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An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

Computer Modeling in Engineering & sciences 2023年第12期137卷 2621-2640页

作者： Jing Xin Kenan Du Jiale Feng Mao Shan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an710048China Australian Centre for Field Robotics The University of SydneySydney2006Australia

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D *** current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time *** address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space ***,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud ***,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud *** also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor *** results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic ***,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

关键词： 3D semantic map online reconstruction RGB-D images semantic segmentation indoor mobile robot

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Relative navigation method for unmanned aerial vehicles formation using consensus unscented Kalman filter 6

Relative navigation method for unmanned aerial vehicles form...

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6th International Symposium on Autonomous systems, ISAS 2023

作者： Zhuang, Zhixing Gong, Baichun Ding, Xin Hao, Mingrui Chen, Linxiu Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316155

A relative navigation method in which the measurement information between aircraft only has distance or angle was proposed to achieve accurate relative navigation between aircraft formations in the global navigation satellite system (GNSS) Denied Environment. In addition, four relative measurement schemes are analyzed. An augmented state is introduced in the relative navigation system model, and the observability analysis of the navigation system is carried out relying on the Lie derivative theory, which gives the limitation of motion: the relative position and velocity of the aircraft cannot be parallel or zero, and a single aircraft cannot keep flying straight. A consensus unscented Kalman filter (CUKF) algorithm is established using the geometric characteristics in flight. The observability of the system state is improved after using the additional constraint. Finally, a standard Monte Carlo simulation system is established, and the system simulation is carried out, which shows that the Observability analysis is verified to be correct, and the algorithm demonstrates high accuracy. © 2023 IEEE.

关键词： Observability

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Preliminary Study on the Method of Generating Infrared Image Based on CycleGAN 19th

Preliminary Study on the Method of Generating Infrared Image...

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19th Chinese intelligent systems Conference, CISC 2023

作者： Sun, Baiping Tong, Jiahui Geng, Huapin Beijing Electromechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789819968855

Traditional infrared scene simulation method mainly includes the establishment of 3D geometric model of the target, the establishment of scene radiation model, the relationship mapping between infrared radiation and infrared image gray value and other steps. The whole process is tedious, and contain more calculated parameters. This paper introduce CycleGAN network, draw on its ring network structure and unpaired data or paired data as a training set, realize the advantages of domain image conversion effect, explore the visible light image conversion into corresponding infrared image, solve the problems such as samples in the process of infrared imaging simulation is limited, fidelity is low, and coverage is limited. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Infrared radiation

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A GPR-Aided Method for Collaborative Relative Navigation for Multiple Unmanned Aerial Vehicles During Ranging Measurement Outages 6

A GPR-Aided Method for Collaborative Relative Navigation for...

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6th International Symposium on Autonomous systems, ISAS 2023

作者： Ding, Xin Hao, Mingrui Gong, Baichun Chen, Linxiu Zhuang, Zhixing Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316155

To maintain reliable relative navigation accuracy of unmanned aerial vehicles (UAVs) during range measurement outages, a GPR-aided ranging method is proposed to assist the extended Kalman filter for measurement updates. Specifically, when the on-board ranging measurement is available, a Gaussian process regression (GPR) algorithm is used to train the mapping model between acceleration, angular velocity of the inertial navigation system (INS), relative position, and the ranging distance. When ranging measurement is unavailable, the trained GPR algorithm is used for distance prediction, replacing the ranging measurement and being used for consensus extended Kalman filter (CEKF) measurement update to reduce the degree of relative navigation error divergence. Numerical simulation was conducted with three UAVs performing cooperative flight, the results show that the proposed algorithm can provide reliable distance prediction during ranging outage and effectively reduce the divergence of relative state estimation error. © 2023 IEEE.

关键词： Inertial navigation systems

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Online Weapon-target Assignment based on Distributed Auction Mechanism 2

Online Weapon-target Assignment based on Distributed Auction...

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2nd International Conference on Robotics, Automation and intelligent control, ICRAIC 2022

作者： Si, Jiashuai Hao, Mingrui Sci. and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Beijing China

To solve the problem of online weapon-target assignment (OWTA) in the integration of large-scale search and attack in unknown environment, an OWTA algorithm based on distributed auction mechanism is presented. Aiming at the problem that the traditional combinatorial optimization algorithm needs to set up the global battlefield situation in advance, considering the consumability of resources in the attack process, the integrated search and attack task flow is established. Considering the communication restricted environment, the unmanned aerial vehicles (uavs) are grouped, with centralized architecture within the group and distributed structure between the groups, and the corresponding distributed auction mechanism is constructed to achieve OWTA within the communication range limited. In order to solve the problem that it is difficult to ensure the time consistency of the coordinated attack target, a dubins cooperative path planning based on cooperative particle swarm optimization (CPSO) algorithm is proposed. Particle swarm optimization algorithm is used to adjust the radius of the dubins path of each bomb, so that the uav in the same group can hit the target simultaneously without collision and have the shortest flight range. The simulation results show that the designed distributed auction algorithm takes into account the consumption of attack resources, and quickly redistributes the firepower to the new targets in the dynamic uncertain environment, which ensures the maximization of the execution efficiency of the multi-machine cluster fire allocation task. © Published under licence by IOP Publishing Ltd.

