Annu. Rev. Control. Robotics Auton. Syst.最新文献

Medical Robotics: Opportunities in China 医疗机器人:在中国的机会

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2022-05-03 DOI: 10.1146/annurev-control-061521-070251

Yao Guo, Weidong Chen, Jie Zhao, Guang-zhong Yang

引用次数: 5

Increasingly Intelligent Micromachines 日益智能化的微型机器

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2022-01-05 DOI: 10.1146/annurev-control-042920-013322

Tianyun Huang, Hongri Gu, B. Nelson

{"title":"Increasingly Intelligent Micromachines","authors":"Tianyun Huang, Hongri Gu, B. Nelson","doi":"10.1146/annurev-control-042920-013322","DOIUrl":"https://doi.org/10.1146/annurev-control-042920-013322","url":null,"abstract":"Intelligent micromachines, with dimensions ranging from a few millimeters down to hundreds of nanometers, are miniature systems capable of performing specific tasks autonomously at small scales. Enhancing the intelligence of micromachines to tackle the uncertainty and variability in complex microenvironments has applications in minimally invasive medicine, bioengineering, water cleaning, analytical chemistry, and more. Over the past decade, significant progress has been made in the construction of intelligent micromachines, evolving from simple micromachines to soft, compound, reconfigurable, encodable, multifunctional, and integrated micromachines, as well as from individual to multiagent, multiscale, hierarchical, self-organizing, and swarm micromachines. The field leverages two important trends in robotics research—the miniaturization and intelligentization of machines—but a compelling combination of these two features has yet to be realized. The core technologies required to make such tiny machines intelligent include information media, transduction, processing, exchange, and energy supply, but embedding all of these functions into a system at the micro- or nanoscale is challenging. This article offers a comprehensive introduction to the state-of-the-art technologies used to create intelligence for micromachines and provides insight into the construction of next-generation intelligent micromachines that can adapt to diverse scenarios for use in emerging fields. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":147293,"journal":{"name":"Annu. Rev. Control. Robotics Auton. Syst.","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116056331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Partially Observable Markov Decision Processes and Robotics 部分可观察马尔可夫决策过程与机器人

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2022-01-05 DOI: 10.1146/annurev-control-042920-092451

H. Kurniawati

{"title":"Partially Observable Markov Decision Processes and Robotics","authors":"H. Kurniawati","doi":"10.1146/annurev-control-042920-092451","DOIUrl":"https://doi.org/10.1146/annurev-control-042920-092451","url":null,"abstract":"Planning under uncertainty is critical to robotics. The partially observable Markov decision process (POMDP) is a mathematical framework for such planning problems. POMDPs are powerful because of their careful quantification of the nondeterministic effects of actions and the partial observability of the states. But for the same reason, they are notorious for their high computational complexity and have been deemed impractical for robotics. However, over the past two decades, the development of sampling-based approximate solvers has led to tremendous advances in POMDP-solving capabilities. Although these solvers do not generate the optimal solution, they can compute good POMDP solutions that significantly improve the robustness of robotics systems within reasonable computational resources, thereby making POMDPs practical for many realistic robotics problems. This article presents a review of POMDPs, emphasizing computational issues that have hindered their practicality in robotics and ideas in sampling-based solvers that have alleviated such difficulties, together with lessons learned from applying POMDPs to physical robots. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":147293,"journal":{"name":"Annu. Rev. Control. Robotics Auton. Syst.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125418494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 38

Turbulence and Control of Wind Farms 风电场的湍流与控制

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2021-12-06 DOI: 10.1146/annurev-control-070221-114032

C. Shapiro, Genevieve M. Starke, D. Gayme

{"title":"Turbulence and Control of Wind Farms","authors":"C. Shapiro, Genevieve M. Starke, D. Gayme","doi":"10.1146/annurev-control-070221-114032","DOIUrl":"https://doi.org/10.1146/annurev-control-070221-114032","url":null,"abstract":"The dynamics of the turbulent atmospheric boundary layer play a fundamental role in wind farm energy production, governing the velocity field that enters the farm as well as the turbulent mixing that regenerates energy for extraction at downstream rows. Understanding the dynamic interactions among turbines, wind farms, and the atmospheric boundary layer can therefore be beneficial in improving the efficiency of wind farm control approaches. Anticipated increases in the sizes of new wind farms to meet renewable energy targets will increase the importance of exploiting this understanding to advance wind farm control capabilities. This review discusses approaches for modeling and estimation of the wind farm flow field that have exploited such knowledge in closed-loop control, to varying degrees. We focus on power tracking as an example application that will be of critical importance as wind farms transition into their anticipated role as major suppliers of electricity. The discussion highlights the benefits of including the dynamics of the flow field in control and points to critical shortcomings of the current approaches. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":147293,"journal":{"name":"Annu. Rev. Control. Robotics Auton. Syst.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121038946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Magnetic Micro- and Nanoagents for Monitoring Enzymatic Activity In Vivo 监测体内酶活性的磁性微纳米试剂

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2021-12-06 DOI: 10.1146/annurev-control-042920-013605

