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A Legged Small Celestial Body Landing Mechanism:Landing Simulation and Experimental Test

Space(Science & technology) 2023年第1期3卷 453-463页

作者： Zhijun Zhao Shuang Wu Jingdong Zhao Yaobing Wang Chuncheng Zhao Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications Beijing Institute of Spacecraft System EngineeringBeijing 100094China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150006China Department of Aerospace Science and Technology Polytechnic University of MilanMilan 20133Italy

Landing mechanism tends to rebound and turn over,and the stability time is long when landing on the small celestial *** landing performance in different conditions is necessary to be evaluated to guide the ***,landing performance evaluation is realized by *** factors affecting the landing performance including cardan element damping,foot anchors,retro-rocket thrust,landing slope angle,and landing attitude are analyzed.A microgravity platform is built to test the landing mechanism,and the consistency between the simulation and the experiment is *** the basis of simulation and experiment,some landing suggestions are proposed to improve the landing performance.

关键词： thrust mechanism landing

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The Autonomous Pipeline Navigation of a Cockroach Bio-Robot with Enhanced Walking Stimuli

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Cyborg and Bionic systems 2023年第1期4卷 47-55页

作者： Songsong Ma Yuansheng Chen Songlin Yang Shen Liu Lingqi Tang Bing Li Yao Li State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbinChina Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of TechnologyShenzhenChina School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhenChina The Biorobotics Institute Scuola Superiore Sant'AnnaPisaItaly

Tens of crawling bio-robots with cockroaches as the mobile platform have been developed with various *** with artificial crawling robots of the same size,they revealed better flexibility,larger payload,and stronger *** features made bio-robots ideal for pipeline inspection scenarios because the advancements in locomotion mechanisms and efficient power systems are still hurdles for current artificial *** this study,we controlled the bio-robot to crawl in the confined dark pipeline and achieved autonomous motion control with the help of an onboard sensing ***,a micro-camera was mounted on the electronic backpack of the cockroach for image collection,and an IMU sensor was used to compute its body *** electronic backpack transmitted images to the host computer for junction recognition and distance ***,the insect's habituation to electrical stimulation has long been an uncertain factor in the control of ***,a synergistic stimulation strategy was proposed to markedly reduce the habituation and increase the number of effective turning controls to over 100 *** is also found that both the increase of payload and the application of stimulations could promote the metabolic rate by monitoring carbon dioxide *** the integration of synergistic stimulation and autonomous control,we demonstrated the fully autonomous pipeline navigation with our cockroach bio-robot,which realized the cycle number of approximately 10 in a *** research provides a novel technology that has the potential for practical applications in the future.

关键词： robot artificial Robot

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Knowledge-Guided Evolutionary Optimization for Large-Scale Air Defense Resource Allocation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6267-6279页

作者： Li, Wenhua Wang, Rui Heng, Yong Zhang, Tao Wang, Ling National University of Defense Technology College of Systems Engineering Changsha410073 China Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha410073 China Xiangjiang Laboratory Changsha410073 China Beijing Institute of Electronic System Engineering Beijing100854 China Tsinghua University Department of Automation Beijing100084 China

In the high-stakes domain of air defense, resource allocation is a challenging optimization problem that involves many constraints and requires fast solutions. Previous work mainly addressed the single-intercept sensor-weapon-target assignment problem, which assigns missiles and radars to targets without optimizing the launch time. However, this problem can become large-scale and difficult to solve when saturation attack tactics are employed. Therefore, we propose a more realistic model that allows multiple missiles to intercept the same target and considers the launch time as a decision variable. We also incorporate radar relay guidance to maximize the interception probability and minimize the missile cost. To solve this model efficiently, we present a novel evolutionary algorithm with linear population size reduction (LPSR) and knowledge-guided strategies, called LKEA. Specifically, we design a heuristic method to quickly find the optimal launch time for each missile and a knowledge-guided strategy to use the radar channel collision information to guide the evolution. Experimental results show that LKEA is competitive in solving small/medium/large air defense resource allocation problems (ADRAPs). © 2020 IEEE.

关键词： Combinatorial optimization

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Dynamic Scheduling for Airport Special Vehicles Based on a Multi-strategy Hybrid Algorithm 41

Dynamic Scheduling for Airport Special Vehicles Based on a M...

