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IEEE International Conference on Mechatronics and Automation

作者： Jia Guo Kang Hu Jinting Liu State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

To ensure reliable localization for Unmanned Aerial Vehicles(UAVs) in the presence of uncertain speed of the Unmanned Ground Vehicle (UGV), this study examines the relative localization problem of UAV-UGV using distance and bearing measurements. A Correlation of Bearing and Distance-based Relative Localization (CBDRL) algorithm is proposed in this paper under this scenario. The estimation of altitude, distance, and angle are simplified into a representation of the relative positioning between the UAV and UGV. The relative height difference is measured using the barometer in the algorithm. To determine the relative distance, Time of Arrival (TOA) ranging and Ultra Wide Band (UWB) communication are utilized. The relative direction measurement is then determined using the correlations of bearing and distance. We integrate these observations with height, direction, and distance data in an Extended Kalman Filter(EKF) to provide accurate and reliable relative position estimates that allow the UAV to track the target. The simulation results indicate that the CBDRL method developed in this study is superior to previous relative localization algorithms that rely on multi-sensor fusion, and can significantly enhance the accuracy of UAV positioning provided that range and angle measurements are precise enough.

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Multi-UAV 3D Path Planning in Simultaneous Attack

Multi-UAV 3D Path Planning in Simultaneous Attack

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International Conference on control and Automation (ICCA)

作者： Chuyi Xiong Bin Xin Miao Guo Yulong Ding Hao Zhang School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

As the key technology of UAV mission planning, path planning has a very important impact on the combat effectiveness of UAV. In order to destroy enemy units, multiple UAVs are often needed to attack the target at the same time. In the complex combat environment, the path planning of multiple UAVs is a very complex problem. On the basis of genetic algorithm, this paper designs a path planning algorithm to ensure that multiple UAVs arrive at the same time from different angles on the premise of satisfying environment constraints and the motion constraints of UAV. The algorithm uses the method of regionalization to initialize the path, designs a reasonable fitness function, and adds an adaptive disturbance operator to plan the path of each UAV. Finally, the length difference between the paths planned for each UAV is taken as the path evaluation factor. Some of the paths are replanned to achieve the goal of the same path length and simultaneous attack by UAV. The effectiveness of the algorithm is verified by experiments in typical combat scenarios, and the superiority of the adaptive disturbance operator in the optimization of the algorithm is verified by the contrast experiment.

关键词： Path planning Radar Planning Optimization Radar detection Genetic algorithms Three-dimensional displays

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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Chinese Journal of Electronics 2023年第3期19卷 451-456页

作者： Bo Li Wenju Liu Lihua Dou School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词： Training Image segmentation Analytical models Parameter estimation Estimation Probability density function Speech processing

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Convolutional Neural Network Features Comparison Between Back-Propagation and Extreme Learning Machine

Convolutional Neural Network Features Comparison Between Bac...

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Chinese control Conference

作者： Atmane Khellal Hongbin Ma Qing Fei School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

Recently deep learning based architectures have been widely deployed in many problems of artificial intelligence. Among deep learning models, Convolutional Neural Networks (CNN) have been reported in numerous successful applications such as object recognition, and natural language processing. The convolutional neural networks are trained by back-propagating the classification error using the Back-Propagation (BP) algorithm, which requires a large amount of data and slows the training process. To overcome these difficulties, a new fast and accurate approach based on Extreme Learning Machine (ELM) to train any convolutional neural network has been proposed. The developed framework (ELM-CNN) is based on the concept of auto-encoding to learn the convolutional filters with biases, by reconstructing the normalized input and the intercept term. In this paper, systematic comparison with traditional back-propagation based training method (BP-CNN) has been made with respect to two aspects qualitative and quantitative. The experimental results on the popular MNIST dataset show that the ELM-CNN algorithm achieves competitive results in terms of generalization performance and up to 16 times faster than the back-propagation based training of CNN.

关键词： Training Convolutional neural networks Feature extraction Computer architecture Convolution Machine learning Encoding

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Analysis of LoRa for Electronic Shelf Labels Based on Distributed Machine Learning

Analysis of LoRa for Electronic Shelf Labels Based on Distri...

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Chinese control Conference (CCC)

作者： Malak Abid Ali Khan Hongbin Ma Ying Jin Jingxiang Ma Zia Ur Rehman Mizanur Rahman School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

Deforestation is the primary source of global warming; traditional shelf labels use paper to display the price of the products, and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its power. Various technologies provide connectivity and a fast-updating system to eliminate the paper-based approach. LoRa is one of the contenders to design the system for electronic shelf labels (ESLs). In this paper, LoRa has been used to minify data losses and guarantee the successful decoding of the carrier signals. The data parallelism at the network server (NS) is used to distribute the data packets among the gateways (GWs) for concurrent transmissions to the end devices (EDs). The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and collision. The data rate (DR) and spreading factors (SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated tags. The orthogonality principles follow industrial, scientific, and medical regulations (ISM) to avoid data traffic congestion. GWs under different duty cycles (DC) and bandwidth (BW) are examined to minify the network saturation and reduce the energy harvesting of the tags.

