{"title":"On Onboard LiDAR-Based Flying Object Detection","authors":"Matouš Vrba;Viktor Walter;Václav Pritzl;Michal Pliska;Tomáš Báča;Vojtěch Spurný;Daniel Heřt;Martin Saska","doi":"10.1109/TRO.2024.3502494","DOIUrl":null,"url":null,"abstract":"A new robust and accurate approach for the detection and localization of flying objects with the purpose of highly dynamic aerial interception and agile multirobot interaction is presented in this article. The approach is proposed for use on board of autonomous aerial vehicles equipped with a 3-D LiDAR sensor. It relies on a novel 3-D occupancy voxel mapping method for the target detection that provides high localization accuracy and robustness with respect to varying environments and appearance changes of the target. In combination with a proposed cluster-based multitarget tracker, sporadic false positives are suppressed, state estimation of the target is provided, and the detection latency is negligible. This makes the system suitable for tasks of agile multirobot interaction, such as autonomous aerial interception or formation control where fast, precise, and robust relative localization of other robots is crucial. We evaluate the viability and performance of the system in simulated and real-world experiments which demonstrate that at a range of \n<inline-formula><tex-math>$\\text{20} \\,\\text{m}$</tex-math></inline-formula>\n, our system is capable of reliably detecting a microscale UAV with an almost \n<inline-formula><tex-math>$\\text{100} \\%$</tex-math></inline-formula>\n recall, \n<inline-formula><tex-math>$\\text{0.2} \\,\\text{m}$</tex-math></inline-formula>\n accuracy, and \n<inline-formula><tex-math>$\\text{20} \\,\\text{ms}$</tex-math></inline-formula>\n delay.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"593-611"},"PeriodicalIF":10.5000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Robotics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10758263/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
A new robust and accurate approach for the detection and localization of flying objects with the purpose of highly dynamic aerial interception and agile multirobot interaction is presented in this article. The approach is proposed for use on board of autonomous aerial vehicles equipped with a 3-D LiDAR sensor. It relies on a novel 3-D occupancy voxel mapping method for the target detection that provides high localization accuracy and robustness with respect to varying environments and appearance changes of the target. In combination with a proposed cluster-based multitarget tracker, sporadic false positives are suppressed, state estimation of the target is provided, and the detection latency is negligible. This makes the system suitable for tasks of agile multirobot interaction, such as autonomous aerial interception or formation control where fast, precise, and robust relative localization of other robots is crucial. We evaluate the viability and performance of the system in simulated and real-world experiments which demonstrate that at a range of
$\text{20} \,\text{m}$
, our system is capable of reliably detecting a microscale UAV with an almost
$\text{100} \%$
recall,
$\text{0.2} \,\text{m}$
accuracy, and
$\text{20} \,\text{ms}$
delay.
期刊介绍:
The IEEE Transactions on Robotics (T-RO) is dedicated to publishing fundamental papers covering all facets of robotics, drawing on interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and beyond. From industrial applications to service and personal assistants, surgical operations to space, underwater, and remote exploration, robots and intelligent machines play pivotal roles across various domains, including entertainment, safety, search and rescue, military applications, agriculture, and intelligent vehicles.
Special emphasis is placed on intelligent machines and systems designed for unstructured environments, where a significant portion of the environment remains unknown and beyond direct sensing or control.