自主智能系统(英文)最新文献_第6页

Machine learning techniques for robotic and autonomous inspection of mechanical systems and civil infrastructure 机械系统和民用基础设施的机器人和自主检测的机器学习技术

自主智能系统(英文) Pub Date : 2022-04-29 DOI: 10.1007/s43684-022-00025-3

Michael O. Macaulay, Mahmood Shafiee

{"title":"Machine learning techniques for robotic and autonomous inspection of mechanical systems and civil infrastructure","authors":"Michael O. Macaulay, Mahmood Shafiee","doi":"10.1007/s43684-022-00025-3","DOIUrl":"10.1007/s43684-022-00025-3","url":null,"abstract":"<div><p>Machine learning and in particular <i>deep learning</i> techniques have demonstrated the most efficacy in training, learning, analyzing, and modelling large complex structured and unstructured datasets. These techniques have recently been commonly deployed in different industries to support robotic and autonomous system (RAS) requirements and applications ranging from planning and navigation to machine vision and robot manipulation in complex environments. This paper reviews the state-of-the-art with regard to RAS technologies (including unmanned marine robot systems, unmanned ground robot systems, climbing and crawler robots, unmanned aerial vehicles, and space robot systems) and their application for the inspection and monitoring of mechanical systems and civil infrastructure. We explore various types of data provided by such systems and the analytical techniques being adopted to process and analyze these data. This paper provides a brief overview of machine learning and deep learning techniques, and more importantly, a classification of the literature which have reported the deployment of such techniques for RAS-based inspection and monitoring of utility pipelines, wind turbines, aircrafts, power lines, pressure vessels, bridges, etc. Our research provides documented information on the use of advanced data-driven technologies in the analysis of critical assets and examines the main challenges to the applications of such technologies in the industry.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-022-00025-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42816843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nash equilibrium seeking over directed graphs 有向图上的纳什均衡寻求

自主智能系统(英文) Pub Date : 2022-04-18 DOI: 10.1007/s43684-022-00026-2

Yutao Tang, Peng Yi, Yanqiong Zhang, Dawei Liu

引用次数: 0

Exponentially convergent distributed Nash equilibrium seeking for constrained aggregative games 约束聚合对策的指数收敛分布式纳什均衡寻求

自主智能系统(英文) Pub Date : 2022-04-12 DOI: 10.1007/s43684-022-00024-4

Shu Liang, Peng Yi, Yiguang Hong, Kaixiang Peng

引用次数: 0

Multi-agent reinforcement learning for cooperative lane changing of connected and autonomous vehicles in mixed traffic 混合交通中联网和自动驾驶车辆合作变道的多代理强化学习

自主智能系统(英文) Pub Date : 2022-03-16 DOI: 10.1007/s43684-022-00023-5

Wei Zhou, Dong Chen, Jun Yan, Zhaojian Li, Huilin Yin, Wanchen Ge

{"title":"Multi-agent reinforcement learning for cooperative lane changing of connected and autonomous vehicles in mixed traffic","authors":"Wei Zhou, Dong Chen, Jun Yan, Zhaojian Li, Huilin Yin, Wanchen Ge","doi":"10.1007/s43684-022-00023-5","DOIUrl":"10.1007/s43684-022-00023-5","url":null,"abstract":"<div><p>Autonomous driving has attracted significant research interests in the past two decades as it offers many potential benefits, including releasing drivers from exhausting driving and mitigating traffic congestion, among others. Despite promising progress, lane-changing remains a great challenge for autonomous vehicles (AV), especially in mixed and dynamic traffic scenarios. Recently, reinforcement learning (RL) has been widely explored for lane-changing decision makings in AVs with encouraging results demonstrated. However, the majority of those studies are focused on a single-vehicle setting, and lane-changing in the context of multiple AVs coexisting with human-driven vehicles (HDVs) have received scarce attention. In this paper, we formulate the lane-changing decision-making of multiple AVs in a mixed-traffic highway environment as a multi-agent reinforcement learning (MARL) problem, where each AV makes lane-changing decisions based on the motions of both neighboring AVs and HDVs. Specifically, a multi-agent advantage actor-critic (MA2C) method is proposed with a novel local reward design and a parameter sharing scheme. In particular, a multi-objective reward function is designed to incorporate fuel efficiency, driving comfort, and the safety of autonomous driving. A comprehensive experimental study is made that our proposed MARL framework consistently outperforms several state-of-the-art benchmarks in terms of efficiency, safety, and driver comfort.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-022-00023-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"52856324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

End-of-Life Decision making in circular economy using generalized colored stochastic Petri nets 广义有色随机Petri网在循环经济中的寿命终止决策

