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深度学习
复杂时空约束下的多智能体运动规划 版权信息
- ISBN:9787121470110
- 条形码:9787121470110 ; 978-7-121-47011-0
- 装帧:平塑
- 册数:暂无
- 重量:暂无
- 所属分类:>>
复杂时空约束下的多智能体运动规划 本书特色
本书适合从事智能无人平台运动规划研究、开发的技术人员,以及相关专业的高校师生阅读参考。
复杂时空约束下的多智能体运动规划 内容简介
本书主要介绍了满足多个时空约束要求的多智能体运动规划技术,全书共8章:第1~2章阐述了运动规划的基本概念、相关技术,重点讲述了智能体多层次行为模型;第3~6章分别从不同角度对多智能体时空约束建模方法进行了讲解;第7章介绍了相关仿真应用案例;第8章对深度强化学习在运动规划中的应用进行了探索研究。 本书适合从事智能无人平台运动规划研究、开发的技术人员,以及相关专业的高校师生阅读参考。
复杂时空约束下的多智能体运动规划 目录
1.1 研究背景···························································································(1)
1.2 研究现状···························································································(1)
1.3 研究思路···························································································(8)
第2 章 运动规划中的智能体多层次行为模型框架设计·········································.(11)
2.1 环境建模方法··················································································.(11)
2.1.1 三角剖分法···········································································.(11)
2.1.2 可视图方法···········································································.(12)
2.1.3 Voronoi 图法··········································································.(12)
2.1.4 随机采样法···········································································.(13)
2.2 运动规划方法··················································································.(16)
2.2.1 全局运动规划········································································.(16)
2.2.2 局部运动规划········································································.(20)
2.3 智能体多层次行为模型设计································································.(23)
2.3.1 智能体介绍···········································································.(23)
2.3.2 现有智能体行为模型框架·························································.(24)
2.3.3 智能体多层次行为模型框架······················································.(27)
第3 章 基于多信息域、多分辨率场景描述模型的多层次运动规划算法研究··············.(31)
3.1 相关工作························································································.(31)
3.2 层次化运动规划算法总体思路·····························································.(34)
3.2.1 问题描述··············································································.(34)
3.2.2 总体思路··············································································.(35)
3.3 全局层次上的多样化引导路径生成·······················································.(36)
3.3.1 高层时空约束的表示·······························································.(36)
3.3.2 全局概率路径图的生成····························································.(38)
3.3.3 全局多样化引导路径的生成······················································.(39)
3.4 局部层次上的多样化运动路径生成·······················································.(41)
3.4.1 局部高分辨率概率路径图的生成················································.(41)
3.4.2 局部多样化运动路径的生成······················································.(42)
3.5 动态障碍情况下的运动路径重新规划问题··············································.(43)
3.5.1 运动路径的重新规划·······························································.(43)
3.5.2 概率路径图的动态更新····························································.(44)
3.6 仿真实验与结果分析·········································································.(45)
第4 章 多智能体避碰行为研究·······································································.(48)
4.1 相关工作························································································.(48)
4.2 避碰行为的基本概念与问题描述··························································.(50)
4.2.1 基本概念··············································································.(50)
4.2.2 问题描述··············································································.(51)
4.3 反应式避碰行为模型·········································································.(52)
4.4 基于*小代价原则的预测式避碰行为模型··············································.(57)
4.4.1 *小代价原则········································································.(57)
4.4.2 基于*小代价原则的预测式避碰行为建模····································.(58)
4.5 仿真实验与结果分析·········································································.(63)
第5 章 基于增广物理仿真的运动规划多任务约束建模分析与优化求解····················.(67)
5.1 相关工作························································································.(67)
5.2 问题描述························································································.(70)
5.3 控制围栏函数基础背景知识································································.(70)
5.4 基于控制围栏函数的多任务约5
复杂时空约束下的多智能体运动规划 作者简介
李石磊,海军工程大学信息安全系讲师、中国仿真学会仿真技术应用专业委员会委员。主要从事复杂系统建模与仿真、信息安全技术研究与教学,主持了国家自然科学基金青年项目“物理仿真虚拟人运动控制技术研究”、博士后基金项目“复杂动态场景多智能体运动规划技术”,参与了国家自然科学基金面上项目“数据和模型混合驱动的虚拟人群仿真及其在军事中的应用研究”等项目。
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