关键词： Combinatorial optimization

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Multiple UAVs Time-Cooperative Guidance Law Under Directed Communication Topologies

Multiple UAVs Time-Cooperative Guidance Law Under Directed C...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Lyu, Teng Xu, Cheng Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811581540

Collaborative guidance of multiple UAVs with directional communication topologies for directional targets is being researched. First, a new multi-UAV time-cooperative guidance model is established based on the relative motion equation of the UAV target. Next, based on the cooperative control theory of multi-agent systems, a rigorously proven distributed time cooperative guidance method is designed. This ensures that the impact times of multiple UAVs in a directional topology reach asymptotic consistency. After reaching the impact time consensus, all unmanned aerial vehicles use traditional PN guidance techniques to ensure that the UAV accurately hits the target without impacting the impact time consensus. Finally, the simulation results prove the effectiveness of the designed collaborative guidance method. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Multi-Time-Scale Variational Mode Decomposition-Based Robust Fault Diagnosis of Railway Point Machines Under Multiple Noises

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Chinese Journal of Electronics 2024年第3期33卷 814-822页

作者： Junqi LIU Tao WEN Guo XIE Yuan CAO Clive Roberts Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology The School of Electronic and Information Engineering Beijing Jiaotong University Birmingham Centre for Railway Research and Education University of Birmingham

The fault diagnosis of railway point machines(RPMs) has attracted the attention of engineers and *** have studies considered diverse noises along the *** fulfill this aspect,a multi-time-scale variational mode decomposition(MTSVMD) is proposed in this paper to realize the accurate and robust fault diagnosis of RPMs under multiple *** decomposes condition monitoring signals after coarse-grained processing in varying *** this manner,the information contained in the signal components at multiple time scales can construct a more abundant feature space than at a single *** the experimental validation,a random position,random type,random number,and random length(4R) noise-adding algorithm helps to verify the robustness of the *** adequate experimental results demoristrate the superiority of the proposed MTSVMD-based fault diagnosis.

关键词： Railway point machines Fault diagnosis Multi-time-scale Variational mode decomposition

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Warship Object Detection in Remote Sensing Images with Improved YOLOv5

Warship Object Detection in Remote Sensing Images with Impro...

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2023 China Automation Congress, CAC 2023

作者： Liu, Caiyuan Li, Yuan Chen, Linxiu Guan, Weili School of Automation Beijing Institute of Technology Beijing100081 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9798350303759

Aiming at the task of detecting ships on the sea surface in remote sensing images, there are a lot of disturbances such as variable object sizes, cloud occlusion, complex image backgrounds, and different ship orientations, etc. In this paper, we propose a ship rotating object detection network based on the improved YOLOv5, which is constructed through the strategies of introducing Swin Transformer as a feature extraction network to enhance the feature extraction performance of the network, introducing a rotating detection head to realize the detection of the rotation angle, and modifying the network loss function to accelerate the convergence of the network. The network finally achieves a 71.7% map on ShipRSImageNet validation set, which is an improvement of 2.4% compared with the original network model. The network proposed in this paper solves the problem that the YOLOv5 algorithm is unable to detect rotating objects, and the network based on the self-attention mechanism is used to further enhance the ability to detect small objects. Finally, a ship object detector that can be used in real remote sensing satellite images is obtained. © 2023 IEEE.

关键词： Feature extraction

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Linear Quadratic Pursuit and Evasion Differential Game Guidance Strategy with Obstacle Avoidance 34th

Linear Quadratic Pursuit and Evasion Differential Game Guida...

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34th Congress of the International Council of the Aeronautical sciences, ICAS 2024

作者： Wang, Xintao Yang, Ming Ma, Ping Chao, Tao Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150080 China

In this paper, a class of linear quadratic differential game guidance scheme is presented to study the pursuit and evasion conflict scenario that an evader establishes a static obstacle and performs the evasion maneuver to avoid a pursuer. First of all, the engagement kinematic model among the obstacle, the pursuer, and the evader is linearized according to the assumption. The issue of the pursuit and evasion game is transformed into a linear quadratic differential game through the dead zone and the cost functions. Furthermore, the linear quadratic differential game approach is utilized to obtain the guidance strategy with obstacle avoidance. Numerical simulation results are employed to validate the performance of the guidance policy. © 2024, International Council of the Aeronautical sciences. All rights reserved.

关键词： Cost functions

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An Improved MPCA Algorithm with Weight Matrix Based on Many-Objective Optimization 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Huang, Jianrou Zhang, Jingbo Wang, Qian Cai, Xingjuan Complex System and Computational Intelligent Laboratory Taiyuan University of Science and Technology Taiyuan030024 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Data compression and dimensionality reduction play an essential role in machine learning. In recent years, due to the relatively high dimensionality of data, dimensionality reduction based on vectors cannot be well processed and will destroy the structure of high-dimensional data. Therefore, research on dimensionality reduction based on tensors is increasing daily. This paper mainly studies the extended multi-linear principal component analysis (MPCA) of principal component analysis (PCA) in the tensor space. This paper proposes a MPCA dimension reduction algorithm based on the weight matrix, followed by the construction of a multi-objective model. An IP-NSGA-III is proposed to solve the weight matrix. Experimental results of hyperspectral image classification show that, compared with different algorithms, the MPCA algorithm based on the weight matrix proposed in this paper has a better dimension-reduction effect. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Principal component analysis

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