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Sparse Hierarchical LiDAR Bundle Adjustment for Online Collaborative Localization and Mapping

IEEE Robotics and Automation Letters 2025年第6期10卷 5561-5568页

作者： Liu, Jiangpin Xu, Xuecheng Lu, Sha Wang, Si Wang, Chaoqun Xiong, Rong Wang, Yue Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China Shandong University School of Control Science and Engineering Jinan250100 China

This letter presents a sparse hierarchical LiDAR bundle adjustment method for online multi-robot collaborative simultaneous localization and mapping (C-SLAM). The motivation behind this work is that the pose graph cannot directly reflect map inconsistencies. As a result, the map divergence across multiple robots persists even after pose graph optimization. While existing methods have utilized LiDAR bundle adjustment (BA) to address the divergence issues, none of these methods are particularly effective at improving online localization accuracy in multi-robot scenarios. In this work, we propose a sparse hierarchical mechanism where LiDAR bundle adjustment functions as a low-latency module within a centralized C-SLAM system. The hierarchical design accelerates the original BA process, while sparse selection further decreases the problem's complexity, thereby improving computational efficiency. The combination of high-frequency multi-robot pose graph optimization (MR-PGO) and low-frequency multi-robot hierarchical bundle adjustment (MR-HBA) improves accuracy and provides real-time localization results. To validate the effectiveness of our proposed method, we conduct comparative experiments using multiple public datasets and a self-collected dataset, benchmarking against state-of-the-art multi-robot SLAM systems. The results demonstrate that our method significantly enhances the accuracy of localization and mapping. Additionally, we have made the entire system available as an open-source implementation to benefit the broader research community. © 2016 IEEE.

关键词： Multipurpose robots

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Real-time drone detection framework based on advanced texture feature extraction and pattern recognition model using GUI

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Neural Computing and Applications 2025年第5期37卷 3435-3454页

作者： Hussen, Noha Salem, Mofreh Eldesouky, Ali I. Sakr, Noha Elghamrawy, Sally Computers and Control Systems Engineering Department Mansoura University Mansoura Egypt Computer Engineering Department Misr Higher Institute for Engineering and Technology Mansoura Egypt

The increasing prevalence of drones has raised significant concerns regarding their potential for misuse in activities such as smuggling, terrorism, and unauthorized access to restricted airspace. Consequently, the development of robust and efficient drone detection systems has become paramount. Traditional detection methods such as radar and acoustic sensors have limitations in detecting small drones and can be costly to implement. This can lead to lower detection rates and increased security breaches and safety concerns. However, prevailing methodologies often falter in achieving real-time detection with requisite precision and efficacy, particularly within complex operational environments. Motivated by the imperative to surmount these challenges, our research endeavors to introduce a pioneering real-time drone detection framework. Our study encapsulates several seminal advancements. Firstly, we proffer a groundbreaking framework that synergizes advanced integration technique based on texture feature extraction and pattern recognition techniques for real-time drone detection to increase accuracy to detect drones in different conditions such as bad weather and low resolution. Secondly, we introduce an intuitive graphical user interface, enhancing the usability and accessibility of the system in real-time scenario. Lastly, through exhaustive evaluation and comparative analysis, we substantiate the superior performance of our framework in terms of accuracy, precision, and real-time detection capabilities compared to conventional DDS methodologies. Its stability and effectiveness render it a compelling solution for security-focused entities, notably those within air force and military systems. Our experimental results reveal a commendable accuracy rate of 97%, affirming the reliability and precision 98% and recall parameter 98% of our framework in accurately identifying and detecting drones, thus surpassing recent models in the field. © The Author(s), under exclusive

关键词： Graphical user interfaces

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Sensorless control of PMSM Drives Using Octant Newton-Raphson Method and Reduced-Order EKF Considering Speed Reversal and Noise

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IEEE Transactions on Power Electronics 2025年第8期40卷 10793-10803页

作者： Xiang, Fuyuan Yu, Ke Chen, Congyan Li, Shihua Southeast University School of Automation and the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

For back electromotive force-based sensorless control in permanent magnet synchronous motor (PMSM) drives, the conventional phase-locked loop (PLL) exhibits a ±π position estimation error during speed reversal. This paper presents an octant Newton-Raphson method (ONRM) based PLL, which employs a newly defined objective function and a position octant method. It not only ensures the position estimation converges correctly during speed reversal but also improves dynamic performance compared to the conventional PLL. The applicability condition of the ONRM in the presence of noise is also analyzed in detail. Subsequently, due to the noise sensitivity of the ONRM, a reduced-order extended Kalman filter is designed to filter out the non-Gaussian noise in the position estimation while simultaneously estimating the speed. The effectiveness of the proposed sensorless control scheme is verified on a 1.5 kW PMSM drive platform. © 1986-2012 IEEE.

