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
{"title":"移动机器人路径规划的多目标优化算法综述","authors":"Baraa M. Abed, Wesam M. Jasim","doi":"10.3991/ijoe.v18i15.34397","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi Objective Optimization Algorithms for Mobile Robot Path Planning: A Survey\",\"authors\":\"Baraa M. Abed, Wesam M. Jasim\",\"doi\":\"10.3991/ijoe.v18i15.34397\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":247144,\"journal\":{\"name\":\"Int. J. Online Biomed. Eng.\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Online Biomed. Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3991/ijoe.v18i15.34397\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Online Biomed. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/ijoe.v18i15.34397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Constructivist Computer-Based Instruction (CBI) Approach: A CBI Flipped Learning Integrated Problem Based and Case Method (PBL-cflip) in Clinical Refraction Course Automatically Avoiding Overfitting in Deep Neural Networks by Using Hyper-Parameters Optimization Methods Fiat lux et facta est lux: Leonardo Reveals the Secrets of the Heart and Arteries (in Health and Disease) Performance Analysis for 3D Reconstruction Objects in Meshroom and Agisoft - A Comparative Study Gray Level Co-Occurrence Matrices and Support Vector Machine for Improved Lung Cancer Detection
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1