文章基本信息

标题：Exploration-Based Search for an Unknown Number of Targets using a UAV
本地全文：下载
作者：Bilal Yousuf ; Zsófa Lendek ; Lucian Buşoniu 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：15
页码：93-98
DOI：10.1016/j.ifacol.2022.07.614
语种：English
出版社：Elsevier
摘要：AbstractWe consider a scenario in which a UAV must locate an unknown number of targets at unknown locations in a 2D environment. A random finite set formulation with a particle filter is used to estimate the target locations from noisy measurements that may miss targets. A novel planning algorithm selects a next UAV state that maximizes an objective function consisting of two components: target refinement and an exploration. Found targets are saved and then disregarded from measurements to focus on refining poorly seen targets. The desired next state is used as a reference point for a nonlinear tracking controller for the robot. Simulation results show that the method works better than lawnmower and mutual-information baselines.
关键词：KeywordsMulti-target searchunmanned aerial vehicleprobability hypothesis density filterbackstepping control