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第41届中国控制会议

作者： Wei Quan Chen Chen Zhuang Shao Kai Meng School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

When arriving at the airport,flight needs to be served by special *** at the dynamic time window scheduling problem of airport refueling vehicles,this paper establishes a vehicle routing problem model with time window to minimize the operating ***,a multi-strategy genetic algorithm is designed to gain the solve time window scheduling problem,which employs the crossover based on particle swarm optimization to accelerate the early search capability,and the local search method based on simulated annealing to increase the local optimization *** aiming at dynamically adjusting vehicle routes on the basis of static scheduling,a local replanning strategy based on a dynamic time window is introduced,which uses the original route matching and rescheduling *** results show that the multi-strategy hybrid algorithm can effectively reduce the number of routes and vehicles the airport *** different scales' dynamic changes of time windows,the algorithm could enable vehicles to still meet time constraints and effectively minimize the change of routes.

关键词： vehicle scheduling multi-strategy genetic algorithm dynamic scheduling local replanning strategy

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A Regional Necessity Based Multi-agent Target Search Strategy for Post-earthquake Rescue 41

A Regional Necessity Based Multi-agent Target Search Strateg...

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第41届中国控制会议

作者： Xi Luo School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The damage caused by the earthquake is *** the purpose of post-earthquake rescue is to reduce *** it is necessary to improve the efficiency of rescue as much as *** paper focuses on multi-agent cooperative target search in the post-earthquake rescue and how to exploit the prior information of post-disaster building to improve the searching efficiency.A regional necessity based searching strategy is proposed which utilizes pre-disaster building information and adapts to dynamic ***,the target probability map is estimated according to the distribution information of pre-disaster ***,the regional necessity map is constructed by integrating the target probability map and the perception of the environment during the search ***,the search strategy is proposed based on the regional necessity map and the particle swarm optimization *** the gradient direction of regional necessity and local optimal velocity,the agent dynamically selects the search *** comparing with other search strategies in simulation experiments,the proposed strategy could shorten the searching time and improve the searching efficiency in the small and medium-scale task ***,the search strategy can adapt to the post-earthquake dynamic environment,which is confirmed by dynamic experiments.

关键词： multi-agent cooperative target search post-earthquake rescue regional necessity particle swarm optimization

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A Surrogate-Assisted Evolutionary Framework for Expensive Multitask Optimization Problems

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IEEE Transactions on Evolutionary Computation 2024年第3期29卷 1-1页

作者： Tan, Shenglian Wang, Yong Sun, Guangyong Pang, Tong Tang, Ke School of Automation Central South University Changsha China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha China Department of Computer Science and Engineering Guangdong Key Laboratory of Brain-Inspired Intelligent Computation Southern University of Science and Technology Shenzhen China

This paper proposes a surrogate-assisted evolutionary framework (called SELF) to solve expensive multitask optimization problems (ExMTOPs). SELF consists of two main phases: global knowledge transfer phase and local knowledge transfer phase. In the former, a multitask Gaussian process model (MTGP) is established by fusing previously evaluated solutions of multiple optimization tasks. MTGP can capture task-relevant information and the knowledge of landscapes. Then, differential evolution assisted with MTGP is proposed to preselect high-quality candidates. During the preselection, the knowledge of landscapes is transferred among multiple optimization tasks for locating promising regions quickly. In the latter, for each optimization task, Bayesian optimization is adopted to improve the quality of the best individual in the population. Moreover, the improved best individuals in the populations of multiple optimization tasks are adaptively transferred based on a transfer probability, which is computed through the task-relevant information provided by MTGP. By combining these two phases, SELF not only achieves the tradeoff between exploration and exploitation, but also utilizes the global and local knowledge transfer to improve the efficiency for solving ExMTOPs. We test SELF on seven benchmark test problems in the IEEE CEC2017 evolutionary multitask optimization competition. The results demonstrate that the performance of SELF is better than that of other seven advanced methods. In addition, we also apply SELF to deal with two real-world ExMTOPs. The designs provided by SELF exhibit the best performance among all the compared methods, verifying the potential of SELF in practical engineering applications. IEEE

关键词： Linear programming

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A joint sparse Bayesian learning for wideband DOA estimation

A joint sparse Bayesian learning for wideband DOA estimation

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2024 Conference on Spectral technology and Applications, CSTA 2024

