Pub Date : 2023-01-25DOI: 10.1146/annurev-control-061022-012035
Dong Wang, Jinqiang Wang, Zequn Shen, Chengru Jiang, J. Zou, Le Dong, N. Fang, G. Gu
Soft robotic systems are human friendly and can mimic the complex motions of animals, which introduces promising potential in various applications, ranging from novel actuation and wearable electronics to bioinspired robots operating in unstructured environments. Due to the use of soft materials, the traditional fabrication and manufacturing methods for rigid materials are unavailable for soft robots. 3D printing is a promising fabrication method for the multifunctional and multimaterial demands of soft robots, as it enables the personalization and customization of the materials and structures. This review provides perspectives on the manufacturing methods for various types of soft robotic systems and discusses the challenges and prospects of future research, including in-depth discussion of pneumatic, electrically activated, magnetically driven, and 4D-printed soft actuators and integrated soft actuators and sensors. Finally, the challenges of realizing multimaterial, multiscale, and multifunctional 3D-printed soft robots are discussed. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"Soft Actuators and Robots Enabled by Additive Manufacturing","authors":"Dong Wang, Jinqiang Wang, Zequn Shen, Chengru Jiang, J. Zou, Le Dong, N. Fang, G. Gu","doi":"10.1146/annurev-control-061022-012035","DOIUrl":"https://doi.org/10.1146/annurev-control-061022-012035","url":null,"abstract":"Soft robotic systems are human friendly and can mimic the complex motions of animals, which introduces promising potential in various applications, ranging from novel actuation and wearable electronics to bioinspired robots operating in unstructured environments. Due to the use of soft materials, the traditional fabrication and manufacturing methods for rigid materials are unavailable for soft robots. 3D printing is a promising fabrication method for the multifunctional and multimaterial demands of soft robots, as it enables the personalization and customization of the materials and structures. This review provides perspectives on the manufacturing methods for various types of soft robotic systems and discusses the challenges and prospects of future research, including in-depth discussion of pneumatic, electrically activated, magnetically driven, and 4D-printed soft actuators and integrated soft actuators and sensors. Finally, the challenges of realizing multimaterial, multiscale, and multifunctional 3D-printed soft robots are discussed. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"3 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2023-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82609500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1146/annurev-control-070122-102501
A. Kalinowska, P. Pilarski, T. Murphey
Early research on physical human–robot interaction (pHRI) has necessarily focused on device design—the creation of compliant and sensorized hardware, such as exoskeletons, prostheses, and robot arms, that enables people to safely come in contact with robotic systems and to communicate about their collaborative intent. As hardware capabilities have become sufficient for many applications, and as computing has become more powerful, algorithms that support fluent and expressive use of pHRI systems have begun to play a prominent role in determining the systems’ usefulness. In this review, we describe a selection of representative algorithmic approaches that regulate and interpret pHRI, describing the progression from algorithms based on physical analogies, such as admittance control, to computational methods based on higher-level reasoning, which take advantage of multimodal communication channels. Existing algorithmic approaches largely enable task-specific pHRI, but they do not generalize to versatile human–robot collaboration. Throughout the review and in our discussion of next steps, we therefore argue that emergent embodied dialogue—bidirectional, multimodal communication that can be learned through continuous interaction—is one of the next frontiers of pHRI. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"Embodied Communication: How Robots and People Communicate Through Physical Interaction","authors":"A. Kalinowska, P. Pilarski, T. Murphey","doi":"10.1146/annurev-control-070122-102501","DOIUrl":"https://doi.org/10.1146/annurev-control-070122-102501","url":null,"abstract":"Early research on physical human–robot interaction (pHRI) has necessarily focused on device design—the creation of compliant and sensorized hardware, such as exoskeletons, prostheses, and robot arms, that enables people to safely come in contact with robotic systems and to communicate about their collaborative intent. As hardware capabilities have become sufficient for many applications, and as computing has become more powerful, algorithms that support fluent and expressive use of pHRI systems have begun to play a prominent role in determining the systems’ usefulness. In this review, we describe a selection of representative algorithmic approaches that regulate and interpret pHRI, describing the progression from algorithms based on physical analogies, such as admittance control, to computational methods based on higher-level reasoning, which take advantage of multimodal communication channels. Existing algorithmic approaches largely enable task-specific pHRI, but they do not generalize to versatile human–robot collaboration. Throughout the review and in our discussion of next steps, we therefore argue that emergent embodied dialogue—bidirectional, multimodal communication that can be learned through continuous interaction—is one of the next frontiers of pHRI. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"109 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82936678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1146/annurev-control-042920-015119