M. G. Christiansen, Matej Vizovišek, S. Schuerle

{"title":"Magnetic Micro- and Nanoagents for Monitoring Enzymatic Activity In Vivo","authors":"M. G. Christiansen, Matej Vizovišek, S. Schuerle","doi":"10.1146/annurev-control-042920-013605","DOIUrl":"https://doi.org/10.1146/annurev-control-042920-013605","url":null,"abstract":"Enzymes are appealing diagnostic targets because of their centrality in human health and disease. Continuous efforts spanning several decades have yielded methods for magnetically detecting the interactions of enzymes with exogenous molecular substrates. Nevertheless, measuring enzymatic activity in vivo remains challenging due to background noise, insufficient selectivity, and overlapping enzymatic functions. Magnetic micro- and nanoagents are poised to help overcome these issues by offering possible advantages such as site-selective sampling, modular architectures, new forms of magnetic detection, and favorable biocompatibility. Here, we review relevant control and detection strategies and consider examples of magnetic enzyme detection demonstrated with micro- or nanorobotic systems. Most cases have focused on proteolytic enzymes, leaving ample opportunity to expand to other classes of enzymes. Enzyme-responsive magnetic micro- and nanoagents hold promise for lowering barriers of translation and enabling preemptive, point-of-care medical applications. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":147293,"journal":{"name":"Annu. Rev. Control. Robotics Auton. Syst.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130905246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Internal Models in Control, Bioengineering, and Neuroscience 控制、生物工程和神经科学中的内部模型

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2021-11-29 DOI: 10.1146/annurev-control-042920-102205

Michelangelo Bin, Jie Huang, A. Isidori, L. Marconi, M. Mischiati, Eduardo Sontag

引用次数: 15

Energy-Aware Controllability of Complex Networks 复杂网络的能量感知可控性

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2021-11-18 DOI: 10.1146/annurev-control-042920-014957

Giacomo Baggio, F. Pasqualetti, S. Zampieri

{"title":"Energy-Aware Controllability of Complex Networks","authors":"Giacomo Baggio, F. Pasqualetti, S. Zampieri","doi":"10.1146/annurev-control-042920-014957","DOIUrl":"https://doi.org/10.1146/annurev-control-042920-014957","url":null,"abstract":"Understanding the fundamental principles and limitations of controlling complex networks is of paramount importance across natural, social, and engineering sciences. The classic notion of controllability does not capture the effort needed to control dynamical networks, and quantitative measures of controllability have been proposed to remedy this problem. This article presents an introductory overview of the practical (i.e., energy-related) aspects of controlling networks governed by linear dynamics. First, we introduce a class of energy-aware controllability metrics and discuss their properties. Then, we establish bounds on these metrics, which allow us to understand how the structure of the network impacts the control energy. Finally, we examine the problem of optimally selecting a set of control nodes so as to minimize the control effort, and compare the performance of some simple strategies to approximately solve this problem. Throughout the article, we include examples of structured and random networks to illustrate our results. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":147293,"journal":{"name":"Annu. Rev. Control. Robotics Auton. Syst.","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132074809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Stimuli-Responsive Polymers for Soft Robotics 软机器人的刺激响应聚合物

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2021-11-17 DOI: 10.1146/annurev-control-042920-014327

Yusen Zhao, Mutian Hua, Yichen Yan, Shuwang Wu, Yousif Alsaid, Ximin He

引用次数: 15

Multirobot Control Strategies for Collective Transport 集运多机器人控制策略

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2021-11-10 DOI: 10.1146/annurev-control-042920-095844

Hamed Farivarnejad, S. Berman

{"title":"Multirobot Control Strategies for Collective Transport","authors":"Hamed Farivarnejad, S. Berman","doi":"10.1146/annurev-control-042920-095844","DOIUrl":"https://doi.org/10.1146/annurev-control-042920-095844","url":null,"abstract":"One potential application of multirobot systems is collective transport, a task in which multiple robots collaboratively move a payload that is too large or heavy for a single robot. In this review, we highlight a variety of control strategies for collective transport that have been developed over the past three decades. We characterize the problem scenarios that have been addressed in terms of the control objective, the robot platform and its interaction with the payload, and the robots’ capabilities and information about the payload and environment. We categorize the control strategies according to whether their sensing, computation, and communication functions are performed by a centralized supervisor or specialized robot or autonomously by the robots. We provide an overview of progress toward control strategies that can be implemented on robots with expanded autonomous functionality in uncertain environments using limited information, and we suggest directions for future work on developing such controllers. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":147293,"journal":{"name":"Annu. Rev. Control. Robotics Auton. Syst.","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123480732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Secure Networked Control Systems 安全网络控制系统

Annu. Rev. Control. Robotics Auton. Syst. Pub Date : 2021-11-10 DOI: 10.1146/annurev-control-072921-075953

H. Sandberg, V. Gupta, K. Johansson

{"title":"Secure Networked Control Systems","authors":"H. Sandberg, V. Gupta, K. Johansson","doi":"10.1146/annurev-control-072921-075953","DOIUrl":"https://doi.org/10.1146/annurev-control-072921-075953","url":null,"abstract":"Cyber-vulnerabilities are being exploited in a growing number of control systems. As many of these systems form the backbone of critical infrastructure and are becoming more automated and interconnected, it is of the utmost importance to develop methods that allow system designers and operators to do risk analysis and develop mitigation strategies. Over the last decade, great advances have been made in the control systems community to better understand cyber-threats and their potential impact. This article provides an overview of recent literature on secure networked control systems. Motivated by recent cyberattacks on the power grid, connected road vehicles, and process industries, a system model is introduced that covers many of the existing research studies on control system vulnerabilities. An attack space is introduced that illustrates how adversarial resources are allocated in some common attacks. The main part of the article describes three types of attacks: false data injection, replay, and denial-of-service attacks. Representative models and mathematical formulations of these attacks are given along with some proposed mitigation strategies. The focus is on linear discrete-time plant models, but various extensions are presented in the final section, which also mentions some interesting research problems for future work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":147293,"journal":{"name":"Annu. Rev. Control. Robotics Auton. Syst.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125230083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23