Search and Rescue Rotary-Wing UAV and Its Application to the Lushan Ms 7.0 Earthquake

被引:92
|
作者
Qi, Juntong [1 ]
Song, Dalei [1 ]
Shang, Hong [2 ]
Wang, Nianfa [2 ]
Hua, Chunsheng [1 ]
Wu, Chong [1 ]
Qi, Xin [1 ]
Han, Jianda [1 ]
机构
[1] Chinese Acad Sci, State Key Lab Robot, Shenyang Inst Automat, 114 Nanta St, Shenyang 110016, Liaoning, Peoples R China
[2] China Earthquake Adm, China Int Search Rescue Team, Natl Earthquake Response Support Serv, 1 Yuquanxi St, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
AERIAL; MANAGEMENT;
D O I
10.1002/rob.21615
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Rapid search and rescue responses after earthquakes or in postseismic evaluation tend to be extremely difficult. To solve this problem, we summarized the requirements of search and rescue rotary-wing unmanned aerial vehicle (SR-RUAV) systems according to related works, manual earthquake search and rescue, and our knowledge to guide our research works. Based on these requirements, a series of research and technical works have been conducted to present an efficient SR-RUAV system. To help rescue teams locate interested areas quickly, a collapsed-building detecting approach that integrates low-altitude statistical image processing methods was proposed, which can increase survival rates by detecting collapsed buildings in a timely manner. The entire SR-RUAV system was illustrated by simulated earthquake response experiments in the China National Training Base for Search and Rescue (CNTBSR) from 2008 to 2010. On April 20, 2013, Lushan (China) experienced a disastrous earthquake (magnitude 7.0). Because of the distribution of buildings in the rural areas, it was impossible to implement a rapid search and postseismic evaluation via ground searching. We provided our SR-RUAV to the Chinese International Search and Rescue Team (CISAR) and accurately detected collapsed buildings for ground rescue guidance at low altitudes. This system was significantly improved with respect to its searching/planning strategy and vision-based evaluation in different environments based on the lessons learned from actual missions after the earthquake. The SR-RUAV has proved to be applicable and time saving. The physical structure, searching and planning strategy, image-processing algorithm, and improvements in real missions are described in detail in this study.
引用
收藏
页码:290 / 321
页数:32
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