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Analysis of OODA Loop based on Adversarial for complex Game Environments

arXiv

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arXiv 2022年

作者： Lu, Xiangri Ma, Hongbin Wang, Zhanqing State Key Laboratory of Intelligent Decision Control for Complex Systems Beijing Institute of Technology Beijing China Automated Institute Beijing Institute of Technology Beijing China

To address the problem of imperfect confrontation strategy caused by the lack of information of game environment in the simulation of non-complete information dynamic countermeasure modeling for intelligent game, the hierarchical analysis game strategy of confrontation model based on OODA ring (Observation, Orientation, decision, Action) theory is proposed. At the same time, taking into account the trend of unmanned future warfare, NetLogo software simulation is used to construct a dynamic derivation of the confrontation between two tanks. In the validation process, the OODA loop theory is used to describe the operation process of the complex system between red and blue sides, and the four-step cycle of observation, judgment, decision and execution is carried out according to the number of armor of both sides, and then the OODA loop system adjusts the judgment and decision time coefficients for the next confrontation cycle according to the results of the first cycle. Compared with traditional simulation methods that consider objective factors such as loss rate and support rate, the OODA-loop-based hierarchical game analysis can analyze the confrontation situation more comprehensively. © 2022, CC BY.

关键词： decision theory

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Exploiting human walking speed transitions using a dynamic bipedal walking robot with controllable stiffness and limb coordination

Exploiting human walking speed transitions using a dynamic b...

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IEEE-RAS International Conference on Humanoid Robots

作者： Yan Huang Baojun Chen Libo Meng Zhangguo Yu Xuechao Chen Qiang Huang Qining Wang Ministry of Education Beijing Institute of Technology Beijing China Robotics Research Group Peking University Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9781509047192

In this paper, we employ a two-dimensional dynamic bipedal walking robot to investigate the effects of controllable stiffness and limb coordination on speed transition of bipedal walking. The robot is equipped with a variable stiffness actuator at each joint. We proposed a central pattern generatorbased control method to implement limb coordination and realize independent control of torque and stiffness for the robot. Then we carry out human motion experiments on speed transitions. The comparison of hip joint kinematics and ground reaction forces between human and the robot during speed transitions shows that variable stiffness and limb coordination are important for adaptive human walking and can improve the performance of bipedal walking robot. The results may be used to exploit possible principles of complex human gaits.

关键词： Legged locomotion Robot kinematics Hip Oscillators Robot sensing systems Servomotors

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Visualisation of the Early-Stage Vibration of the Automatic-Gauge-control Hydraulic Cylinder Based on the Acoustic Emission Hits-Density Imaging

Visualisation of the Early-Stage Vibration of the Automatic-...

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2015年中国智能自动化学术会议

作者： Hongzhi Chen Yongli Zhao Jie Huang Chang Cheng State Key Laboratory of Hybrid Process Industry Automation System and Equipment Technology Automation Research and Design Institute of Metallurgical Industry Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Fujian Institute of Education

By taking into account the hits-density imaging technique that has been introduced by authors' previous publications, the acoustic emission bursts emitted from the automatic-gauge-control hydraulic cylinder under normal loading and early-stage vibration were investigated. First, six acoustic emission descriptors that showed significance regarding the cumulative probability distribution were visualised, followed by the reconstruction of the hits-density images using these features;Through the visual examination of the hits-density images regarding the cylinders' normal loading and early-stage vibration, apparent visual differences between normal and early-stage vibration under the same loading can be observed;By projecting the hits-density images onto the principal component space, a trajectory which represents the condition developments was observed, which shows a visual-based resolution for dealing with vast transient bursts data reduction,reconstruction and visualisation.

关键词： Visualisation Hits-density imaging Early-stage vibration Acoustic emission

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Coordinated motion control and event-based obstacle-crossing for four wheel-leg independent motor-driven robotic system via MPC

arXiv

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arXiv 2020年

作者： Liu, Dongchen Wang, Junzheng Wang, Shoukun The National Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing10081 China The Ministry of Industry and Information Technology Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing10081 China

This work investigates the coordinated motion control and obstacle-crossing problem for a four wheel-leg independent motor-driven robotic system via a model predictive control (MPC) approach based on an event-triggering mechanism. The modeling of a wheel-leg robotic control system with a dynamic supporting polygon is organized. The system dynamic model is 3 degrees of freedom ignoring the pitch, roll, and vertical motions. The single wheel dynamic is analyzed considering the characteristics of the motor-driven and the Burckhardt nonlinear tire model. As a result, an over-actuated predictive model is proposed with the motor torques as inputs and the system states as outputs. As the supporting polygon is only adjusted at certain conditions, an event-based triggering mechanism is designed to save hardware resources and energy. The MPC controller is evaluated on a virtual prototype as well as a physical prototype. The simulation results guide the parameter tuning for the controller implementation in the physical prototype. The experimental results on these two prototypes verify the efficiency of the proposed approach. © 2020, CC BY.

关键词： Geometry

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Electronic compass calibration based on Adaptive Differential Evolution Algorithm-Fourier Neural Network

Electronic compass calibration based on Adaptive Differentia...

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作者： Gong, Kun Deng, Fang Chen, Jie School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

ISBN: (纸本)9789881725592

Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN) to improve the measurement accuracy of electronic compass. This method uses Fourier neural network to model electronic compass error, and adopts Adaptive Differential Evolution to optimize the weights of neural network, and get more exact error model to compensate measured values. The compensation object is the common electronic compass composed by two-dimensional magnetic resistance sensor. Compared with the compensation effect of Least-square method, BP neural network and Fourier neural networks, It proves that the mode of this method can realize the high precision in the sample space mapping and high non-linear approximation ability, and this method has faster convergence rate, can avoid falling into local minima, reduces the training error, and improves error compensation accuracy. This method decreases the error range from 3.4° ∼ 25.2° before compensation to -0.20° ∼ 0.72°, and the average of the absolute error is 0.30°. Repeatability tests also proved the compensation plan have a good consistency. © 2011 Chinese Assoc of Automati.

关键词： Error compensation

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