关键词： Extended Kalman filters

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Parallel Seeds:From Foundation Models to Foundation Intelligence for Agricultural Sustainability

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 481-484页

作者： Laiyi Fu Shunkang Ling Danyang Wu Mengzhen Kang Fei-Yue Wang Hequan Sun the Shool of Automation Science and Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University the College of Information Engineering Northwest A&F University IEEE the State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences

THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the development of sustainable agriculture, where a fundamental step is crop breeding to improve agronomic or economic traits, e.g., increasing yields of crops while decreasing resource usage and minimizing pollution to the environment [2].

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Geometric attitude tracking control of quadrotor UAVs with adaptive extended state observers

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ISA Transactions 2025年 160卷 289-297页

作者： Wang, Liping Chen, Jiapeng Huang, Yuyuan Zhu, Yongbin Pei, Hailong Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong School of Automation Science and Engineering South China University of Technology Guangzhou510640 China

This paper studies a geometric attitude tracking control problem of quadrotor unmanned aerial vehicles (UAVs) with adaptive extended state observers (AESOs). Through coordinate transformation, the error dynamic of AESO can be transformed into a canonical form which is easier to analyze by linear time-varying theory. In the presence of unknown disturbances and system uncertainties, the estimated error and stability of AESO can be analyzed. Simultaneously, a geometric tracking controller is developed on SO(3) with AESOs which guarantees that the error exponentially converges to a bounded set related to the estimated error. Some examples and a flight test are given to verify the availability of the control scheme. © 2025

关键词： Unmanned aerial vehicles (UAV)

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An ISS-Based Design of Global Robust Adaptive Output Regulators for Nonlinear systems

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IEEE Transactions on Automatic control 2025年第5期70卷 3354-3361页

作者： Han, Qi Wang, Lei Chen, Zhiyong Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China University of Newcastle School of Engineering CallaghanNSW2308 Australia

Achieving global input-to-state stability (ISS) in closed-loop systems becomes a challenging task when integrating an adaptive scheme into control design. This challenge is particularly prominent in the global output regulation of nonlinear systems. The current state of the art in global robust adaptive output regulators is limited to achieving a weaker form of integral-ISS. In this article, we present an ISS-based design framework for a class of nonlinear systems with input perturbation via a novel adaptive output regulator. Specifically, we introduce a new adaptive internal model comprising an internal model candidate, a parameter estimator, and a filter. This innovative design transforms the original output regulation problem into a robust stabilization problem. We leverage the cyclic small-gain theorem to design a robust stabilizer, ensuring that the resulting closed-loop system achieves global ISS with the perturbation acting as the input. © 1963-2012 IEEE.

关键词： Closed loop control systems

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Distance Based Single-Channel Target Speech Extraction

Distance Based Single-Channel Target Speech Extraction

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Shi, Runwu Yen, Benjamin Nakadai, Kazuhiro Dept. of Systems & Control Engineering Tokyo Institute of Technology Tokyo Japan

ISBN: (纸本)9798350368741

This paper aims to achieve single-channel target speech extraction (TSE) in enclosures by solely utilizing distance information. This is the first work that utilizes only distance cues without using speaker physiological information for single-channel TSE. Inspired by recent single-channel Distance-based separation and extraction methods, we introduce a novel model that efficiently fuses distance information with time-frequency (TF) bins for TSE. Experimental results in both single-room and multi-room scenarios demonstrate the feasibility and effectiveness of our approach. This method can also be employed to estimate the distances of different speakers in mixed speech. Online demos are available at https://***/distance-demo-page/. © 2025 IEEE.