作者： Zhao, Yonghong Liu, Jisong Wang, Junlong Dong, Shuxin Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Department of Automation and Information Engineering Xi'an University of Technology Shaanxi Xi'an710048 China

ISBN: (纸本)9781510683082

Wideband direction of arrival (DOA) estimation using sensor array is a noteworthy problem frequently occurring in many applications involving radar, sonar, and communication. We present a wideband DOA method based on a sparse Bayesian learning of multiple sub-bands jointly with the redundant dictionary matrix at the reference frequency. Explicitly enforcing the focusing operation and the singular value decomposition (SVD) to sensor measurements is motivated by a desire to decrease the computational complexity and storage capacity. A joint sparse Bayesian learning framework is proposed to deal with multiple sub-bands under one segment to obtain the DOA information. Moreover, the proposed method can be directly extended to multiple segments. Comparing to other wideband DOA estimation methods, the proposed method has the advantages of increased resolution, higher accuracy, and correlation of the sources, as well as not requiring the initial angles for the focusing matrix. Simulations are provided to show the effectiveness and improved performance of the proposed method. © 2024 SPIE.

关键词： Direction of arrival

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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Trajectory planning and base attitude restoration of dual-arm free-floating space robot by enhanced bidirectional approach

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Frontiers of Mechanical Engineering 2022年第1期17卷 2-17页

作者： Zongwu XIE Xiaoyu ZHAO Zainan JIANG Haitao YANG Chongyang LI State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Robotic System Department Jiangsu Jitri-Hust Intelligent Equipment TechnologyWuxi 214000China

When free-floating space robots perform space tasks,the satellite base attitude is disturbed by the dynamic *** disturbance of the base orientation may affect the communication between the space robot and the control center on *** this paper,the enhanced bidirectional approach is proposed to plan the manipulator trajectory and eliminate the final base attitude variation.A novel acceleration level state equation for the nonholonomic problem is proposed,and a new intermediate variable-based Lyapunov function is derived and solved for smooth joint trajectory and restorable base *** the method,the state equation is first proposed for dual-arm robots with and without end constraints,and the system stability is analyzed to obtain the system *** input modification further increases the system stability and simplifies the calculation *** are carried out in the end,and the proposed method is validated in minimizing final base attitude change and trajectory ***,the minute internal force during the coordinated operation and the considerable computing efficiency increases the feasibility of the method during space tasks.

关键词： free-floating space robot dual arm coordinated operation base attitude restoration bidirectional approach

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Automatic velocity picking based on optimal key points tracking algorithm

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Petroleum Science 2024年第2期21卷 903-917页

作者： Yong-Hao Wang Wen-Kai Lu Song-Bai Jin Yang Li Yu-Xuan Li Xiao-Feng Gu The Institute for Artificial Intelligence(THUAI) Tsinghua UniversityBeijing100084China State Key Laboratory of Intelligent Technology and Systems Tsinghua UniversityBeijing100084China Beijing National Research Center for Information Science and Technology(BNRist) Beijing100084China The Department of Automation Tsinghua UniversityBeijing100084China

Picking velocities from semblances manually is laborious and necessitates experience. Although various methods for automatic velocity picking have been developed, there remains a challenge in efficiently incorporating information from nearby gathers to ensure picked velocity aligns with seismic horizons while also improving picking accuracy. The conventional method of velocity picking from a semblance volume is computationally demanding, highlighting a need for a more efficient strategy. In this study, we introduce a novel method for automatic velocity picking based on multi-object tracking. This dynamic tracking process across different semblance panels can integrate information from nearby gathers effectively while maintaining computational efficiency. First, we employ accelerated density clustering on the velocity spectrum to discern cluster centers without the requirement for prior knowledge regarding the number of clusters. These cluster centers embody the maximum likelihood velocities of the main subsurface structures. Second, our proposed method tracks key points within the semblance volume. Kalman filter is adopted to adjust the tracking process, followed by interpolation on these tracked points to construct the final velocity model. Our synthetic data example demonstrates that our proposed algorithm can effectively rectify the picking errors of the clustering algorithm. We further compare the performances of the clustering method(CM), the proposed tracking method(TM), and the variational method(VM) on a field dataset from the Gulf of Mexico. The results attest that our method offers superior accuracy than CM, achieves comparable accuracy with VM, and benefits from a reduced computational cost.

关键词： Velocity picking Multi-object tracking Density clustering Kalman filter

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