A. Wills, Thomas Bo Schön
Sequential Monte Carlo methods—also known as particle filters—offer approximate solutions to filtering problems for nonlinear state-space systems. These filtering problems are notoriously difficult to solve in general due to a lack of closed-form expressions and challenging expectation integrals. The essential idea behind particle filters is to employ Monte Carlo integration techniques in order to ameliorate both of these challenges. This article presents an intuitive introduction to the main particle filter ideas and then unifies three commonly employed particle filtering algorithms. This unified approach relies on a nonstandard presentation of the particle filter, which has the advantage of highlighting precisely where the differences between these algorithms stem from. Some relevant extensions and successful application domains of the particle filter are also presented. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"Sequential Monte Carlo: A Unified Review","authors":"A. Wills, Thomas Bo Schön","doi":"10.1146/annurev-control-042920-015119","DOIUrl":"https://doi.org/10.1146/annurev-control-042920-015119","url":null,"abstract":"Sequential Monte Carlo methods—also known as particle filters—offer approximate solutions to filtering problems for nonlinear state-space systems. These filtering problems are notoriously difficult to solve in general due to a lack of closed-form expressions and challenging expectation integrals. The essential idea behind particle filters is to employ Monte Carlo integration techniques in order to ameliorate both of these challenges. This article presents an intuitive introduction to the main particle filter ideas and then unifies three commonly employed particle filtering algorithms. This unified approach relies on a nonstandard presentation of the particle filter, which has the advantage of highlighting precisely where the differences between these algorithms stem from. Some relevant extensions and successful application domains of the particle filter are also presented. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"47 4 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77951045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-06DOI: 10.1146/annurev-control-062922-090153
A. Annaswamy
This article provides an exposition of the field of adaptive control and its intersections with reinforcement learning. Adaptive control and reinforcement learning are two different methods that are both commonly employed for the control of uncertain systems. Historically, adaptive control has excelled at real-time control of systems with specific model structures through adaptive rules that learn the underlying parameters while providing strict guarantees on stability, asymptotic performance, and learning. Reinforcement learning methods are applicable to a broad class of systems and are able to produce near-optimal policies for highly complex control tasks. This is often enabled by significant offline training via simulation or the collection of large input-state datasets. This article attempts to compare adaptive control and reinforcement learning using a common framework. The problem statement in each field and highlights of their results are outlined. Two specific examples of dynamic systems are used to illustrate the details of the two methods, their advantages, and their deficiencies. The need for real-time control methods that leverage tools from both approaches is motivated through the lens of this common framework. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"Adaptive Control and Intersections with Reinforcement Learning","authors":"A. Annaswamy","doi":"10.1146/annurev-control-062922-090153","DOIUrl":"https://doi.org/10.1146/annurev-control-062922-090153","url":null,"abstract":"This article provides an exposition of the field of adaptive control and its intersections with reinforcement learning. Adaptive control and reinforcement learning are two different methods that are both commonly employed for the control of uncertain systems. Historically, adaptive control has excelled at real-time control of systems with specific model structures through adaptive rules that learn the underlying parameters while providing strict guarantees on stability, asymptotic performance, and learning. Reinforcement learning methods are applicable to a broad class of systems and are able to produce near-optimal policies for highly complex control tasks. This is often enabled by significant offline training via simulation or the collection of large input-state datasets. This article attempts to compare adaptive control and reinforcement learning using a common framework. The problem statement in each field and highlights of their results are outlined. Two specific examples of dynamic systems are used to illustrate the details of the two methods, their advantages, and their deficiencies. The need for real-time control methods that leverage tools from both approaches is motivated through the lens of this common framework. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"128 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80981736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-30DOI: 10.1146/annurev-control-062422-102559
