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Effects of heuristics in path planning for mobile robots in uncertain and dynamic environments

机译:在不确定和动态环境中移动机器人路径规划中启发式的影响

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In this work, several heuristics are proposed to assess their effects in path planning for mobile robots in uncertain and dynamic environments. Path planning for mobile robots is a widely used technique where an optimal collision-free path is searched through an environment. It is one of the most important primitives in robotics and is considered to be a hard problem. Since environments may contain static as well as dynamic obstacles, the optimal path must be collision-free. The situation becomes complicated for mobile robots when an environment consists of dynamic obstacles with random velocities and arbitrary directions. Though there have been a lot of research in static environments, concentration given on uncertain and dynamic environments is a few. Our goal is to find a path in such uncertain and dynamic environments considering simulation time and travel-distance. In order to analyze the robustness of our proposed heuristics, we plugged each of these heuristics in several search algorithms. We also compared the performances of these algorithms. Finally, this paper analyzes the effects of the proposed heuristics in path planning in uncertain and dynamic environments which are usual real-word scenarios for mobile robots.
机译:在这项工作中,提出了几种启发式机构来评估其在不确定和动态环境中的移动机器人的路径规划中的影响。移动机器人的路径规划是一种广泛使用的技术,其中通过环境搜索了最佳的防撞路径。它是机器人中最重要的原语之一,被认为是一个难题。由于环境可能包含静态以及动态障碍物,因此必须无需碰撞。当环境包括随机速度和任意方向的动态障碍物组成时,这种情况变得复杂。虽然在静态环境中有很多研究,但在不确定和动态环境中给出的集中是少数。我们的目标是在考虑模拟时间和旅行距离的这种不确定和动态环境中找到一条路径。为了分析我们拟议启发式的稳健性,我们将这些启发式中的每一个都在几个搜索算法中插入。我们还比较了这些算法的性能。最后,本文分析了拟议启发式在路径规划中的效果,这是移动机器人通常的实际字段的不确定和动态环境。

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