IEEE Robotics Autom. Mag.最新文献_第2页

State Constrained Stochastic Optimal Control for Continuous and Hybrid Dynamical Systems Using DFBSDE 基于DFBSDE的连续和混合动力系统状态约束随机最优控制

IEEE Robotics Autom. Mag. Pub Date : 2023-05-11 DOI: 10.48550/arXiv.2305.06499

Bolun Dai, P. Krishnamurthy, A. Papanicolaou, F. Khorrami

引用次数: 4

Robustness of Dynamics in Games: A Contraction Mapping Decomposition Approach 游戏动态的鲁棒性:一种收缩映射分解方法

IEEE Robotics Autom. Mag. Pub Date : 2023-03-27 DOI: 10.48550/arXiv.2303.15386

Sina Arefizadeh, Sadegh Arefizadeh, S. Etesami, Sadegh Bolouki

{"title":"Robustness of Dynamics in Games: A Contraction Mapping Decomposition Approach","authors":"Sina Arefizadeh, Sadegh Arefizadeh, S. Etesami, Sadegh Bolouki","doi":"10.48550/arXiv.2303.15386","DOIUrl":"https://doi.org/10.48550/arXiv.2303.15386","url":null,"abstract":"A systematic framework for analyzing dynamical attributes of games has not been well-studied except for the special class of potential or near-potential games. In particular, the existing results have shortcomings in determining the asymptotic behavior of a given dynamic in a designated game. Although there is a large body literature on developing convergent dynamics to the Nash equilibrium (NE) of a game, in general, the asymptotic behavior of an underlying dynamic may not be even close to a NE. In this paper, we initiate a new direction towards game dynamics by studying the fundamental properties of the map of dynamics in games. To this aim, we first decompose the map of a given dynamic into contractive and non-contractive parts and then explore the asymptotic behavior of those dynamics using the proximity of such decomposition to contraction mappings. In particular, we analyze the non-contractive behavior for better/best response dynamics in discrete-action space sequential/repeated games and show that the non-contractive part of those dynamics is well-behaved in a certain sense. That allows us to estimate the asymptotic behavior of such dynamics using a neighborhood around the fixed point of their contractive part proxy. Finally, we demonstrate the practicality of our framework via an example from duopoly Cournot games.","PeriodicalId":13196,"journal":{"name":"IEEE Robotics Autom. Mag.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80403652","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

Kernel-based Regularized Iterative Learning Control of Repetitive Linear Time-varying Systems 重复线性时变系统的核正则化迭代学习控制

IEEE Robotics Autom. Mag. Pub Date : 2023-03-07 DOI: 10.48550/arXiv.2303.03822

Xian Yu, Xiaozhu Fang, Biqiang Mu, Tianshi Chen

{"title":"Kernel-based Regularized Iterative Learning Control of Repetitive Linear Time-varying Systems","authors":"Xian Yu, Xiaozhu Fang, Biqiang Mu, Tianshi Chen","doi":"10.48550/arXiv.2303.03822","DOIUrl":"https://doi.org/10.48550/arXiv.2303.03822","url":null,"abstract":"For data-driven iterative learning control (ILC) methods, both the model estimation and controller design problems are converted to parameter estimation problems for some chosen model structures. It is well-known that if the model order is not chosen carefully, models with either large variance or large bias would be resulted, which is one of the obstacles to further improve the modeling and tracking performances of data-driven ILC in practice. An emerging trend in the system identification community to deal with this issue is using regularization instead of the statistical tests, e.g., AIC, BIC, and one of the representatives is the so-called kernel-based regularization method (KRM). In this paper, we integrate KRM into data-driven ILC to handle a class of repetitive linear time-varying systems, and moreover, we show that the proposed method has ultimately bounded tracking error in the iteration domain. The numerical simulation results show that in contrast with the least squares method and some existing data-driven ILC methods, the proposed one can give faster convergence speed, better accuracy and robustness in terms of the tracking performance.","PeriodicalId":13196,"journal":{"name":"IEEE Robotics Autom. Mag.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82503101","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: 0

Ruminations on CES, Robotics, and the Future [President's Message] CES、机器人与未来的思考[总统致辞]

IEEE Robotics Autom. Mag. Pub Date : 2023-03-01 DOI: 10.1109/mra.2023.3237459

F. Park

引用次数: 0

RAS New Quadruped Robot Challenges: Pushing the Boundaries of Robotics Research and Development [Competitions] RAS新型四足机器人挑战赛:推动机器人研究与开发的边界

IEEE Robotics Autom. Mag. Pub Date : 2023-03-01 DOI: 10.1109/mra.2023.3238203

H. Moon

引用次数: 0

Enabling Homecare With Robotic Technologies [From the Guest Editors] 用机器人技术实现家庭护理[来自客座编辑]

IEEE Robotics Autom. Mag. Pub Date : 2023-03-01 DOI: 10.1109/mra.2023.3237439

W. Sheng, Hesheng Wang, Ying-Lung Lin, Y. Hirata, S. Mazzoleni