Toward a language-theoretic foundation for planning and filtering
Toward a language-theoretic foundation for planning and filtering
复制标题
为规划和过滤奠定语言理论基础
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
J. O’Kane
中科院分区：
文献类型：
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作者：
Fatemeh Zahra Saberifar;S. Ghasemlou;Dylan A. Shell;J. O’Kane
我们解决了使机器人硬件与其适当的软件协同设计自动化的算法问题。具体地说，我们考虑了机器人传感器和驱动组件的退化可能对该机器人完成其任务的能力产生的影响。我们引入了一种新的形式结构，它将包括多种形式的计划、计划问题和过滤器在内的各种众所周知的结构概括和合并成称为流程图的单一数据结构，并根据形式语言理论的思想给出了这些图结构的语义。我们描述了Prorustean图上的一组操作(语义保持和语义突变)，并展示了如何通过应用这些操作来回答一系列关于机器人硬件更改的破坏性的问题。我们还强调了这种新方法与现有研究线索之间的联系，包括组合过滤、Erdmann的策略复合体和混合自动机。
We address problems underlying the algorithmic question of automating the co-design of robot hardware in tandem with its apposite software. Specifically, we consider the impact that degradations of a robot’s sensor and actuation suites may have on the ability of that robot to complete its tasks. We introduce a new formal structure that generalizes and consolidates a variety of well-known structures including many forms of plans, planning problems, and filters, into a single data structure called a procrustean graph, and give these graph structures semantics in terms of ideas based in formal language theory. We describe a collection of operations on procrustean graphs (both semantics-preserving and semantics-mutating), and show how a family of questions about the destructiveness of a change to the robot hardware can be answered by applying these operations. We also highlight the connections between this new approach and existing threads of research, including combinatorial filtering, Erdmann’s strategy complexes, and hybrid automata.