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Relative Localizability and Localization for Multirobot systems

IEEE Transactions on robotics 2025年 41卷 2931-2949页

作者： Chen, Liangming Liang, Chenyang Yuan, Shenghai Cao, Muqing Xie, Lihua Southern University of Science and Technology School of System Design and Intelligent Manufacturing Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Southern University of Science and Technology School of System Design and Intelligent Manufacturing Shenzhen518055 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore Carnegie Mellon University Robotics Institute PittsburghPA15213 United States

Inter-robot relative positions are crucial for executing various multirobot missions, such as formation maneuvering and collaborative inspection. However, the current sensing technology usually provides part of relative position information, such as inter-robot distances, bearings and angles. This prompts the study of determining inter-robot relative positions, i.e., relative localization, from these partial measurements. Based on the existing results of static networks' localizability and mobile robots' relative localization, we propose a novel concept, relative localizability to describe whether a multirobot system is relatively localizable. Given each robot's self-displacement measurements and inter-robot partial measurements in d (d ≤ 4) sampling instants, we show that a multirobot system's relative localization can be achieved in a purely algebraic and distributed manner, in which the multirobot system is said to be d-step relatively localizable. To make the results more general, we consider that the multirobot system consists of landmarks, leaders, and followers, and that the inter-robot measurements can be distances, bearings or angles. When robots' coordinate frames have different orientations, we show that the given local measurements can be used to determine robots' relative positions and their coordinate frames' relative orientations simultaneously. Simulations and experiments of relative localization for ground robots are conducted to validate the obtained results. © 2004-2012 IEEE.

关键词： Multipurpose robots

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Wearable Fiber Bragg Grating Sensors for Physiological Signal and Body Motion Monitoring: A Review

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Zhang, Feng Hao, Yupeng Tian, Aofei Yang, Zhengbao Zhang, Bo Fukuda, Toshio Shi, Chaoyang Tianjin University Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education School of Mechanical Engineering Tianjin300072 China The Hong Kong University of Science and Technology Department of Mechanical and Aerospace Engineering Hong Kong Future Robotics Organization Waseda University Tokyo162-0044 Japan Nagoya University Department of Micro-Nano Systems Engineering Aichi Nagoya464-8601 Japan

Wearable sensors play a crucial role in real-time physiological parameters and body motion monitoring, enabling early detection and prevention of potential health issues. However, conventional electrical sensors are susceptible to electromagnetic interference (EMI), limiting their application in magnetic resonance imaging (MRI), electrosurgery, and humid environments. Optical wearable devices based on fiber Bragg gratings (FBGs) offer distinct advantages such as miniaturization, immunity to EMI, high sensitivity, and multiplexing capabilities, making them promising for healthcare applications. Nevertheless, FBG sensors face challenges such as susceptibility to breakage and cross-sensitivity to temperature and multiple strain signals, creating obstacles in expanding strain monitoring range, reducing monitoring errors, and improving wear resistance. This review comprehensively introduces the latest advancements, technical challenges, and potential solutions associated with wearable FBG sensing devices for detecting physiological signals and body motion, particularly emphasizing their applications in monitoring small- and large-strain body movements. This article focuses on the sensing characteristics of FBG units in both soft and rigid substrate materials and tracks the advancement in sensing structure optimization for enhanced measurement capabilities. Future directions and opportunities for technological improvement in this field are also discussed. © 1963-2012 IEEE.

关键词： Fiber Bragg gratings

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Fast filtering algorithm based on vibration systems and neural information exchange and its application to micro motion robot

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Chinese Physics B 2014年第1期23卷 159-169页

作者：高娃查富生宋宝玉李满天 State Key Laboratory of Robotics and System Harbin Institute of Technology Department of Mechanical Design Harbin Institute of Technology

This paper develops a fast filtering algorithm based on vibration systems theory and neural information exchange approach. The characters, including the derivation process and parameter analysis, are discussed and the feasibility and the effectiveness are testified by the filtering performance compared with various filtering methods, such as the fast wavelet transform algorithm, the particle filtering method and our previously developed single degree of freedom vibration system filtering algorithm, according to simulation and practical approaches. Meanwhile, the comparisons indicate that a significant advantage of the proposed fast filtering algorithm is its extremely fast filtering speed with good filtering perfi^rmance. Further, the developed fast filtering algorithm is applied to the navigation and positioning system of the micro motion robot, which is a high real-time requirement for the signals preprocessing. Then, the preprocessing data is used to estimate the heading angle error and the attitude angle error of the micro motion robot. The estimation experiments illustrate the high practicality of the proposed fast filtering algorithm.

