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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Kim, Ho Joong Lombaerts, Thomas Looye, Gertjan Department of Aerospace Engineering San José State University Santa Clara County San JoseCA95121 United States Aerospace Engineering Department Charles W. Davidson College of Engineering United States KBR NASA Ames Research Center Intelligent Systems Division Mail Stop 269-1 Moffett FieldCA94083 United States Institute of System Dynamics and Control German Aerospace Center DLR Weßling82234 Germany

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper describes the design and evaluation of an autoflight controller under maximized crosswind landing scenarios using Nonlinear Dynamic Inversion (NDI) and Incremental Nonlinear Dynamic Inversion (INDI) control methods. The simulation model is representative of a nonlinear, 6 DOF twin-engined civilian transport aircraft in landing configuration starting 300 meters above the runway. The designed flight controller is of cascaded control structure based upon the time scale separation principle. While only INDI based design is evaluated, each control loop implements both NDI and INDI based design, accompanied with feed forward path control for select loops. The controller is evaluated through multiple Monte Carlo statistical analyses, each set containing 2000 landings, which are performed under widely distributed environmental and system parameters. The designed INDI method based controller as discussed in this paper satisfies all safe landing criteria for crosswind landings of up to 30 knots. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Aircraft landing

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Minimizing Data Collection Latency for Coexisting Time-Critical Wireless Networks with Tree Topologies

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2354-2369页

作者： Zhang, Jialin Liang, Wei Yang, Bo Shi, Huaguang Liang, Ying-Chang Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control System Shenyang Institute of Automation Shenyang110016 China Northwest A and F University College of Information Engineering Yangling712100 China Henan University School of Artificial Intelligence Zhengzhou450046 China University of Electronic Science and Technology of China Center for Intelligent Networking and Communications Chengdu611731 China

Time-Critical Wireless Network (TCWN) is a promising communication technology that can satisfy the low latency, high reliability, and deterministic requirements of mission-critical applications. Multiple TCWNs required by various applications inevitably coexist with each other. Most existing works aim to achieve acceptable latency or consider the simplest topology (i.e., line topology). As latency requirements become more stringent, exploring the minimum data collection latency becomes an interesting problem. In this paper, the coexisting system consists of multiple tree-topology-based TCWNs. We first establish a conversion framework to convert an arbitrary tree topology into multiple analogous line topologies to reduce the analysis complexity. We then propose a Time-Critical wireless network Scheduling (TCS) algorithm to minimize the data collection latency of coexisting TCWNs. The TCS algorithm consists of two phases. In the internetwork scheduling phase, we strictly derive a general expression to characterize the practical network requirements. In the intranetwork scheduling phase, we design two levels of priority assignment algorithms to accurately characterize the critical states and resource requirements of different nodes. We conduct extensive simulations to verify the effectiveness of the TCS algorithm. The evaluation results show that the TCS algorithm can achieve minimum data collection latency in more than 99.956% cases, and the maximum difference compared to the optimal value is one time slot. © 2004-2012 IEEE.

关键词： Scheduling algorithms

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CPL-SLAM: Centralized Collaborative Multi-Robot Visual-Inertial SLAM Using Point-and-Line Features

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IEEE Internet of Things Journal 2025年第12期12卷 21866-21875页

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center The Ministry of Education for Intelligent Control System and Intelligent Equipment Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering China Carleton University Canada

Traditional visual-inertial SLAM (Simultaneous Localization and Mapping) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intra-robot and inter-robot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

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Robust optimization-based fusion of GNSS and Visual-Inertial-Wheel Odometry

Robust optimization-based fusion of GNSS and Visual-Inertial...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Hou, Jake Jie Wu, Xinrui Shan, Jiwei Li, Dun Wang, Hesheng Shanghai Jiao Tong University Department of Automation China Shanghai Karlang Industrial Nantong Intelligent Technology Co. Ltd China Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

SLAM is significant to autonomous mobile robots. In order to realize drift-free state estimation and provide accurate localization results for the subsequent navigation, we develop an optimization-based framework consisting of a high-frequency Inertial-Wheel Odometry(IWO), Visual-Inertial-Wheel Odometry(VIWO) and a global fusion module. To fuse the local state with the position provided by GNSS, we perform ternary edge in factor graph optimization to estimate the transformation between the local frame and ENU coordinate. Thanks to the tightly-coupled VIWO, the localization property of the odometry presents more robustness, and improve the accuracy of global fusion. A noise repropagation strategy is introduced to ensure the consistency of the IMU and wheel odometer. We evaluate the proposed system on public datasets and test it in real-world scenario. The experimental results show that our system achieves accurate pose estimation in outdoor environments. © 2022 IEEE.