关键词： distance based sound separation single-channel Target speech extraction

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GY-YOLO: ghost separable YOLO for pedestrian detection

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Neural Computing and Applications 2025年 1-27页

作者： Elhenidy, Ali M. Labib, Labib M. Haikal, Amira Y. Saafan, Mahmoud M. Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Faculty of Engineering Mansoura National University Gamasa Egypt

In recent years, there has been impressive development in human detection. The main challenge in pedestrian detection is the training data. To assess detectors in crowd scenarios more effectively, a novel dataset in this study called the HEP dataset (Hybrid Egyptian Pedestrian dataset) is introduced. The HEP dataset is extensive, has comprehensive annotations, and is highly diverse. The dataset images are collected by two different means. Most of the images are collected from different mobile cameras for people crossing the street in high crowded streets in Egypt, and the rest of the images are collected from the web. That is why the dataset is called hybrid. The collected dataset is more suitable for pedestrian detection as the whole images focus on pedestrian scenarios for people outdoors crossing the street. This outperforms the previous benchmarks such as CrowdHuman and WiderPerson which collect data from the web and surveillance cameras with lots of images for indoor people. GS-YOLO also is proposed to address the real-time performance and the occlusion in the crowd scenes issues. GS-YOLO is a novel pedestrian detection model that utilizes efficient Ghost and depth separable convolution modules. GS-YOLO replaces all the convolution layers in the backbone and the head of the original YOLOv8 with Ghost and depth separable modules, respectively. A deformable to-features module is proposed to enrich features for the different feature pyramid networks. GS-YOLO is trained and tested over the collected dataset and other benchmarks like CrowdHuman and WiderPerson datasets. GS-YOLO achieves competitive results over the state-of-the-art models such as YOLOv5 and YOLOv8. GS-YOLO achieves 92.8% mAp on the HEP dataset, while YOLOv5 achieves 90.3% mAp and YOLOv8 achieves 91.1% mAp. © The Author(s) 2025.

关键词： Computer vision Deep learning Pedestrian detection YOLO

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Degradation of carbamazepine by the UVA-LED_(365)/ClO_(2)/NaClO process:Kinetics,mechanisms and DBPs yield

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Journal of Environmental Sciences 2025年第2期148卷 399-408页

作者： Chenyan Hu Yihui Wu Zhengyu Dong Ziyi Dong Shengjie Ji Lili Hu Xinyu Yang Hao Liu College of Environmental and Chemical Engineering Shanghai Engineering Research Center of EnergySaving in Heat Exchange SystemsShanghai University of Electric PowerShanghai 200090China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China

A mixed oxidant of chlorine dioxide(ClO_(2))and NaClO was often used in water treatment.A novel UVA-LED(_(365) nm)-activated mixed ClO_(2)/NaClO process was proposed for the degradation of micropollutants in this ***(CBZ)was selected as the target *** with the UVA_(365)/ClO_(2) process,the UVA_(365)/ClO_(2)/NaClO process can improve the degradation of CBZ,with the rate constant increasing from 2.11×10^(−4) sec^(−1) to 2.74×10^(−4) sec^(−1).In addition,the consumption of oxidants in the UVA_(365)/ClO_(2)/NaClO process(73.67%)can also be lower than that of UVA_(365)/NaClO(86.42%).When the NaClO ratio increased,both the degradation efficiency of CBZ and the consumption of oxidants can increase in the UVA_(365)/ClO_(2)/NaClO *** solution pH can affect the contribution of NaClO in the total oxidant *** the pH range of 6.0-8.0,the combination process can generate more active species to promote the degradation of *** change of active species with oxidant molar ratio was investigated in the UVA_(365)/ClO_(2)/NaClO *** ClO_(2) acted as the main oxidant,HO·and Cl·were the main active species,while when NaClO was the main oxidant,ClO·played a role in the *** chloride ion(Cl^(-)),bicarbonate ion(HCO_(3)^(-)),and nitrate ion(NO_(3)^(-))can promote the reaction *** the concentration of NaClO in the reaction solution increased,the generation of chlorates will *** UVA_(365)/ClO_(2)/NaClO process can effectively control the formation of volatile disinfection by-products(DBPs),and with the increase of ClO_(2) dosage,the formation of DBPs can also decrease.

关键词： UVA Chlorine dioxide(ClO_(2)) NaClO Carbamazepine(CBZ) Disinfection by-products

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