关键词： fast filtering vibration system neural information exchange micro motion robot

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R-SIEL: a physics-informed learning algorithm for discovering dynamics of serial manipulators

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Expert systems with Applications 2025年 287卷

作者： Omar, Mohamed Li, Ruifeng Wang, Ke Asker, Ahmed State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China Production and Mechanical Design Engineering Department Faculty of Engineering Mansoura University Mansoura 35516 Egypt Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou 450000 China School of Engineering and Applied Sciences Nile University Giza 12573 Egypt

Dynamic modeling is essential for serial manipulators’ design and control. Multi-body dynamics simulators, such as SIMULINK and Adams, can precisely replicate a robot's dynamic behavior but are incapable of determining its nonlinear dynamic model. This work aims to identify serial manipulators’ dynamics from simulation data, which extends the capability of using an algorithm that combines the Euler-Lagrange method and sparse identification of nonlinear dynamics (SINDy) with physics-based constraints and Akaike Information Criterion (AICc). The algorithm is called Recursive SINDy Euler-Lagrange (R-SIEL). The Euler-Lagrange method is used to construct a preliminary library of symbolic functions. The physics-informed constraints, which utilize the similarities between the symbolic coefficients of the dynamic equations, are employed to decrease the number of functions in the library to get a constrained library. SINDy is equipped with three kinds of constraints: the constrained library, the dataset, and similarities between links’ dynamic equations. The generation of the three distinct datasets—training, constraints, and testing data—uses simulated data from the MATLAB® SIMULINK environment. The algorithms of sequential threshold least-squares and L₀-minimization are coded with the convex optimization package CVX to determine the best dynamic model. The resulting models are tested with the testing dataset, and based on the lowest AICc, the best model is chosen. The proposed algorithm is applied to different serial manipulators: 2DOF robot, Stanford, PRR robot, ABB SCARA, UR5, and KUKA KR4 AGILUS robots. The resulting model is validated with the dynamic model derived using the conventional Euler-Lagrange method. For the considered manipulators, the R-SIEL algorithm shows a high capability to identify the dynamic model compared to the one identified compared to the previous algorithm. © 2025 Elsevier Ltd

关键词： CVX Dynamics of serial manipulators Euler-Lagrange Serial manipulators SIMULINK SINDy

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Drilling Power Consumption and Soil Conveying Volume Performances of Lunar Sampling Auger

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Chinese Journal of mechanical Engineering 2015年第3期28卷 451-459页

作者： TIAN Ye TANG Dewei DENG Zongquan JIANG Shengyuan QUAN Qiquan State Key Laboratory of Robotics and System Harbin Institute of Technology University Research Center of Package Mechanical Design Harbin University of Commerce

The sampling auger used in lunar sampling and return mission is to transmit power and convey soil, and its performance is the key factor of the whole mission. However, there is currently a lack of the optimization research on soil conveying volume and power consumption models in auger structure design. To provide the drilled object, the simulation lunar soil, whose physical and mechanical property is the same as the real soil, is made by reducing soil void ratio. The models are formulated to analyze the influence of auger structure parameters on power consumption and soil conveying volume. To obtain the optimized structure parameters of auger, the multi-objective optimization functions of the maximum soil conveying volume and minimum power consumption are developed. To verify the correctness of the models, the performances of different augers drilling simulation soil are tested. The test results demonstrate that the power consumption of optimized auger is the lowest both in theory and test, and the experimental results of soil conveying volume are in agreement with theoretical analysis. Consequently, a new method for designing a lunar sampling auger is proposed which includes the models of soil conveying volume and transportation power consumption, the optimization of structure parameters and the comparison tests. This method provides a reference for sampling auger designing of the Chinese Lunar Sample Mission.