关键词： Frequency estimation

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LHMap-loc: Cross-Modal Monocular Localization Using LiDAR Point Cloud Heat Map

LHMap-loc: Cross-Modal Monocular Localization Using LiDAR Po...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Xinrui Wu Jianbo Xu Puyuan Hu Guangming Wang Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Department of Engineering University of Cambridge Cambridge U.K

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Localization using a monocular camera in the pre-built LiDAR point cloud map has drawn increasing attention in the field of autonomous driving and mobile robotics. However, there are still many challenges (e.g. difficulties of map storage, poor localization robustness in large scenes) in accurately and efficiently implementing cross-modal localization. To solve these problems, a novel pipeline termed LHMap-loc is proposed, which achieves accurate and efficient monocular localization in LiDAR maps. Firstly, feature encoding is carried out on the original LiDAR point cloud map by generating offline heat point clouds, by which the size of the original LiDAR map is compressed. Then, an end-to-end online pose regression network is designed based on optical flow estimation and spatial attention to achieve real-time monocular visual localization in a pre-built map. In addition, a series of experiments have been conducted to prove the effectiveness of the proposed method. Our code is available at: https://***/IRMVLab/LHMap-loc.

关键词： Location awareness Point cloud compression Visualization Laser radar Accuracy Robot vision systems Real-time systems

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Multi-Vision Sensor Fusion Localization and Navigation of Robot in Unstructured Environment

Multi-Vision Sensor Fusion Localization and Navigation of Ro...

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Chinese Automation Congress (CAC)

作者： Fuhao Shang Lelai Zhou Yibin Li Chen Zhang Center for Robotics School of Control Science and Engineering Shandong University Jinan China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China

Robots that have the ability to work in complex natural environments have broad application prospects. Focusing on the lack of autonomous navigation ability of the robot in the wild environment, this paper respectively proposes the improved localization and trajectory tracking methods. The multi-vision sensor fusion localization method is based on dual-factor graph optimization, which realizes the rapid processing of asynchronous sensor information. The dual-factor graph optimization can improve the localization accuracy and fault tolerance of the system under outdoor environments. Meanwhile, the multi-fine granularity MPC-based trajectory tracking method for unstructured terrain. Under the large-scale global path, a refined map is built around the robot. And the elevation difference is introduced to impose new constraints at the omni-directional velocity. The proposed methods in this study are implemented in actual environment. Experiments and simulations in representative terrain environments have verified the effectiveness of the improved methods.

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Design of an Embedded Leg Capsule Robot 20

Design of an Embedded Leg Capsule Robot

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Yihui Xue, Tao Wang, Jing Yueliwasi, Yimuranjiang Tianjin University of Technology Tianjin Key Laboratory for Advanced Electromechanical System Design and Intelligent Control 391 Binshui Xidao Tianjin China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education 391 Binshui Xidao Tianjin China

ISBN: (纸本)9798350320831

The capsule robot enters the patient's intestinal system directly by swallowing and takes continuous images using the miniature camera unit it carries, but during its travel, its own gravity and the peristaltic movement of the intestine make the physician limited in obtaining images of the intestine and making a diagnosis. In order to solve this problem, a capsule endoscope with an embedded leg mechanism is proposed. Compared to commercially available capsule robot. This capsule robot can easily move through the intestine autonomously by means of the relationship between the leg, the screw nut and the linkage, enabling forward, backward and stationary functions. The capsule robot has a diameter of 14 mm, a length of 30 mm and a maximum diameter of 26.66 mm with the legs spread out. The hollow space is allocated to include basic endoscopic components such as a miniature camera and a rotating motor. A series of tests, including in vitro tests, were carried out to test the feasibility of the leg mechanism of this capsule robot. Based on the results of the experiments, the proposed leg mechanism can effectively act on the Micro-capsule endoscope, and is able to move effectively through the intestine. © 2023 IEEE.

