Aerial Wilderness Search and Rescue with Ground Support. Kashino, Z., Nejat, G., & Benhabib, B. Journal of Intelligent & Robotic Systems, 99(1):147–163, July, 2020. ![Aerial Wilderness Search and Rescue with Ground Support [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 8 downloads Unmanned aerial vehicles (UAVs) have been proposed for a wide range of applications. Their use in wilderness search and rescue (WiSAR), in particular, has been investigated for fast search-area coverage from a high vantage point. The probability of success in such searches, however, can be further improved utilizing cooperative systems that employ both UAVs and unmanned ground vehicles (UGVs). In this paper, we present a new coordinated-search planning method, for collaborative UAV-UGV teams. The proposed method, particularly developed for WiSAR, considers the search area to be continuously growing and that the search is sparse. It is also assumed that targets detected by UAVs must be identified by a ground-level searcher. The UAV/UGV motion-planning method presented herein, therefore, has two major components: (i) coordinated search and (ii) joint target identification. The novelty of the proposed method lies in its use of (i) time-dependent target-location iso-probability curves, and (ii) an effective and efficient coordinated target-identification algorithm. The method has been validated via numerous simulated WiSAR searches for varying scenarios. Furthermore, extensive comparative experiments with other methods have shown that our method has higher rates of target detection and shorter search times, significantly outperforming alternative techniques by 75% – 255% in terms of target detection probability.
@article{kashino_aerial_2020,
title = {Aerial {Wilderness} {Search} and {Rescue} with {Ground} {Support}},
volume = {99},
issn = {1573-0409},
url = {https://doi.org/10.1007/s10846-019-01105-y},
doi = {10.1007/s10846-019-01105-y},
abstract = {Unmanned aerial vehicles (UAVs) have been proposed for a wide range of applications. Their use in wilderness search and rescue (WiSAR), in particular, has been investigated for fast search-area coverage from a high vantage point. The probability of success in such searches, however, can be further improved utilizing cooperative systems that employ both UAVs and unmanned ground vehicles (UGVs). In this paper, we present a new coordinated-search planning method, for collaborative UAV-UGV teams. The proposed method, particularly developed for WiSAR, considers the search area to be continuously growing and that the search is sparse. It is also assumed that targets detected by UAVs must be identified by a ground-level searcher. The UAV/UGV motion-planning method presented herein, therefore, has two major components: (i) coordinated search and (ii) joint target identification. The novelty of the proposed method lies in its use of (i) time-dependent target-location iso-probability curves, and (ii) an effective and efficient coordinated target-identification algorithm. The method has been validated via numerous simulated WiSAR searches for varying scenarios. Furthermore, extensive comparative experiments with other methods have shown that our method has higher rates of target detection and shorter search times, significantly outperforming alternative techniques by 75\% – 255\% in terms of target detection probability.},
language = {en},
number = {1},
urldate = {2020-08-26},
journal = {Journal of Intelligent \& Robotic Systems},
author = {Kashino, Zendai and Nejat, Goldie and Benhabib, Beno},
month = jul,
year = {2020},
keywords = {Autonomous mobile-target search, Iso-probability curves, UAV-UGV Cooperative search planning, Wilderness search and rescue},
pages = {147--163},
}
Downloads: 8
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