关键词： lunar sampling optimal design auger soil conveying volume model structure parameter

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BAN: A Universal Paradigm for Cross-Scene Classification Under Noisy Annotations From RGB and Hyperspectral Remote Sensing Images

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Chen, Wentang Wen, Yibin Zheng, Juepeng Huang, Jianxi Fu, Haohuan Sun Yat-sen University School of Artificial Intelligence Zhuhai519082 China Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province School of Mechanical Engineering Robotics Institute Hangzhou310027 China Southwest Jiaotong University Faculty of Geosciences and Engineering Chengdu610032 China China Agricultural University College of Land Science and Technology Beijing100107 China Ministry of Agriculture and Rural Affairs Key Laboratory of Remote Sensing for Agri-Hazards Beijing100125 China Tsinghua University Tsinghua Shenzhen International Graduate School Shenzhen518071 China Tsinghua University Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Beijing100190 China National Supercomputer Center in Shenzhen Shenzhen518071 China

While domain adaptation (DA) methods have made significant strides in remote sensing community, most current works assume that the source domain labels are accurate. However, limited emphasis has been placed on the scenario where source data are mislabeled with noisy annotations, which is more common in real applications and referred to as noisy DA (NDA). This article formulates remote sensing cross-scene classification on NDA scenarios and proposes a novel network called bilateral adaptation network (BAN), which consists of two parts: 1) forward learning (FL), which utilizes a model learning from the noisy source domain and transfers knowledge to target domain;and 2) backward learning (BL), which utilizes a dual model to acquire knowledge from the target domain and transfer it to source domain. We conduct two parts alternately and adopt a symmetrical Kullback-Leibler (KL) loss to align predictions of the model and its dual model in the same domain. This interactive strategy is able to explore bilateral relationships between domains, implicitly reducing label noise in the source domain. In addition, BAN could serve as a universal paradigm to not only improve the existing NDA methods but also enhance recent DA approaches. Comprehensive evaluations on three publicly available RGB-band remote sensing datasets and two hyperspectral datasets validate the superior effectiveness of our proposed BAN. BAN improves the average accuracy by 6.70%-15.70% on RGB datasets and overall accuracy (OA) by 1.36%-3.14% on hyperspectral datasets with flip-20% noise compared to other state-of-the-art DA and NDA approaches. Promising results indicate the potential of our approach in tackling more general and practical problems with noisy source domain. © 2025 IEEE.

关键词： Contrastive Learning

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Advanced Centroid State Estimation and Instability Detection Framework Leveraging UKF and AdvSAE-LSTM

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IEEE Sensors Journal 2025年

作者： Mao, Han Zhu, Aibin Tu, Yao Song, Jiyuan Zheng, Chunli Li, Meng Xu, Peng Shi, Lei Liu, Yang Li, Xiao Guan, Zhenpeng Xi'an Jiaotong University Institute of Robotics and Intelligent Systems Shaanxi Key Laboratory of Intelligent Robots Xi'an710049 China Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi'an710049 China Xi'an Jiaotong University School of Energy and Power Engineering Xi'an710049 China Xi'an Jiaotong University School of Mechanical Engineering Xi'an710049 China Xi'an Jiaotong University Honghui Hospital Xi'an710000 China Xi'an Jiaotong University Department of Sports Xi'an710049 China Xi'an Jiaotong University Second Affiliated Hospital Department of General Surgery Xi'an710004 China Fourth Medical Center of PLA General Hospital Department of Rehabilitation Senior Department of Orthopedics Beijing100048 China Sports Medicine and Rehabilitation National Clinical Research Center for Orthopedics Beijing100048 China Peking University Shougang Hospital Orthopedics Department Beijing100144 China

With the growing aging population, fall detection has become a significant research focus in recent years. However, most existing studies have not effectively improved the accuracy of centroid state estimation in human instability, particularly in terms of multi-source information fusion. To address this, we propose a centroid state estimation method based on the Unscented Kalman Filter (UKF), integrating data from the five-link model and trunk IMU sensors, significantly enhancing both the accuracy and robustness of centroid state estimation. Experimental results demonstrate that the proposed method achieves estimation errors of 0.0099 m and 0.0226 m/s for centroid displacement and velocity in the x-direction, and 0.0006 m and 0.0099 m/s in the y-direction, indicating high accuracy. To overcome the reliance of traditional supervised learning methods on large amounts of labeled data for instability state estimation, we propose an unsupervised learning-based instability state estimation method, featuring the AdvSAE-LSTM model. Data from different sensors are preprocessed and independent training datasets are constructed, after which the feature maps from each sensor are concatenated to form a global feature map. Compared to baseline methods, the proposed approach significantly improves instability state detection performance. Specifically, when the SAS threshold is set to 0.02, both the False Positive Rate (FPR) and False Negative Rate (FNR) are 0%, with a detection delay of only 77.16 ms, achieving highly efficient and accurate estimation of human instability states. © 2025 IEEE.