A. Barbot, F. Ortiz, A. Bolopion, M. Gauthier, P. Lambert
Surface tension effects are known to be dominant at the submillimeter scale. Within this context, the literature has extensively described the underlying physics (e.g., surface tension, wetting, surface texturation, and coatings), and capillary forces have been exploited in a variety of applications (e.g., capillary picking, self-alignment, capillary sealing, and capillary bearings). As several stimuli can be used to control liquid menisci, these forces have been used mainly in microrobotics in open loop (i.e., without real-time feedback). However, at least two major sources of uncertainty hinder these forces from working properly in open loop: the variability due to contact-angle hysteresis (the difference between wetting and unwetting) and the variability in the involved volume of liquid. To be able to reject these disturbances, successful sensor integration and associated advanced control schemes need to be embedded in capillary microrobotic microsystems. This article analyzes research contributions in this field from three different perspectives: the stimulus action of the surface tension effect (light, B-field, etc.), the application field (actuation, picking, sealing, etc.), and the sensing and control schemes. Technologically complex developments coexist with elegant and straightforward engineering solutions. Biological aspects of surface tension are not included in this review. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"Exploiting Liquid Surface Tension in Microrobotics","authors":"A. Barbot, F. Ortiz, A. Bolopion, M. Gauthier, P. Lambert","doi":"10.1146/annurev-control-062422-102559","DOIUrl":"https://doi.org/10.1146/annurev-control-062422-102559","url":null,"abstract":"Surface tension effects are known to be dominant at the submillimeter scale. Within this context, the literature has extensively described the underlying physics (e.g., surface tension, wetting, surface texturation, and coatings), and capillary forces have been exploited in a variety of applications (e.g., capillary picking, self-alignment, capillary sealing, and capillary bearings). As several stimuli can be used to control liquid menisci, these forces have been used mainly in microrobotics in open loop (i.e., without real-time feedback). However, at least two major sources of uncertainty hinder these forces from working properly in open loop: the variability due to contact-angle hysteresis (the difference between wetting and unwetting) and the variability in the involved volume of liquid. To be able to reject these disturbances, successful sensor integration and associated advanced control schemes need to be embedded in capillary microrobotic microsystems. This article analyzes research contributions in this field from three different perspectives: the stimulus action of the surface tension effect (light, B-field, etc.), the application field (actuation, picking, sealing, etc.), and the sensing and control schemes. Technologically complex developments coexist with elegant and straightforward engineering solutions. Biological aspects of surface tension are not included in this review. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"89 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88106114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-28DOI: 10.1146/annurev-control-080122-090049
S. Parascho
Over the past decades, robotics has shown great potential to impact the built environment, from automation to differentiation and efficient construction. However, construction processes are highly complex and require tackling a multitude of problems, from safety and robustness to ease of control and interactivity. For this reason, the field of construction robotics is still evolving, requiring finding solutions for new challenges every day. The present review analyzes the role of robotics in construction and architecture over time and highlights current trends in shifting from pure automation toward collaborative and adaptive processes that have the potential to fully integrate robotics into a rigid and challenging industry, such as construction. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"Construction Robotics: From Automation to Collaboration","authors":"S. Parascho","doi":"10.1146/annurev-control-080122-090049","DOIUrl":"https://doi.org/10.1146/annurev-control-080122-090049","url":null,"abstract":"Over the past decades, robotics has shown great potential to impact the built environment, from automation to differentiation and efficient construction. However, construction processes are highly complex and require tackling a multitude of problems, from safety and robustness to ease of control and interactivity. For this reason, the field of construction robotics is still evolving, requiring finding solutions for new challenges every day. The present review analyzes the role of robotics in construction and architecture over time and highlights current trends in shifting from pure automation toward collaborative and adaptive processes that have the potential to fully integrate robotics into a rigid and challenging industry, such as construction. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"118 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72686611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-28DOI: 10.1146/annurev-control-062722-100728
Timothy H. Chung, Viktor L. Orekhov, Angela Maio
The Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge represented a multiyear (2018–2021), competition-based initiative to inspire and shape the future of field robotics, specifically in advancing integrated technologies for operating in complex underground environments. Bringing together robotics researchers and innovators from around the world to compete in physical and simulated contests, it spotlighted significant opportunities to incentivize and extract high-value technical results and insights to inform future advances. This article captures and quantifies these results, extracts relevant insights, and offers lessons learned and recommendations for further work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"Into the Robotic Depths: Analysis and Insights from the DARPA Subterranean Challenge","authors":"Timothy H. Chung, Viktor L. Orekhov, Angela Maio","doi":"10.1146/annurev-control-062722-100728","DOIUrl":"https://doi.org/10.1146/annurev-control-062722-100728","url":null,"abstract":"The Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge represented a multiyear (2018–2021), competition-based initiative to inspire and shape the future of field robotics, specifically in advancing integrated technologies for operating in complex underground environments. Bringing together robotics researchers and innovators from around the world to compete in physical and simulated contests, it spotlighted significant opportunities to incentivize and extract high-value technical results and insights to inform future advances. This article captures and quantifies these results, extracts relevant insights, and offers lessons learned and recommendations for further work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"13 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84640744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-18DOI: 10.1146/annurev-control-063022-094301
F. Iida, F. Giardina
Embodiment is a crucial concept for the autonomy and adaptivity of systems working in the physical world with high degrees of uncertainty and complexity. The physical bodies of autonomous adaptive systems heavily influence the information flow from the environment to the central processing (and vice versa), requiring us to consider the full triad of brain, body, and environment to investigate intelligent behavior. This article provides a structured review of embodied intelligence with a special emphasis on the concept of timescales and their role in self-organization and the emergence of complex behavior. We classify embodied interactions into three types—cross-timescale matching, separation, and nontemporal sequences—and discuss how these interactions were studied in the past as well as how they can contribute to the systematic investigation of complex autonomous and adaptive systems in both biological and artificial entities. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"On the Timescales of Embodied Intelligence for Autonomous Adaptive Systems","authors":"F. Iida, F. Giardina","doi":"10.1146/annurev-control-063022-094301","DOIUrl":"https://doi.org/10.1146/annurev-control-063022-094301","url":null,"abstract":"Embodiment is a crucial concept for the autonomy and adaptivity of systems working in the physical world with high degrees of uncertainty and complexity. The physical bodies of autonomous adaptive systems heavily influence the information flow from the environment to the central processing (and vice versa), requiring us to consider the full triad of brain, body, and environment to investigate intelligent behavior. This article provides a structured review of embodied intelligence with a special emphasis on the concept of timescales and their role in self-organization and the emergence of complex behavior. We classify embodied interactions into three types—cross-timescale matching, separation, and nontemporal sequences—and discuss how these interactions were studied in the past as well as how they can contribute to the systematic investigation of complex autonomous and adaptive systems in both biological and artificial entities. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"31 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88168185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-14DOI: 10.1146/annurev-control-062322-100607
O. Yasa, Yasunori Toshimitsu, M. Michelis, Lewis S. Jones, Miriam Filippi, T. Buchner, Robert K. Katzschmann
Soft robots’ flexibility and compliance give them the potential to outperform traditional rigid-bodied robots while performing multiple tasks in unexpectedly changing environments and conditions. However, soft robots have not yet revealed their full potential since nature is still far more advanced in several areas, such as locomotion and manipulation. To understand what limits their performance and hinders their transition from laboratory to real-world conditions, future studies should focus on understanding the principles behind the design and operation of soft robots. Such studies should also consider the major challenges with regard to complex materials, accurate modeling, advanced control, and intelligent behaviors. As a starting point for such studies, this review provides a current overview of the field by examining the working mechanisms of advanced actuation and sensing modalities, modeling techniques, control strategies, and learning architectures for soft robots. Next, we summarize how these approaches can be applied to create sophisticated soft robots and examine their application areas. Finally, we provide future perspectives on what key challenges should be tackled first to advance soft robotics to truly add value to our society. