On Onboard LiDAR-Based Flying Object Detection
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 Li...
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| Published in: | IEEE transactions on robotics Vol. 41; pp. 593 - 611 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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01.01.2025
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| ISSN: | 1552-3098, 1941-0468 |
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| 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 <inline-formula><tex-math notation="LaTeX">\text{20} \,\text{m}</tex-math></inline-formula>, our system is capable of reliably detecting a microscale UAV with an almost <inline-formula><tex-math notation="LaTeX">\text{100} \%</tex-math></inline-formula> recall, <inline-formula><tex-math notation="LaTeX">\text{0.2} \,\text{m}</tex-math></inline-formula> accuracy, and <inline-formula><tex-math notation="LaTeX">\text{20} \,\text{ms}</tex-math></inline-formula> delay. |
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| AbstractList | 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 <inline-formula><tex-math notation="LaTeX">\text{20} \,\text{m}</tex-math></inline-formula>, our system is capable of reliably detecting a microscale UAV with an almost <inline-formula><tex-math notation="LaTeX">\text{100} \%</tex-math></inline-formula> recall, <inline-formula><tex-math notation="LaTeX">\text{0.2} \,\text{m}</tex-math></inline-formula> accuracy, and <inline-formula><tex-math notation="LaTeX">\text{20} \,\text{ms}</tex-math></inline-formula> delay. |
| Author | Baca, Tomas Vrba, Matous Walter, Viktor Hert, Daniel Spurny, Vojtech Pritzl, Vaclav Pliska, Michal Saska, Martin |
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| SubjectTerms | Accuracy Aerial systems autonomous aerial interception Autonomous aerial vehicles Detectors Laser radar Location awareness multirobot systems object detection perception and autonomy Point cloud compression Robot sensing systems Robots segmentation and categorization Target tracking Three-dimensional displays |
| Title | On Onboard LiDAR-Based Flying Object Detection |
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