动态智能体运动规划中PIO及其变体的研究进展

Muhammad Shafiq, Zain ANWAR ALI, Eman H. Alkhammash
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引用次数: 0

摘要

鸽子启发优化(Pigeon Inspired Optimization, PIO)算法由于其收敛速度快、效率高,与其他生物启发算法相比,越来越受到人们的欢迎。信鸽的导航能力被精确地运用到鸽类优化算法中,现有算法的不断进步使其更适合于各个领域的复杂优化问题。本文主要介绍了动态智能体运动规划技术中动态智能体运动规划的基本原理和技术进展。该调查还包括自其发展以来提出的工作的发现和局限性,以帮助世界各地的研究学者选择特定的算法,特别是运动规划。为了了解算法在未来研究中的重要性,本研究可能会扩展到基于应用的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Recent Trends of PIO and Its Variants Applied for Motion Planning of Dynamic Agents
Pigeon Inspired Optimization (PIO) algorithm is gaining popularity since its development due to faster convergence ability with great efficiencies when compared with other bio-inspired algorithms. The navigation capability of homing pigeons has been precisely used in Pigeon Inspired Optimization algorithm and continuous advancement in existing algorithms is making it more suitable for complex optimization problems in various fields. The main theme of this survey paper is to introduce the basics of PIO along with technical advancements of PIO for the motion planning techniques of dynamic agents. The survey also comprises of findings and limitations of proposed work since its development to help the research scholar around the world for particular algorithm selection especially for motion planning. This survey might be extended up to application based in order to understand the importance of algorithm in future studies.
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