检索结果-南通市图书馆

data-driven offline reinforcement learning approach for quadrotor's motion and path planning

Chinese Journal of Aeronautics 2024年第11期37卷 386-397页

作者： Haoran ZHAO Hang FU Fan YANG Che QU Yaoming ZHOU School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China Beijing Advanced Discipline Center for Unmanned Aircraft System Beihang UniversityBeijing 100191China Tianmushan Laboratory Hangzhou 311115China

Non-learning based motion and path planning of an Unmanned Aerial Vehicle(UAV)is faced with low computation efficiency,mapping memory occupation and local optimization *** article investigates the challenge of quadrotor control using offline reinforcement *** establishing a data-driven learning paradigm that operates without real-environment interaction,the proposed workflow offers a safer approach than traditional reinforcement learning,making it particularly suited for UAV control in industrial *** introduced algorithm evaluates dataset uncertainty and employs a pessimistic estimation to foster offline deep reinforcement *** highlight the algorithm's superiority over traditional online reinforcement learning methods,especially when learning from offline ***,the article emphasizes the importance of a more general behavior *** evaluations,the trained policy demonstrated versatility by adeptly navigating diverse obstacles,underscoring its real-world applicability.

关键词： Motion planning Unmanned aerial vehicle Reinforcement learning data-driven learning Markov decision process

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

data-driven rolling eco-speed optimization for autonomous vehicles

引用

Frontiers of Engineering Management 2024年第4期11卷 620-632页

作者： Ying YANG Kun GAO Shaohua CUI Yongjie XUE Arsalan NAJAFI Jelena ANDRIC School of Management Shanghai UniversityShanghai 200444China Department of Architecture and Civil Engineering Chalmers University of TechnologyGothenburg 41296Sweden School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Volvo Group Trucks Technology Gothenburg 40508Sweden

In urban settings,fluctuating traffic conditions and closely spaced signalized intersections lead to frequent emergency acceleration,deceleration,and idling in *** maneuvers contribute to elevated energy use and *** in vehicle-to-vehicle and vehicleto-infrastructure communication technologies allow autonomous vehicles(AVs)to perceive signals over long distances and coordinate with other vehicles,thereby mitigating environmentally harmful *** paper introduces a data-driven algorithm for rolling eco-speed optimization in AVs aimed at enhancing vehicle *** algorithm integrates a deep belief network with a back propagation neural network to formulate a traffic state perception mechanism for predicting feasible speed *** consumption data from the Argonne National Laboratory in the United States serves as the basis for establishing the quantitative correlation between the fuel consumption rate and speed.A spatiotemporal network is subsequently developed to achieve eco-speed optimization for AVs within the projected speed *** proposed algorithm results in a 12.2%reduction in energy consumption relative to standard driving practices,without a significant extension in travel time.

关键词： data-driven learning speed optimization autonomous vehicles energy saving

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：