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Fuzzy dynamic localization for mobile robots

机译:移动机器人的模糊动态定位

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In this paper, we introduce a new fuzzy logic-based approach for dynamic localization of mobile robots equipped with a ring of sonar sensors. In this approach, the angular uncertainty and radial imprecision of sonar data are modeled by possibility distributions. From sonar data, a local fuzzy composite map is constructed and fitted to the given global map of the environment to identify robot's location. As a result of this fit, either a unique fuzzy location or multiple candidate fuzzy locations are obtained. To reduce the multiple candidate locations, the robot is moved to a new location and a new local fuzzy composite map is constructed. Then, a new set of candidate fuzzy locations is obtained. By considering the robot's movement, a set of hypothesized locations is identified from the old set of candidate locations. The hypothesized locations are matched with the new candidate locations and the candidates with low degree of match are eliminated. This process is continued until a unique location is obtained. The matching process is performed by using the fuzzy pattern matching technique. The proposed method is implemented on a Nomad 200 robot and the results are reported.
机译:在本文中,我们介绍了一种新的基于模糊逻辑的方法,该方法可以对配备了声纳传感器环的移动机器人进行动态定位。在这种方法中,声纳数据的角度不确定性和径向不精确性通过可能性分布来建模。根据声纳数据,可以构建局部模糊合成图,并将其拟合到给定的环境全局图上,以识别机器人的位置。作为这种拟合的结果,获得了唯一的模糊位置或多个候选模糊位置。为了减少多个候选位置,将机器人移至新位置并构建新的局部模糊合成图。然后,获得一组新的候选模糊位置。通过考虑机器人的运动,从旧的候选位置集合中识别出一组假设的位置。假定的位置与新的候选位置匹配,并且消除了匹配度低的候选。继续该过程,直到获得唯一的位置。通过使用模糊模式匹配技术来执行匹配过程。该方法在Nomad 200机器人上实现,并报告了结果。

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