自主智能系统(英文) Pub Date : 2022-03-12 DOI: 10.1007/s43684-022-00022-6

Gautier Vanson, Pascale Marangé, Eric Levrat

{"title":"End-of-Life Decision making in circular economy using generalized colored stochastic Petri nets","authors":"Gautier Vanson, Pascale Marangé, Eric Levrat","doi":"10.1007/s43684-022-00022-6","DOIUrl":"10.1007/s43684-022-00022-6","url":null,"abstract":"<div><p>Circular economy enables to restore product value at the end of life i.e. when no longer used or damaged. Thus, the product life cycle is extended and this economy permits to reduce waste increase and resources rarefaction. There are several revaluation options (reuse, remanufacturing, recycling, …). So, decision makers need to assess these options to determine which is the best decision. Thus, we will present a study about an End-Of-Life (EoL) decision making which aims to facilitate the industrialization of circular economy. For this, it is essential to consider all variables and parameters impacting the decision of the product trajectory. A first part of the work proposes to identify the variables and parameters impacting the decision making. A second part proposes an assessment approach based on a modeling by Generalized Colored Stochastic Petri Net (GCSPN) and on a Monte-Carlo simulation. The approach developed is tested on an industrial example from the literature to analyze the efficiency and effectiveness of the model. This first application showed the feasibility of the approach, and also the limits of the GCSPN modelling.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-022-00022-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43164694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mass estimation method for intelligent vehicles based on fusion of machine learning and vehicle dynamic model 基于机器学习和车辆动态模型融合的智能车辆质量估计方法

自主智能系统(英文) Pub Date : 2022-03-11 DOI: 10.1007/s43684-022-00020-8

Zhuoping Yu, Xinchen Hou, Bo Leng, Yuyao Huang

{"title":"Mass estimation method for intelligent vehicles based on fusion of machine learning and vehicle dynamic model","authors":"Zhuoping Yu, Xinchen Hou, Bo Leng, Yuyao Huang","doi":"10.1007/s43684-022-00020-8","DOIUrl":"10.1007/s43684-022-00020-8","url":null,"abstract":"<div><p>Vehicle mass is an important parameter for motion control of intelligent vehicles, but is hard to directly measure using normal sensors. Therefore, accurate estimation of vehicle mass becomes crucial. In this paper, a vehicle mass estimation method based on fusion of machine learning and vehicle dynamic model is introduced. In machine learning method, a feedforward neural network (FFNN) is used to learn the relationship between vehicle mass and other state parameters, namely longitudinal speed and acceleration, driving or braking torque, and wheel angular speed. In dynamics-based method, recursive least square (RLS) with forgetting factor based on vehicle dynamic model is used to estimate the vehicle mass. According to the reliability of each method under different conditions, these two methods are fused using fuzzy logic. Simulation tests under New European Driving Cycle (NEDC) condition are carried out. The simulation results show that the estimation accuracy of the fusion method is around 97%, and that the fusion method performs better stability and robustness compared with each single method.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-022-00020-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47404510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An ontological modelling of multi-attribute criticality analysis to guide Prognostics and Health Management program development 多属性关键性分析的本体建模，以指导预后和健康管理项目的开发

自主智能系统(英文) Pub Date : 2022-03-02 DOI: 10.1007/s43684-022-00021-7

Adalberto Polenghi, Irene Roda, Marco Macchi, Alessandro Pozzetti

{"title":"An ontological modelling of multi-attribute criticality analysis to guide Prognostics and Health Management program development","authors":"Adalberto Polenghi, Irene Roda, Marco Macchi, Alessandro Pozzetti","doi":"10.1007/s43684-022-00021-7","DOIUrl":"10.1007/s43684-022-00021-7","url":null,"abstract":"<div><p>Digital technologies are becoming more pervasive and industrial companies are exploiting them to enhance the potentialities related to Prognostics and Health Management (PHM). Indeed, PHM allows to evaluate the health state of the physical assets as well as to predict their future behaviour. To be effective in developing PHM programs, the most critical assets should be identified so to direct modelling efforts. Several techniques could be adopted to evaluate asset criticality; in industrial practice, criticality analysis is amongst the most utilised. Despite the advancement of artificial intelligence for data analysis and predictions, the criticality analysis, which is built upon both quantitative and qualitative data, has not been improved accordingly. It is the goal of this work to propose an ontological formalisation of a multi-attribute criticality analysis in order to i) fix the semantics behind the terms involved in the analysis, ii) standardize and uniform the way criticality analysis is performed, and iii) take advantage of the reasoning capabilities to automatically evaluate asset criticality and associate a suitable maintenance strategy. The developed ontology, called MOCA, is tested in a food company featuring a global footprint. The application shows that MOCA can accomplish the prefixed goals; specifically, high priority assets towards which direct PHM programs are identified. In the long run, ontologies could serve as a unique knowledge base that integrate multiple data and information across facilities in a consistent way. As such, they will enable advanced analytics to take place, allowing to move towards cognitive Cyber Physical Systems that enhance business performance for companies spread worldwide.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-022-00021-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48152028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural network-based adaptive sliding mode control for underactuated dual overhead cranes suffering from matched and unmatched disturbances 基于神经网络的欠驱动双桥起重机匹配和非匹配扰动自适应滑模控制

