移动机器人路径规划的多目标优化算法综述

Baraa M. Abed, Wesam M. Jasim
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引用次数: 1

摘要

路径规划算法是机器人领域最重要的研究领域。路径规划(PP)可以定义为移动机器人在移动之前确定最合适的导航路径的过程。路径规划的优化是指找到最优或接近最优的路径。多目标优化(MOO)涉及寻找满足多个目标的最佳解值,如短、平滑和安全。mooo提出了在通过妥协(权衡)来平衡这些矛盾问题的同时做出决策的挑战。因此,没有单一的解决方案适用于MOO中的所有目的,而是有一系列的解决方案。本文的目的是概述移动机器人导航策略,用于寻找具有最少数量的标准(最短,平滑和最安全)的路径。在这里,详细讨论了多目标方法,以确定研究差距。此外,了解在各种环境条件下如何制定路径规划策略也很重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi Objective Optimization Algorithms for Mobile Robot Path Planning: A Survey
Path planning algorithms is the most significant area in the robotics field. Path Planning (PP) can be defined as the process of determining the most appropriate navigation path before a mobile robot moves. Optimization of path planning refers to finding the optimal or near-optimal path. Multi-objective optimization (MOO) is concerned with finding the best solution values that satisfy multiple objectives, such as shortness, smoothness, and safety. MOOs present the challenge of making decisions while balancing these contradictory issues through compromise (tradeoff). As a result, there is no single solution appropriate for all purposes in MOO, but rather a range of solutions. The purpose of this paper is to present an overview of mobile robot navigation strategies employed to find the path that has the minimum number of criteria (shortest, smoothness, and safest) so far. Here, multi objective approaches are discussed in detail in order to identify research gaps. In addition, it is important to understand how path planning strategies are developed under various environmental circumstances.
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