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A LiDAR SLAM Based on Clustering Features and Constraint Separation

IEEE TRANSACTIONS ON INSTRUMENTATION AND measurement 2025年 74卷

作者： Wang, Shaohu Song, Aiguo Miao, Tianyuan Ji, Qinjie Li, Huijun Southeast Univ Sch Instrument Sci & Engn State Key Lab Digital Med Engn Jiangsu Key Lab Remote Measurement & Control Nanjing 210096 Peoples R China

Simultaneous localization and mapping (SLAM) is a key technology for robot localization. Currently, most robot application scenarios are limited to either indoor or outdoor environments. When robots operate across both indoor and outdoor environments, they often experience significant positioning errors or even failures. To address this problem, we propose a light detection and ranging (LiDAR) SLAM approach based on clustering features and constraint separation. First, the ground is removed from the point cloud, followed by rough segmentation of the remaining point cloud. Feature points are then extracted from each rough cluster using normalized principal component analysis (PCA) and reflection intensity information, enabling fine segmentation. Clusters are separated based on their eigenvectors, and pose variables are estimated independently according to the different constraints of the separated clusters in various directions. These estimates are then weighted and fused to complete the front-end odometry. In the back-end optimization, scan and local map matching, physical world constraints, and loop closure are employed to jointly optimize pose variables, resulting in a globally consistent point cloud map. We evaluated our method on public and custom datasets, and the results show that, compared to other state-of-the-art methods, our approach achieves better localization accuracy and more robust performance in both indoor and outdoor environments, as well as in combined indoor-outdoor scenarios.

关键词： Constraint separation indoor and outdoor envi- ronments light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) point cloud segmentation (PCS) point cloud segmentation (PCS) point cloud segmentation (PCS)

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UTC-RS: An Underwater Tracked Cleaning Robot System for Hydraulic Structures

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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第3期10卷 2311-2318页

作者： Mao, Juzheng Zhou, Jun Xie, Feng Liu, Yue Song, Guangming Song, Aiguo Southeast Univ Sch Instrument Sci & Engn State Key Lab Digital Med Engn Jiangsu Key Lab Remote Measurement & Control Nanjing 210096 Peoples R China

During the inspection and maintenance of the underwater part of hydraulic structures, it is often necessary to clean the surface of a certain area for subsequent operations. At present, there are still few robots capable of underwater fine cleaning. Therefore, this letter introduces the design of a novel tracked robot system that can be used for underwater fine surface cleaning operations. The robot uses a crawling track chassis and is equipped with a self-designed high-precision operating robotic arm, force-controlled grippers, and underwater brushing tools. Considering the complexity of the underwater environment, an underwater force-position hybrid control algorithm suitable for the robot is proposed, taking into account the water flow resistance. Its effectiveness has been verified in the experimental pool and the proposed robot system has been applied in the actual engineering site. The robot achieves a brushing efficiency of approximately 72 m(2) per hour, with a force control accuracy of +/- 0.5 N, and the cleaning effect shows a significant improvement when compared to the condition before cleaning.

关键词： Cleaning Robots Hydraulic systems Surface cleaning Mobile robots Force control Brushes Grippers Autonomous underwater vehicles Service robots Concrete surface cleaning force-position hybrid control underwater tracked robot

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Experimental analysis of hybrid multiple-layer piezoelectric-solar energy harvester for self-powered wireless sensing

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2025年 73卷

作者： Yang, Hongxin Shao, Nan Wang, Jingxiong Xu, Jiawen Xu, Husheng Zhang, Yuanjing Southeast Univ Sch Instrument Sci & Engn Jiangsu Key Lab Remote Measurement & Control Nanjing 210096 Jiangsu Peoples R China Jiangsu Police Inst Nanjing 210031 Jiangsu Peoples R China

In this study, a hybrid multiple-layer piezoelectric-solar energy harvester is proposed, which can be used to realize self-powered low-power wireless sensing in different environments. A new multiple-layer piezoelectric energy harvester was explored for vibration energy harvesting and tested with integrated solar cells. The vibration energy harvester was tested in three cases with different nonlinearity. The solar energy harvester and the vibration energy harvester were then combined to harvest ambient energy. The harvested solar energy and vibration energy were then stored in a capacitor. A low-power wireless sensing node was designed and composed of an Attiny85 microcontroller, temperature and humidity sensor, and wireless communication module. The power supply algorithm was developed for a regular evaluation of the energy in the storage capacitor and the command of operation of wireless sensing. Experimental results showed that the harvester can support the operation of the wireless sensor in hybrid, standalone vibration, and solar energy modes, respectively. The proposed hybrid energy harvesting and low-power wireless sensing node can be applied in remote sensing in power transmission lines, buildings, and coastline monitoring.

