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13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Zhang, Yanchao Geng, Hao Liu, Bin Zhang, Yinlong Yuan, Xudong Zhang, Sichao School of Information Science and Engineering Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350361674

In order to solve the problems of long-term cumulative error and the absence of absolute pose in the existing Lidar-Inertial Measurement Unit (IMU) fusion methods for Automated Guided Vehicle (AGV) Simultaneous Localization and Mapping (SLAM), we propose a new SLAM method for mobile robot, integrating Lidar, IMU, and a downward vision camera. Firstly, we tightly couple Lidar-IMU and downward vision camera using a multimodal fusion framework. Downward visual measurements are integrated as QR factors into the factor graph, providing absolute pose information to correct cumulative error in the Lidar-IMU system and enable the joint pose estimation of the AGV. Secondly, an enhanced Iterative Closest Point (ICP) point cloud matching algorithm has been developed to correct the incorrect pose. This approach achieves Scan-to-Map alignment by employing a coarse-to-fine matching strategy, thereby enhancing the accuracy of point cloud alignment. Finally, the extended Kalman filter is used to optimize the Lidar pose drift, as well as the Lidar mapping effectively by using the Lidar-IMU as the measurements and the downward visual measurements as the updates. The algorithm has been extensively evaluated on the developed AGV experimental platform. The experimental results show that the position error is less than 0.02 meters and the orientation error is less than 1°, which solves the problems of long-term error accumulation and the lack of absolute pose information for AGV navigation. © 2024 IEEE.

关键词： Extended Kalman filters

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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IEEE International Conference on systems, Man and cybernetics

作者： Zibo Miao Yu Pan Qing Gao Guangdong Key Laboratory of Intelligent Morphing Mechanisms School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique.

关键词： Perturbation methods Design methodology Quantum optics Robustness Feedback control Closed loop systems Tuning cybernetics

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Robust and Efficient Trajectory Planning for Formation Flight in Dense Environments

arXiv

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arXiv 2022年

作者： Quan, Lun Yin, Longji Zhang, Tingrui Wang, Mingyang Wang, Ruilin Zhong, Sheng Zhou, Xin Cao, Yanjun Xu, Chao Gao, Fei The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Huzhou Institute Zhejiang University Huzhou313000 China

Formation flight has a vast potential for aerial robot swarms in various applications. However, existing methods lack the capability to achieve fully autonomous large-scale formation flight in dense environments. To bridge the gap, we present a complete formation flight system that effectively integrates real-world constraints into aerial formation navigation. This paper proposes a differentiable graph-based metric to quantify the overall similarity error between formations. This metric is invariant to rotation, translation, and scaling, providing more freedom for formation coordination. We design a distributed trajectory optimization framework that considers formation similarity, obstacle avoidance, and dynamic feasibility. The optimization is decoupled to make large-scale formation flights computationally feasible. To improve the elasticity of formation navigation in highly constrained scenes, we present a swarm reorganization method that adaptively adjusts the formation parameters and task assignments by generating local navigation goals. A novel swarm agreement strategy called global-remap-local-replan and a formation-level path planner is proposed in this work to coordinate the global planning and local trajectory optimizations. To validate the proposed method, we design comprehensive benchmarks and simulations with other cutting-edge works in terms of adaptability, predictability, elasticity, resilience, and efficiency. Finally, integrated with palm-sized swarm platforms with onboard computers and sensors, the proposed method demonstrates its efficiency and robustness by achieving the largest scale formation flight in dense outdoor environments. Copyright © 2022, The Authors. All rights reserved.

