategy respectively. Correspondingly, these two types of time could be saved up to 87.01% and 98.57%. Finally, the overall efficiency of the intelligent manufacturing system is improved since the PWSM is able to effectively reduce the idle waiting time and pick-up waiting time of the workstations under the condition of limited transportation resources.

关键词： Job shop scheduling Transportation Optimal scheduling Production Workstations Numerical models Sensors