关键词： Hybrid energy harvesting Solar energy Piezoelectric vibration energy Low power consumption Self-powered wireless sensing node

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Zero-shot domain adaptation with enhanced consistency for semantic segmentation

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COMPUTERS & ELECTRICAL ENGINEERING 2025年 123卷

作者： Yang, Jiming Da, Feipeng Hong, Ru Cai, Zeyu Gai, Shaoyan Key Lab Measurement & Control Complex Syst Engn Nanjing 210000 Jiangsu Peoples R China

Zero-shot domain adaptation is a specialized area within transfer learning focused on achieving domain adaptation without using any samples from the target domain. This is particularly important when target domain samples are difficult to obtain. The rapid development in generative models, particularly diffusion models, has introduced robust tools for zero-shot domain adaptation tasks. This paper proposes an innovative framework to address domain adaptive semantic segmentation under zero-shot conditions. We introduce a Dynamic control Fusion Module, which autonomously learns the fusion scales and effectively integrates hidden states with image controls, enhancing generation in complex scenarios. Furthermore, we propose a Semantic and Image-Text Consistency Strategy, designed to impose consistency constraints on both the semantic content and the style of generated images, ensuring closer alignment with the target domain. We perform experiments on Cityscapes, ACDC, and GTAV datasets. The results show that our method improves the quality of generated target domain images and semantic segmentation performance, demonstrating its effectiveness in zero-shot domain adaptation tasks. Overall, our method shows consistent improvements over baseline approaches across the five sub-experiments. Overall, our method demonstrates consistent improvements over baseline approaches across most domain adaptation tasks. Specifically, in the tasks involving adaptation to Night and Snow, it achieves 2.6% and 2.3% higher mIoU compared to the baseline, respectively.

关键词： Domain adaptation Zero-shot Diffusion models

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Predictor-based event-triggered learning control of networked control systems with false data injection attacks and output delay

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APPLIED MATHEMATICS AND COMPUTATION 2025年 490卷

作者： Yang, Meng Zhai, Junyong Southeast Univ Sch Automat Key Lab Measurement & Control CSE Minist Educ Nanjing 210096 Jiangsu Peoples R China

This article is concerned with the predictor-based event-triggered learning control of networked control systems (NCSs) with false data injection attacks (FDIAs) and output delay. Firstly, by applying the prediction method, a new state observer including an output predictor is employed to get the estimation of delayed sampled-data output in the context of sampling. To improve the efficiency of limited networked resources, an intelligent periodic event-triggered scheme (PETS) is established, in which the triggered threshold can be optimized by the asynchronous advantage actor-critic (A3C) algorithm. Then, a predictor-based event-triggered learning control strategy is developed to handle the FDIAs occurring in the controller-to-actuator channel, and the neural network (NN) technique is introduced to approximate the false data. By applying the Lyapunov function, some sufficient conditions are given to guarantee the boundedness of the NCSs. At last, a simulation of a satellite system is given to confirm the superiorities of the presented predictor- based learning control strategy.

关键词： Networked control systems Intelligent periodic event-triggered scheme Neural networks False data injection attacks Output predictor

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Enhanced power-line energy harvesting by capacitance compensation for remote self-powered CO2 monitoring

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AIP ADVANCES 2025年第2期15卷

作者： Qian, Jieying Xu, Jiawen State Grid Suzhou Power Supply Co Suzhou 210096 Jiangsu Peoples R China Southeast Univ Sch Instrument Sci & Engn Jiangsu Key Lab Remote Measurement & Control Nanjing 210096 Jiangsu Peoples R China Southeast Univ Inst Biomed Devices Suzhou 215163 Jiangsu Peoples R China

Aiming at carbon neutrality and compliance, it is necessary to monitor carbon emissions in remote areas. In this study, we proposed a remote self-powered CO2 monitoring system powered by a capacitance compensation enhanced power line energy harvester. The harvester consists of a magnetic core, a 4000-turn coil, and a matching capacitance. The coils would generate electrical energy due to the flux variation around the power lines. Besides, we demonstrate experimentally that the introduction of capacitance compensation would enhance the power output of the energy harvester and hence boost the overall efficiency of the system. Experimental studies of the proposed system revealed a capacitance compensation output power of 103.8 mW with a resistance load of 55 k Omega under 219 mA(rms) current at 50 Hz. A microcontroller-based wireless sensor node was built for evaluation. The proposed system would ensure reliable remote CO2 monitoring mounted on power lines. (c) 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://***/licenses/by/4.0/).

关键词： Power distribution lines

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Digital image correlation calculation method for RGB-D camera multi-view matching using variable template

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measurement 2025年 240卷

作者： Hu, Huiran Song, Aiguo Southeast Univ Sch Instrument Sci & Engn Nanjing 210096 Jiangsu Peoples R China Southeast Univ Sch Instrument Sci & Engn State Key Lab Digital Med Engn Nanjing 210096 Jiangsu Peoples R China Southeast Univ Sch Instrument Sci & Engn Jiangsu Key Lab Remote Measurement & Control Nanjing 210096 Jiangsu Peoples R China

Multi-view matching is an indispensable method for digital image correlation 3D reconstruction. However, as the camera viewing angle changes, traditional DIC methods can lead to the accumulation of matching errors and an increase in mismatches, thereby affecting the 3D reconstruction quality. This paper proposes a digital image correlation method for multi-view RGB-D images based on variable template matching. Initial positioning is achieved by dynamically adjusting the size and sampling direction of the variable template. Sub-pixel registration is then performed using the inverse compositional algorithm, followed by multi-view point cloud fusion using the Iterative Closest Point (ICP) registration method. Experimental results show that the iteration speed of point cloud registration is increased by 30%, and the cumulative error is reduced by 62.5%. These improvements demonstrate that the proposed method is suitable for multi-viewpoint matching scenarios, achieving excellent results in multi-view feature point matching and multi-view point cloud fusion, significantly enhancing 3D reconstruction accuracy and efficiency.

