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摘要翻译：
我们提出了一种新的路径规划方法，称为“阿里阿德涅线索算法”。它被设计为在高维连续空间中寻找路径，并适用于静态和动态环境中的多自由度机器人--障碍物可能移动的环境。阿里阿德涅的线索算法包括两个子算法，称为搜索和探索，以交织的方式应用。Explore构建可访问空间的表示形式，而Search查找目标。这两个问题都作为优化问题提出。我们描述了该算法在动态环境中为一个六自由度手臂规划路径的实际实现，其中另一个六自由度手臂被用作移动障碍物。实验结果表明，该算法无需任何预处理，只需一秒钟就能找到一条路径。
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英文标题：
《The Ariadne's Clew Algorithm》
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作者：
J. M. Ahuactzin, P. Bessiere, E. Mazer
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最新提交年份：
2011
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
We present a new approach to path planning, called the "Ariadne's clew algorithm". It is designed to find paths in high-dimensional continuous spaces and applies to robots with many degrees of freedom in static, as well as dynamic environments - ones where obstacles may move. The Ariadne's clew algorithm comprises two sub-algorithms, called Search and Explore, applied in an interleaved manner. Explore builds a representation of the accessible space while Search looks for the target. Both are posed as optimization problems. We describe a real implementation of the algorithm to plan paths for a six degrees of freedom arm in a dynamic environment where another six degrees of freedom arm is used as a moving obstacle. Experimental results show that a path is found in about one second without any pre-processing.
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PDF链接：
https://arxiv.org/pdf/1105.5440
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