自主智能系统(英文) Pub Date : 2022-01-07 DOI: 10.1007/s43684-021-00019-7

Tianci Wen, Yongchun Fang, Biao Lu

{"title":"Neural network-based adaptive sliding mode control for underactuated dual overhead cranes suffering from matched and unmatched disturbances","authors":"Tianci Wen, Yongchun Fang, Biao Lu","doi":"10.1007/s43684-021-00019-7","DOIUrl":"10.1007/s43684-021-00019-7","url":null,"abstract":"<div><p>To improve transportation capacity, dual overhead crane systems (DOCSs) are playing an increasingly important role in the transportation of large/heavy cargos and containers. Unfortunately, when trying to deal with the control problem, current methods fail to fully consider such factors as external disturbances, input dead zones, parameter uncertainties, and other unmodeled dynamics that DOCSs usually suffer from. As a result, dramatic degradation is caused in the control performance, which badly hinders the practical applications of DOCSs. Motivated by this fact, this paper designs a neural network-based adaptive sliding mode control (SMC) method for DOCS to solve the aforementioned issues, which achieves satisfactory control performance for both actuated and underactuated state variables, even in the presence of matched and mismatched disturbances. The asymptotic stability of the desired equilibrium point is proved with rigorous Lyapunov-based analysis. Finally, extensive hardware experimental results are collected to verify the efficiency and robustness of the proposed method.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-021-00019-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49006319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Task scheduling for transport and pick robots in logistics: a comparative study on constructive heuristics 物流中运输和拣选机器人的任务调度：构造启发式的比较研究

自主智能系统(英文) Pub Date : 2021-12-16 DOI: 10.1007/s43684-021-00017-9

Hanfu Wang, Weidong Chen

{"title":"Task scheduling for transport and pick robots in logistics: a comparative study on constructive heuristics","authors":"Hanfu Wang, Weidong Chen","doi":"10.1007/s43684-021-00017-9","DOIUrl":"10.1007/s43684-021-00017-9","url":null,"abstract":"<div><p>We study the Transport and Pick Robots Task Scheduling (TPS) problem, in which two teams of specialized robots, transport robots and pick robots, collaborate to execute multi-station order fulfillment tasks in logistic environments. The objective is to plan a collective time-extended task schedule with the minimization of makespan. However, for this recently formulated problem, it is still unclear how to obtain satisfying results efficiently. In this research, we design several constructive heuristics to solve this problem based on the introduced sequence models. Theoretically, we give time complexity analysis or feasibility guarantees of these heuristics; empirically, we evaluate the makespan performance criteria and computation time on designed dataset. Computational results demonstrate that coupled append heuristic works better for the most cases within reasonable computation time. Coupled heuristics work better than decoupled heuristics prominently on instances with relative few pick robot numbers and large work zones. The law of diminishing marginal utility is also observed concerning the overall system performance and different transport-pick robot numbers.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-021-00017-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41950817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hastily formed knowledge networks and distributed situation awareness for collaborative robotics 协作机器人快速形成的知识网络和分布式态势感知

自主智能系统(英文) Pub Date : 2021-12-07 DOI: 10.1007/s43684-021-00016-w

Patrick Doherty, Cyrille Berger, Piotr Rudol, Mariusz Wzorek

{"title":"Hastily formed knowledge networks and distributed situation awareness for collaborative robotics","authors":"Patrick Doherty, Cyrille Berger, Piotr Rudol, Mariusz Wzorek","doi":"10.1007/s43684-021-00016-w","DOIUrl":"10.1007/s43684-021-00016-w","url":null,"abstract":"<div><p>In the context of collaborative robotics, distributed situation awareness is essential for supporting collective intelligence in teams of robots and human agents where it can be used for both individual and collective decision support. This is particularly important in applications pertaining to emergency rescue and crisis management. During operational missions, data and knowledge are gathered incrementally and in different ways by heterogeneous robots and humans. We describe this as the creation of <i>Hastily Formed Knowledge Networks</i> (HFKNs). The focus of this paper is the specification and prototyping of a general distributed system architecture that supports the creation of HFKNs by teams of robots and humans. The information collected ranges from low-level sensor data to high-level semantic knowledge, the latter represented in part as RDF Graphs. The framework includes a synchronization protocol and associated algorithms that allow for the automatic distribution and sharing of data and knowledge between agents. This is done through the distributed synchronization of RDF Graphs shared between agents. High-level semantic queries specified in SPARQL can be used by robots and humans alike to acquire both knowledge and data content from team members. The system is empirically validated and complexity results of the proposed algorithms are provided. Additionally, a field robotics case study is described, where a 3D mapping mission has been executed using several UAVs in a collaborative emergency rescue scenario while using the full HFKN Framework.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-021-00016-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42332368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0