关键词： Digital image correlation Multi-view matching Point cloud RGB-D camera Variable template

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Design and control of a Fully Actuated Aerial Manipulator System for Measuring the Thickness of Metal Facilities

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IEEE TRANSACTIONS ON INSTRUMENTATION AND measurement 2025年 74卷

作者： Hao, Shuang Mao, Juzheng Zhang, Junyi Zhao, Xiangyang Song, Guangming Song, Aiguo Liu, Peter Xiaoping Southeast Univ Sch Instrument Sci & Engn State Key Lab Digital Med Engn Jiangsu Key Lab Remote Measurement & Control Nanjing 210096 Peoples R China Carleton Univ Dept Syst & Comp Engn Ottawa ON KIS 5B6 Canada

An aerial manipulator (AM) system for thickness measurement of metal facilities is introduced in this article, which includes a fully actuated flying platform and an end effector. The AM utilizes the fully actuated advantage of the flying platform to apply controlled contact forces to the environment without the need for complex robotic manipulators. An end effector is designed, which includes an ultrasonic thickness (UT) probe mounted on a spring-damping buffer, and a coupling agent injection device allows the coupling to be applied during the inspection process. We divide the aerial inspection process into two phases: the approach phase and the contact phase. In the approach phase, we design a yaw control assistance method to ensure that the AM can contact the target surface with the desired yaw, even outside the operator's line of sight. In the contact phase, a parallel force/velocity controller tailored to the motion characteristic of the AM is proposed to achieve precise contact force control. A switching function is designed to ensure stable transitions between the motion control and force control. The control effectiveness and the ability to measure the thickness of the metal facility of the AM system are demonstrated by practical experiments.

关键词： Inspection Force Thickness measurement Force control Metals End effectors Surface impedance Attitude control Switches Surface emitting lasers Aerial contact inspection aerial manipulator (AM) aerial physics interaction force control autonomous aerial vehicle (AAV)

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Multi-dimensional Taylor Network-Based Adaptive Output Feedback control for Stochastic Nonlinear Systems with Input Delay

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2025年 1-34页

作者： Zheng, Xiao-Yi Yan, Hong-Sen Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing 210096 Jiangsu Peoples R China Southeast Univ Sch Automat Nanjing 210096 Jiangsu Peoples R China

For stochastic nonlinear systems with input delay and unmeasured states, the existing control schemes cannot be directly applied to their control problems. Proposed here is a brand-new adaptive output feedback control scheme based on the multi-dimensional Taylor network (MTN) that approximates the unknown nonlinear function. The MTN-based state observer is constructed to estimate the unmeasured states, and an appropriate auxiliary system with the same order as that of the controlled system is introduced to compensate for the influence of the input delay. Using the designed state observer, the MTN-based adaptive output feedback control strategy is proposed via the backstepping technique to ensure that all the signals of the closed-loop system remain bounded in probability, the output signal tracks the reference signal successfully, and the tracking error is bounded by the expected bound. Two simulation examples are provided to verify the validity of the developed controller.

关键词： Adaptive control Output feedback control Auxiliary system Input delay Multi-dimensional Taylor network Stochastic nonlinear system

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PCBSSD: Self-supervised symmetry-aware detector for PCB displacement and orientation inspection

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measurement 2025年 243卷

作者： Li, Jingxuan Da, Feipeng Yu, Yi Southeast Univ Sch Automat Nanjing 210096 Jiangsu Peoples R China Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing 210096 Jiangsu Peoples R China

Component displacement or orientation frequently impacts the electrical properties of high-density printed circuit boards (PCB), while current methods heavily depend on supervised learning. Diverging from these methods, we introduce a novel self-supervised symmetry-aware detector (PCBSSD), aiming at transitioning from supervised to unsupervised learning for detecting the displacement in symmetric devices. Specifically, a view-transform based paradigm is proposed to exploit symmetry in visual objects through consistencies across different views. Through self-supervision, PCBSSD detects device displacement from their rotational symmetry and orientations from reflective symmetry. To validate PCBSSD, we present a real-world dataset named PCBMO. Experiments show that our method, without any manual annotation, achieves performance comparable to state-of-the-art supervised methods as to accuracy and speed. To our best knowledge, PCBSSD is the first unsupervised displacement inspection approach harnessing the symmetry of devices. It offers a competitive alternative, particularly effective for symmetric objects that widely present in PCB.

关键词： Oriented object detection Defect detection Self-supervised learning Printed circuit boards Automated optical inspection

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