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Methodology for Path Planning and Optimization of Mobile Robots: A Review

机译:移动机器人路径规划和优化的方法论:综述

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Mobile robotics research is an emerging area since last three decades. The present research on mobile robotics addresses the problems which are mainly on path planning algorithm and optimization in static as well as dynamic environments. A detailed review has been made in the broad field of mobile robotic research especially focussing on the path planning strategy in various cluttered environments, their advantages and disadvantages of each of these strategies/methods have been highlighted. The path planning strategy of mobile robots can be categorised as Classical Methods and Heuristic Methods. Further subcategorized as (i) Analytical Methods, (ii) Enumerative Methods, (iii) Evolutionary Methods and (iv) Meta-Heuristic Methods. Each of these aforesaid methods has its own advantages and disadvantages. However, the main weakness arises from the fact that, analytical methods are too complex for intangible applications, whereas the enumerative methods are anxious by the extent of the search space. On the other hand, when search space is too large in path planning strategy, many evolutionary methods have been shown to be ineffective. To overcome these drawbacks, meta-heuristic methods have been fascinating considerably in this broad field of research. Many techniques are developed in path planning for mobile robot worldwide, however, the most commonly used techniques are presented here for further study.
机译:移动机器人技术研究是最近三十年来的一个新兴领域。当前关于移动机器人的研究解决了主要在静态和动态环境中的路径规划算法和优化问题。在移动机器人研究的广泛领域中进行了详细的审查,特别是在各种混乱环境中的路径规划策略上,这些策略/方法各自的优缺点都得到了强调。移动机器人的路径规划策略可以分为经典方法和启发式方法。进一步细分为(i)分析方法,(ii)枚举方法,(iii)进化方法和(iv)元启发式方法。这些上述方法中的每一种都有其自身的优点和缺点。但是,主要缺点来自于以下事实:对于无形应用而言,分析方法过于复杂,而枚举方法则对搜索空间的范围感到焦虑。另一方面,当路径规划策略中的搜索空间太大时,许多进化方法已被证明是无效的。为了克服这些缺点,在这种广泛的研究领域中,元启发式方法已经非常引人入胜。在全球范围内针对移动机器人的路径规划中开发了许多技术,但是,这里介绍了最常用的技术以供进一步研究。

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