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Sensor based navigation for car-like mobile robots using generalized Voronoi graph

机译:基于传感器的使用广义Voronoi图的汽车样移动机器人导航

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Our research objective is to realize sensor based navigation by car-like mobile robots. The generalized Voronoi graph (GVG) can describe a mobile robot's path for sensor based navigation from the point of view of completeness and safety. However, it is impossible to apply the path to a car-like mobile robot directly, because limitation of the minimum turning radius prevents following the non-smooth GVG. To solve the problem, we propose a local smooth path planning algorithm for car-like mobile robots. Basically, an initial path is generated by a conventional path planning algorithm using GVG theory, and it is deformed smoothly to enable car-like robots' following by maximizing an evaluation function proposed in the paper. The key topics are: definition of our evaluation function; and how to modify the GVG. We introduce a local smooth path planning algorithm based on the GVG, and explain a detail of the evaluation function. Simulation results support validity of the algorithm.
机译:我们的研究目标是通过汽车的移动机器人实现基于传感器的导航。广义Voronoi图(GVG)可以从完整性和安全性的角度来描述基于传感器的导航的移动机器人路径。然而,不可能直接将路径应用于汽车状移动机器人,因为在非平滑的GVG之后,最小转弯半径的限制阻止。为了解决问题,我们提出了一种用于汽车样移动机器人的本地平滑路径规划算法。基本上,使用GVG理论的传统路径规划算法产生初始路径,并且通过最大化纸张中提出的评估功能,使其变形以使汽车状机器人能够实现。关键主题是:我们的评估功能的定义;以及如何修改GVG。我们介绍了基于GVG的本地光滑路径规划算法,并解释了评估功能的细节。仿真结果支持算法的有效性。

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