Robot Motion Planning: A Game-Theoretic Foundation
Robot Motion Planning: A Game-Theoretic Foundation
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DOI：
10.1007/s004539910020
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发表时间：
2000
期刊：
影响因子：
1.1
通讯作者：
Steven M. LaValle
中科院分区：
文献类型：
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作者：
Steven M. LaValle
基本路径规划的分析技术和算法在机器人、虚拟样机、计算机图形学和计算生物学等各种应用中变得非常有价值。然而，基本路径规划代表了机器人中经常遇到的一般运动规划问题的一个非常有限的版本。除了标准的几何工作空间约束外，许多问题可能涉及诸如传感和模型不确定性、非完整性、动力学、多个机器人和目标、最优性标准、不可预测性和非平稳性等复杂性。本文提出了一个统一的博弈论数学基础，在此基础上可以为这类更广泛的问题开发分析和算法，并受到使用统一的构型空间概念进行基本路径规划所获得的类似好处的启发。通过采用这种方法，获得了一种通用算法，用于计算广泛的运动规划问题的近似最优解，包括那些涉及传感和控制中的不确定性、环境不确定性和多机器人协调的问题。
Analysis techniques and algorithms for basic path planning have become quite valuable in a variety of applications such as robotics, virtual prototyping, computer graphics, and computational biology. Yet, basic path planning represents a very restricted version of general motion planning problems often encountered in robotics. Many problems can involve complications such as sensing and model uncertainties, nonholonomy, dynamics, multiple robots and goals, optimality criteria, unpredictability, and nonstationarity, in addition to standard geometric workspace constraints. This paper proposes a unified, game-theoretic mathematical foundation upon which analysis and algorithms can be developed for this broader class of problems, and is inspired by the similar benefits that were obtained by using unified configuration-space concepts for basic path planning. By taking this approach, a general algorithm has been obtained for computing approximate optimal solutions to a broad class of motion planning problems, including those involving uncertainty in sensing and control, environment uncertainties, and the coordination of multiple robots.