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Mapping in Unknown Graph-Like Worlds

机译：未知图样世界中的映射

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We consider the problem of constructing a map of an unknown environment by an autonomous agent such as a mobile robot. Because accurate positional information is often difficult to ensure, we consider the problem of exploration in the absence of metric (positional) information. Worlds are represented by graphs (not necessarily planar) consisting of a fixed number of discrete places linked by bidirectional paths. We assume the robot can consistently enumerate the edges leaving a vertex (that is, it can assign a cyclic ordering). A mobile robot is assigned the task of creating a topological map, i.e. a graph-like representation of the places in the world and their connectivity, by moving from place to place along the paths it encounters. It can detect edges and count them, but cannot directly sense the labels associated with a place or an edge. In principle, this type of representation could be used for non-spatial environments such as computer networks. We present an approach to the exploration of unknown environments for which local sensing information alone is insufficient to distinguish distinct places, based simply on the structure of the world itself. Places are identified by a non-unique signature and by using a collection of such non-unique local signatures, an extended signature may be constructed that determines the robot's position (although in certain "degenerate" worlds additional information is required). We describe the "exploration tree" as a representation of a collection of alternative descriptions of the environment. In addition, heuristics are presented that can accelerate the search for the correct world model.
机译：我们考虑了由诸如移动机器人之类的自治代理构造未知环境的地图的问题。由于通常很难确保准确的位置信息，因此我们考虑在缺乏度量（位置）信息的情况下进行探索的问题。世界由由双向路径链接的固定数量的离散位置组成的图形（不一定是平面的）表示。我们假设机器人可以一致地枚举离开顶点的边（也就是说，它可以分配循环顺序）。移动机器人被分配创建拓扑图的任务，即通过沿其所遇到的路径在一个地方移动到另一个地方来创建世界上各个地方及其连接的图形表示。它可以检测边缘并对其进行计数，但不能直接感应与某个位置或边缘相关的标签。原则上，这种表示形式可用于非空间环境，例如计算机网络。我们提出了一种探索未知环境的方法，仅凭其本身的结构，仅凭本地感知信息不足以区分不同的地方。通过非唯一签名并通过使用此类非唯一本地签名的集合来标识位置，可以构造确定机器人位置的扩展签名（尽管在某些“简并”世界中需要附加信息）。我们将“探索树”描述为对环境的其他描述的集合的表示。此外，还提供了启发式方法，可以加快对正确世界模型的搜索。

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