关键词： Machine design

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Small-size temperature/high-pressure integrated sensor via flip-chip method

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Microsystems & Nanoengineering 2024年第4期10卷 153-162页

作者： Mimi Huang Xiaoyu Wu Libo Zhao Xiangguang Han Yong Xia Yi Gao Zeyu Cui Cheng Zhang Xiaokai Yang Zhixia Qiao Zhikang Li Feng Han Ping Yang Zhuangde Jiang State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong UniversityXi’an 710049China Xi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and System Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China School of Mechanical Engineering Xi’an Jiaotong University710049 Xi’anChina School of Instrument Science and Technology Xi’an Jiaotong University710049 Xi’anChina Chongqing Key Laboratory of Micro-Nano Systems and Intelligent Sensing Chongqing Academician WorkstationChongqing 2011 Collaborative Innovation Center of Micro/Nano Sensing and Intelligent Ecological Internet of ThingsChongqing Technology and Business UniversityNan’an DistrictChongqing 400067China Xi’an Aerospace Yuanzheng Fluid Control Co.Ltd. Xi’an 710049China

Hydraulic technology with smaller sizes and higher reliability trends,including fault prediction and intelligent control,requires high-performance temperature and pressure-integrated *** designs rely on planar wafer-or chip-level integration,which is limited by pressure range,chip size,and low *** propose a small-size temperature/high-pressure integrated sensor via the flip-chip *** pressure and temperature units are arranged vertically,and the sensing signals of the two units are integrated into one plane through silicon vias and gold–gold bonding,reducing the lateral size and improving the efficiency of signal *** flip-chip technique ensures a reliable electrical connection.A square diaphragm with rounded corners is designed and optimised with simulation to sense high pressure based on the piezoresistive *** temperature sensing unit with a thin-film platinum resistor measures temperature and provides back-end high-precision compensation,which will improve the precision of the pressure *** integrated chip is fabricated by MEMS technology and packaged to fabricate the extremely small integrated *** integrated sensor is characterised,and the pressure sensor exhibits a sensitivity and sensitivity drift of 7.97mV/MPa and−0.19%FS in the range of 0–20 MPa and−40 to 120℃.The linearity,hysteresis,repeatability,accuracy,basic error,and zero-time drift are 0.16%FS,0.04%FS,0.06%FS,0.18%FS,±0.23%FS and 0.04%FS,*** measurement error of the temperature sensor and temperature coefficient of resistance is less than±1°C and 3142.997 ppm/℃,*** integrated sensor has broad applicability in fault diagnosis and safety monitoring of high-end equipment such as automobile detection,industrial equipment,and oil drilling platforms.

关键词： size corners sizes

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Development of completion tool pressure test control system 10

Development of completion tool pressure test control system

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2023 10th International Conference on Advanced Manufacturing Technology and Materials engineering, AMTME 2023

作者： Sun, Zhiyu Zhao, Lianyu Wang, Chenglin Zhao, Xiaolei Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China Offshore Oil Engineering Co. Ltd. Tianjin300461 China

In oil exploitation, the completion tool is the key point to ensure the effective development of oil wells, and it must undergo strict pressure testing. Due to the high test pressure, there are potential safety hazards in the manual operation process. To improve safety and test efficiency, the automatic precision test system is developed. The detection system must realize the pressure detection process, provide feedback on the key data, give the corresponding curve reference, and generate the detection report. Through the PID algorithm, the precise control of the motor is realized. The system safety is guaranteed, and the detection accuracy is improved. The test results show that the completion tool pressure test control system can greatly improve detection efficiency. It can also fully reflect the entire detection process, accurately calculate some key parameters such as pressure drop, and obtain accurate results. The detection error is kept within 0.5%, ensuring the reliability of the detection process. © Published under licence by IOP Publishing Ltd.

关键词： control systems

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Bearing Fault Diagnosis Based on Multiple Feature Transfer Learning Network 11

Bearing Fault Diagnosis Based on Multiple Feature Transfer L...

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11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Qiao, Huanzhang Liu, Lida Tian, Xincheng Liu, Yan Center for Robotics School of Control Science and Engineering Shandong University Jinan250061 China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan250061 China Shandong Raone Technology Co. LTD Jinan250012 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

The intelligent fault diagnosis methods have gained great success, they usually depend on large amounts of labeled data. Unfortunately, it is a realistic problem to collected massive labeled data in actual industrial scene. In addition, even labeled data is easy to collect, the methods trained by these labeled data may not be able to classify unlabeled data obtained under different working states. Inspired by transfer learning, in the paper we propose a deep learning-based fault diagnosis method named multiple feature transfer learning network (MFTLN) to resolve the data distribution difference due to changed working conditions. MFTLN employee multiple extractors to get domain-invariant features and align source domain and target domain by maximum mean discrepancy (MMD) metric. We performed six bearing fault diagnosis transfer learning experiments to verify the superiority of the proposed method, the experimental results indicated that the recognition accuracy of the proposed method is obviously higher than those of the other 5 popular domain adaptive fault diagnosis methods when the target domain data is unlabeled. © 2022 IEEE.

关键词： Failure analysis

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