基于 Dhouib-Matrix-SPP 方法的认知型移动机器人智能路径规划

Souhail Dhouib
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引用次数: 0

摘要

移动机器人路径问题旨在为移动机器人找到从起点到目标点的最佳无碰撞最短路径。在本文中,环境被视为静态,并表示为双向网格图。此外,本文还采用了新颖的最优方法 Dhouib-Matrix-SPP (DM-SPP) 为移动机器人在静态环境中创建最优最短路径。DM-SPP 是一种基于距离矩阵列行导航的贪婪方法,其特点是能快速求解稀疏图。通过在 13 个测试案例中应用 DM-SPP 并将其结果与四种元启发式方法(最大最小蚂蚁系统、带惩罚措施的蚂蚁系统、A* 和改进的混合 A*)的结果进行比较分析。从不同场景获得的结果表明,拟议的 DM-SPP 方法可以迅速超越四种预定义的人工智能方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Intelligent path planning for cognitive mobile robot based on Dhouib-Matrix-SPP method

The Mobile Robot Path Problem looks to find the optimal shortest path from the starting point to the target point with collision-free for a mobile robot. This is a popular issue in robotics and in this paper the environment is considered as static and represented as a bidirectional grid map. Besides, the novel optimal method Dhouib-Matrix-SPP (DM-SPP) is applied to create the optimal shortest path for a mobile robot in a static environment. DM-SPP is a greedy method based on a column row navigation in the distance matrix and characterized by its rapidity to solve sparse graphs. The comparative analysis is conducted by applying DM-SPP on thirteen test cases and comparing its results to the results given by four metaheuristics the Max-Min Ant System, the Ant System with punitive measures, the A* and the Improved Hybrid A*. The outcomes acquired from different scenarios indicate that the proposed DM-SPP method can rapidly outperform the four predefined artificial intelligence methods.

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