计算几何算法与移动机器人路径规划的交叉研究

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Algorithms Pub Date : 2023-10-27 DOI:10.3390/a16110498
Ehsan Latif, Ramviyas Parasuraman
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引用次数: 0

摘要

在计算几何(CG)的数学学科中,设计、分析和实施解决几何输入和输出问题的实用算法。它有时被用来指模式识别和定义实体建模方法来操纵曲线和曲面。CG是一个内容丰富的领域,涵盖了解决复杂优化问题的理论,如移动机器人系统的路径规划和扩展到分布式多机器人系统。本文简要讨论了CG的基本原理及其在解决单机器人和多机器人系统中众所周知的自动路径规划问题中的应用。我们还讨论了2021年CG- shop(计算几何:解决困难优化问题)竞赛中的三种获奖算法,以证明CG在多机器人系统中的实用性。我们还提到了CG和机器人交叉领域的一些开放问题。本文综述了CG在机器人技术中的潜在应用以及未来的研究方向。
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On the Intersection of Computational Geometry Algorithms with Mobile Robot Path Planning
In the mathematical discipline of computational geometry (CG), practical algorithms for resolving geometric input and output issues are designed, analyzed, and put into practice. It is sometimes used to refer to pattern recognition and to define the solid modeling methods for manipulating curves and surfaces. CG is a rich field encompassing theories to solve complex optimization problems, such as path planning for mobile robot systems and extension to distributed multi-robot systems. This brief review discusses the fundamentals of CG and its application in solving well-known automated path-planning problems in single- and multi-robot systems. We also discuss three winning algorithms from the CG-SHOP (Computational Geometry: Solving Hard Optimization Problems) 2021 competition to evidence the practicality of CG in multi-robotic systems. We also mention some open problems at the intersection of CG and robotics. This review provides insights into the potential use of CG in robotics and future research directions at their intersection.
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来源期刊
Algorithms
Algorithms Mathematics-Numerical Analysis
CiteScore
4.10
自引率
4.30%
发文量
394
审稿时长
11 weeks
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