Mobile robot navigation based on expected state value under uncertainty of self-localization
Mobile robot navigation based on expected state value under uncertainty of self-localization
复制标题
自定位不确定性下基于期望状态值的移动机器人导航
DOI：
10.1109/iros.2003.1250674
复制
发表时间：
2003
期刊：
影响因子：
--
通讯作者：
K. Umeda
中科院分区：
文献类型：
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作者：
R. Ueda;T. Arai;K. Asanuma;S. Kamiya;T. Kikuchi;K. Umeda
自定位的不确定性是自主移动机器人导航中最严重的问题之一。有一些研究处理这个问题。然而，他们中的大多数假设不确定性的程度是已知的或以前已经测量过的，尽管它很容易随着环境的一些微小变化而变化。为了避免这种假设，我们采取以下方法：1)机器人使用对感知噪声和环境变化具有相当鲁棒性的自定位方法；2)机器人行为计划基于机器人能够完美识别环境的假设；3)一种新的决策算法从规划结果和自定位结果实时计算适当的行为。在RoboCup四足机器人联赛的足球机器人上实现了这些算法，并通过实验验证了算法的有效性。
Uncertainty of self-localization is one of the most serious problems related to navigation of autonomous mobile robots. There are some studies that deal with this problem. However, most of them assume that the extent of the uncertainty is known or has been measured previously, though it changes easily with some trivial changes of the environment. To avoid this assumption, we take the following approach: 1) a robot uses a self- localization method that is quite robust against sensing noise and the environment change, 2) the plan for robot behavior is based on the assumption that the robot can recognize the environment perfectly, 3) a novel decision-making algorithm computes proper behavior from the planning result and self-localization results in real time. These algorithms were implemented on a soccer robot of the RoboCup four-legged robot league, and their efficiency was verified with experiments.