关键词： Antennas

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Certifiably Optimal Mutual Localization with Anonymous Bearing Measurements

arXiv

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arXiv 2022年

作者： Wang, Yingjian Wen, Xiangyong Yin, Longji Xu, Chao Cao, Yanjun Gao, Fei State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

Mutual localization is essential for coordination and cooperation in multi-robot systems. Previous works have tackled this problem by assuming available correspondences between measurements and received odometry estimations, which are difficult to acquire, especially for unified robot teams. Furthermore, most local optimization methods ask for initial guesses and are sensitive to their quality. In this paper, we present a certifiably optimal algorithm that uses only anonymous bearing measurements to formulate a novel mixed-integer quadratically constrained quadratic problem (MIQCQP). Then, we relax the original nonconvex problem into a semidefinite programming (SDP) problem and obtain a certifiably global optimum using with off-the-shelf solvers. As a result, our method can determine bearing-pose correspondences and furthermore recover the initial relative poses between robots under a certain condition. We compare the performance with local optimization methods on extensive simulations under different noise levels to show our advantage in global optimality and robustness. Real-world experiments are conducted to show the practicality and robustness. © 2022, CC BY.

关键词： Multipurpose robots

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Human-Robot Pose Tracking Based on CNN with Color and Geometry Aggregation 16th

Human-Robot Pose Tracking Based on CNN with Color and Geo...

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16th International Conference on Social Robotics, ICSR + InnoBiz 2024

作者： Xu, Yue Zhang, Yinlong Liu, Shuai Liu, Yuanhao Liang, Wei He, Hongsheng Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9789819611508

Accurately tracking the robotic arm and human joints is crucial to ensure safety during human-robot interaction. However, traditional pose tracking methods often exhibit insufficient performance and robustness in complex environments. The variations in the robotic arm’s environment and posture make it challenging for traditional methods to accurately capture the positions and posture of its joints. Specifically, when addressing challenges such as high similarity, occlusion, background complexity, and joint recognition failures, they often struggle to provide reliable and accurate results. To address these challenges, this paper proposes a human-robot pose tracking algorithm based on a new convolutional neural network model. To enhance detection accuracy, an improved color detection module is introduced to resolve joint misclassification. A geometric perception module is designed to accurately locate joints even under occlusion. Additionally, innovative iEMA and DBB modules are incorporated. The iEMA module employs edge detection technology to dynamically adjust thresholds for correct matching by improving the edge matching process. The DBB module refines the boundary box parameters for precise localization by introducing adaptive bounding box updates in real-time. This algorithm also integrates human pose recognition, enabling real-time pose recognition, thereby facilitating more intelligent and natural human-robot interaction. The algorithm has been rigorously evaluated on a custom-designed robotic arm platform. Experimental results validate the algorithm’s effectiveness and feasibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

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Real-time Whole-body Motion Planning for Mobile Manipulators Using Environment-adaptive Search and Spatial-temporal Optimization

Real-time Whole-body Motion Planning for Mobile Manipulators...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Chengkai Wu Ruilin Wang Mianzhi Song Fei Gao Jie Mei Boyu Zhou School of Artificial Intelligence Sun Yat-Sen University Zhuhai China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China State Key Laboratory of Industrail Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Mobile manipulators have recently gained significant attention in the robotics community due to their superior potential in industrial and service applications. However, the high degree of freedom associated with mobile manipulators poses challenges in achieving real-time whole-body motion planning. To bridge the gap, this paper presents a motion planning method capable of generating high-quality, safe, agile and feasible trajectories for mobile manipulators in real time. First, we present a novel environment-adaptive path searching method, which can generate paths in real-time in various environments by adaptively adjusting searching dimension based on environment complexity. Additionally, we propose a real-time spatial-temporal trajectory optimization method that takes into account the whole-body safety, agility and dynamic feasibility of mobile manipulators. Moreover, task constraints are applied to ensure that the trajectory can fulfill specific task requirements. Simulation and real-world experiments demonstrate that our method is capable of generating whole-body trajectories in real-time in challenging environments. We will release our code to benefit the community.

关键词： Service robots Dynamics Transportation Real-time systems Planning Safety Complexity theory

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An Isomerism Learning Model to Solve Time-Varying Problems Through Intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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Smart Contract Service Optimization in Blockchain-Cloud Collaborative Computing 24

Smart Contract Service Optimization in Blockchain-Cloud Coll...

