A ROS-based hybrid algorithm for the UAV path planning problem

运动规划 计算机科学 路径(计算) 障碍物 平面图(考古学) 机器人 算法 范围(计算机科学) A*搜索算法 职位(财务) 混合算法(约束满足) 实时计算 模拟 人工智能 约束满足 考古 财务 概率逻辑 政治学 法学 经济 历史 程序设计语言 约束逻辑程序设计
作者
Demet Canpolat Tosun,Yasemin Işık
出处
期刊:Aircraft Engineering and Aerospace Technology [Emerald (MCB UP)]
卷期号:95 (5): 784-798 被引量:8
标识
DOI:10.1108/aeat-04-2022-0102
摘要

Purpose It is possible with classical path planning algorithms to plan a path in a static environment if the instant position of the vehicle is known and the target and obstacle positions are constant. In a dynamic case, these methods used for the static environment are insufficient. The purpose of this study is to find a new method that can provide a solution to the four-rotor unmanned aerial vehicle (UAV) path planning problem in static and dynamic environments. Design/methodology/approach As a solution to the problem within the scope of this study, there is a new hybrid method in which the global A* algorithm and local the VFH+ algorithm are combined. Findings The performance of the designed algorithm was tested in different environments using the Gazebo model of a real quadrotor and the robot operating system (ROS), which is the widely used platform for robotic applications. Navigation stacks developed for mobile robots on the ROS platform were also used for the UAV, and performance benchmarks were carried out. From the proposed hybrid algorithm, remarkable results were obtained in terms of both planning and implementation time compared to ROS navigation stacks. Originality/value This study proposes a new hybrid approach to the path planning problem for UAVs operating in both static and dynamic environments.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
xixi发布了新的文献求助10
1秒前
1秒前
1秒前
曲江离发布了新的文献求助10
1秒前
火力全开完成签到,获得积分10
1秒前
林云夕发布了新的文献求助10
2秒前
九九发布了新的文献求助10
2秒前
刘凤莲关注了科研通微信公众号
2秒前
weven完成签到,获得积分10
3秒前
宿雨完成签到,获得积分10
3秒前
3秒前
4秒前
泯珉发布了新的文献求助10
4秒前
Hello应助哈哈镜阿姐采纳,获得10
4秒前
满意语芙发布了新的文献求助10
5秒前
5秒前
6秒前
6秒前
塔木完成签到,获得积分10
6秒前
宿雨发布了新的文献求助10
6秒前
6秒前
幸运的元元完成签到,获得积分10
6秒前
zoe发布了新的文献求助10
7秒前
JJFly发布了新的文献求助10
7秒前
7秒前
wanci应助Orange采纳,获得10
7秒前
8秒前
量子星尘发布了新的文献求助10
8秒前
8秒前
ChenLan完成签到,获得积分20
9秒前
香菜丸子发布了新的文献求助10
9秒前
shi完成签到,获得积分20
9秒前
myc641完成签到 ,获得积分10
9秒前
9秒前
zhscu完成签到,获得积分10
9秒前
weven发布了新的文献求助10
9秒前
9秒前
10秒前
LiuQianyi完成签到 ,获得积分10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to strong mixing conditions volume 1-3 5000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5719182
求助须知:如何正确求助?哪些是违规求助? 5255402
关于积分的说明 15287996
捐赠科研通 4869073
什么是DOI,文献DOI怎么找? 2614641
邀请新用户注册赠送积分活动 1564561
关于科研通互助平台的介绍 1521851