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"An Overview of Soft Robotics","authors":"O. Yasa, Yasunori Toshimitsu, M. Michelis, Lewis S. Jones, Miriam Filippi, T. Buchner, Robert K. Katzschmann","doi":"10.1146/annurev-control-062322-100607","DOIUrl":"https://doi.org/10.1146/annurev-control-062322-100607","url":null,"abstract":"Soft robots’ flexibility and compliance give them the potential to outperform traditional rigid-bodied robots while performing multiple tasks in unexpectedly changing environments and conditions. However, soft robots have not yet revealed their full potential since nature is still far more advanced in several areas, such as locomotion and manipulation. To understand what limits their performance and hinders their transition from laboratory to real-world conditions, future studies should focus on understanding the principles behind the design and operation of soft robots. Such studies should also consider the major challenges with regard to complex materials, accurate modeling, advanced control, and intelligent behaviors. As a starting point for such studies, this review provides a current overview of the field by examining the working mechanisms of advanced actuation and sensing modalities, modeling techniques, control strategies, and learning architectures for soft robots. Next, we summarize how these approaches can be applied to create sophisticated soft robots and examine their application areas. Finally, we provide future perspectives on what key challenges should be tackled first to advance soft robotics to truly add value to our society. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"34 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83726879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-02DOI: 10.1146/annurev-control-042820-010811
M. Franceschetti, M. J. Khojasteh, M. Win
Networked control systems, where feedback loops are closed over communication networks, arise in several domains, including smart energy grids, autonomous driving, unmanned aerial vehicles, and many industrial and robotic systems active in service, production, agriculture, and smart homes and cities. In these settings, the two main layers of the system, control and communication, strongly affect each other's performance, and they also reveal the interaction between a cyber-system component, represented by information-based computing and communication technologies, and a physical-system component, represented by the environment that needs to be controlled. The information access and distribution constraints required to achieve reliable state estimation and stabilization in networked control systems have been intensively studied over the course of roughly two decades. This article reviews some of the cornerstone results in this area, draws a map for what we have learned over these years, and describes the new challenges that we will face in the future. Rather than simply listing different results, we present them in a coherent fashion using a uniform notation, and we also put them in context, highlighting both their theoretical insights and their practical significance. Particular attention is given to recent developments related to decentralized estimation in distributed sensing and communication systems and the information-theoretic value of event timing in the context of networked control. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
{"title":"The Many Facets of Information in Networked Estimation and Control","authors":"M. Franceschetti, M. J. Khojasteh, M. Win","doi":"10.1146/annurev-control-042820-010811","DOIUrl":"https://doi.org/10.1146/annurev-control-042820-010811","url":null,"abstract":"Networked control systems, where feedback loops are closed over communication networks, arise in several domains, including smart energy grids, autonomous driving, unmanned aerial vehicles, and many industrial and robotic systems active in service, production, agriculture, and smart homes and cities. In these settings, the two main layers of the system, control and communication, strongly affect each other's performance, and they also reveal the interaction between a cyber-system component, represented by information-based computing and communication technologies, and a physical-system component, represented by the environment that needs to be controlled. The information access and distribution constraints required to achieve reliable state estimation and stabilization in networked control systems have been intensively studied over the course of roughly two decades. This article reviews some of the cornerstone results in this area, draws a map for what we have learned over these years, and describes the new challenges that we will face in the future. Rather than simply listing different results, we present them in a coherent fashion using a uniform notation, and we also put them in context, highlighting both their theoretical insights and their practical significance. Particular attention is given to recent developments related to decentralized estimation in distributed sensing and communication systems and the information-theoretic value of event timing in the context of networked control. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":"2 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80400891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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