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24th IEEE International Conference on Mobile Data Management, MDM 2023

作者： Wan, Ji Hu, Kai Li, Jie Su, Hao Wu, Qingshun Li, Mingyuan Feng, Libo Pan, Yan Beihang University State Key Laboratory of Software Development Environment Beijing China Beihang Yunnan Innovation Institute Yunnan Key Laboratory of Blockchain Application Technology Kunming China Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou China The First Affiliated Hospital of Zhengzhou University Zhengzhou China Yunnan University National Pilot School of Software Kunming China China Industrial Control Systems Cyber Emergency Response Team Institute of Software Beijing China

ISBN: (纸本)9798350341010

Smart contract is a trusted service provided on the blockchain, while cloud service is a traditional service mode with a large number of resources. The combination of the blockchain and cloud service is of great significance to the trusted expansion of services and the access to services inside and outside the blockchain. In this paper, we study the smart contract extension service in blockchain-cloud collaborative computing. The service module decoupling method of smart contract is proposed, and the parallel execution algorithm of smart contract service is designed, which improves the execution efficiency of smart contract service. Finally, this paper designs a secure data interaction method of smart contract and cloud service, which helps to maintain the data consistency between cloud computing and blockchain. The experimental results show that the proposed method can save at most 42.13% of the running time, and it can promote the data consistency between the cloud service and the blockchain. © 2023 IEEE.

关键词： Smart contract

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Spatial Sectorized Neural Network for 2-D DOA Estimation in the Full Azimuth

Spatial Sectorized Neural Network for 2-D DOA Estimation in ...

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European Signal Processing Conference (EUSIPCO)

作者： Feiyang Qian Hang Zheng Chengwei Zhou Zhiguo Shi State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China Jinhua Institute of Zhejiang University Jinhua China

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

Most existing deep learning-based direction-of- arrival (DOA) estimation methods are realized within a limited range of DOAs per training time, posing great challenges to effective DOA estimation in a full 3-D space of 360°. To address the problem, a spatial sectorized neural network is proposed for 2- D DOA estimation in the full azimuth. In particular, the full angular region is divided into a series of sectors to compress the ranges of both azimuth and elevation angles. Based on that, we formulate the full-azimuth DOA estimation problem into two tasks, namely, sector identification and angles mapping. To this end, the proposed network consists of a classifier and an estimator, thereby addressing the issue of angle discontinuity near the 0° and 360°. The estimated DOAs can be reconstructed from the outputs of the proposed network based on the angles mapping relationship, leading to an effective 2-D DOA estimation in the full azimuth. Our simulation results indicate that the proposed network outperforms the conventional model-based method and neural-network-based method in estimation accuracy.

关键词： Training Direction-of-arrival estimation Accuracy Azimuth Simulation Neural networks Estimation Europe Signal processing

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TTAGO-COUPLED-MULTIPLEX-DIGITAL-RPA-CRISPR/CAS12A FOR EGFR MUTATIONS DETECTION 26

TTAGO-COUPLED-MULTIPLEX-DIGITAL-RPA-CRISPR/CAS12A FOR EGFR M...

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26th International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Zhuang, Jianjian Xia, Liping Zou, Zheyu Yin, Juxin Mu, Ying Department of Clinical Pharmacology Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province Affiliated Hangzhou First People's Hospital Cancer Center Zhejiang University School of Medicine Hangzhou310006 China School of information and Electrical Engineering Zhejiang University City College Hangzhou China Research Centre for Analytical Instrumentation Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781733419048

Herein, Ttago-Coupled-Multiplex-digital-RPA-CRISPR/Cas12a (TCMDC) was proposed for the enrichment and multiplex detection of EGFR mutations. TCMDC realizes the fast enrichment of mutant nucleic acid templates by using Ttago to cut the wild-type template efficiently. The RPA-dual-crRNA Cas12a without need of PAM sequence realizes the universal one-tube RPA-Cas12a detection. Moreover, a multiplex digital PCR chip was developed and TCMDC was used to achieve absolute quantitative detection of multiplex EGFR mutations. As a mutation detection method, TCMDC not only has extremely high sensitivity (0.001%) and specificity, but also is very fast (1h), simple and convenient, which has versatility in point-of-care cancer diagnosis and precision medicine. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized systems for Chemistry and Life Sciences. All rights reserved.

关键词： Diagnosis

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