关键词： Kalman filters

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Wearable multichannel pulse condition monitoring system based on flexible pressure sensor arrays

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microsystems & Nanoengineering 2022年第1期8卷 249-258页

作者： Jie Wang Yirun Zhu Zhiyong Wu Yunlin Zhang Jian Lin Tao Chen Huicong Liu Fengxia Wang Lining Sun Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electric EngineeringSoochow UniversitySuzhou 215123China Micro Nano System Research Center Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province&College of Information EngineeringTaiyuan University of TechnologyTaiyuan 030024China Suzhou Institute of Nano-tech and Nanobionics Chinese Academy of SciencesSuzhou 215123China

Pulse diagnosis is an irreplaceable part of traditional Chinese medical ***,application of the traditional pulse monitoring method was restricted in the modernization of Chinese medical science since it was difficult to capture real signals and integrate obscure feelings with a modern data ***,a novel multichannel pulse monitoring platform based on traditional Chinese medical science pulse theory and wearable electronics was *** pulse sensing platform simultaneously detected pulse conditions at three pulse positions(Chi,Cun,and Guan).These signals were fitted to smooth surfaces to enable 3-dimensional pulse mapping,which vividly revealed the shape of the pulse length and width and compensated for the shortcomings of traditional single-point pulse ***,the pulse sensing system could measure the pulse signals from different individuals with different conditions and distinguish the differences in pulse *** addition,this system could provide full information on the temporal and spatial dimensions of a person’s pulse waveform,which is similar to the true feelings of doctors’*** innovative,cost-effective,easily designed pulse monitoring platform based on flexible pressure sensor arrays may provide novel applications in modernization of Chinese medical science or intelligent health care.

关键词： multichannel system replace

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On Simulation for Fuzzy Control on Oxygen Concentration of the Mixed Air Supplied by Breathing Adjuster 34

On Simulation for Fuzzy Control on Oxygen Concentration of t...

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第三十四届中国控制会议

作者： SUN Hao WANG Shou-jun SUN Qing-lin Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System The College of Mechanical Engineering Tianjin University of Technology The College of Computer and Control Engineering Nankai University Tianjin Key Laboratory of Intelligent Robotics

ISBN: (纸本)9781467374439

The breathing adjuster is the core component of life support system of an aircraft and it is very important to control the valve to make the breathing adjuster supply the pilot the mixed air with the suitable oxygen concentration. In this paper the mathematical model, which describes the relation between the opening degree of the valve of the breathing adjuster and the flight altitude of the aircraft, is set up through analyzing requirement of aviation physiology and working principles of the breathing adjuster. Then a fuzzy controller is designed to control the opening degree of the valve in order to make the breathing adjuster supply to the pilot the mixed air with suitable oxygen concentration. Finally MATLAB Simulink is employed to verify the feasibility and validity of the fuzzy controlling approach. The results of simulating experiments show that the fuzzy control approach proposed in this paper can make the breathing adjuster supply the mixed air with suitable oxygen concentration to the pilot boarded on an aircraft.

关键词： Breathing adjuster,Oxygen concentration,the opening degree of the valve,Fuzzy control,Simulation

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Real-time filtering method based on neuron filtering mechanism and its application on robot speed signals

Real-time filtering method based on neuron filtering mechani...

引用

3rd International Conference on Computer Engineering and Network, CENet 2013

作者： Gao, Wa Zha, Fusheng Song, Baoyu Li, Mantian Wang, Pengfei Jiang, Zhenyu Guo, Wei State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150006 China Department of Mechanical Design Harbin Institute of Technology Harbin 150006 China

ISBN: (纸本)9783319017655

In order to implement the real-time filtering and tracking of robot signals with high efficiency, a novel real-time filtering method based on neuron filtering mechanism is developed in this paper. By considering the ubiquity of resonance in mammal and combining the mechanism of neural information processing, the derived details and the feasible parameter criterion under minimum error variance condition are given. For illustration, the application on quadruped robot is discussed. The quadruped robot feet speed signals are processed by developed real-time filtering method and Kalman filtering algorithm, respectively, and the computation time of both methods is tested. Experiment results show that the performance of developed real-time filtering method is better than that of Kalman filtering algorithm, not only in filtering and tracking performance but also in filtering speed. The novel real-time filtering method based on neuron filtering mechanism can effectively implement the real-time filtering and tracking with regard to robot signals. © 2014 Springer International Publishing Switzerland.

关键词： Neurons

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