Flight-Test Evaluation of Small Form-Factor LiDAR and Radar Sensors for sUAS Detect-and-Avoid Applications

被引:0
作者
de Haag, Maarten Uijt [1 ]
Bartone, Chris G. [1 ]
Braasch, Michael S. [1 ]
机构
[1] Ohio Univ, Athens, OH 45701 USA
来源
2016 IEEE/AIAA 35TH DIGITAL AVIONICS SYSTEMS CONFERENCE (DASC) | 2016年
关键词
component; unmanned aerial systems; detect-and-avoid; LIDAR; radar; seek and avoid; UAS; UAV; drone;
D O I
暂无
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Despite well over a decade of intensive research and development efforts, detect-and-avoid (DAA) technology remains in an immature state for medium and large unmanned aerial systems (UAS) and is in its very infancy for small UAS (sUAS). Routine Beyond Visual Line-of-Sight (BVLOS) operations will not be achieved until this technological impasse has been surpassed. Although a multi-system/multi-sensor approach is known to be the robust solution, sUAS platforms are challenged to host such an equipment suite in addition to their revenue-generating payload for commercial applications. Recent developments in small form-factor LiDAR and radar sensors may prove to be vital components in the overall DAA solution for sUAS. These types of sensors are being developed primarily for the autonomous ground vehicle market, but may be adapted for UAS applications. This paper documents a series of ground and flight tests conducted to evaluate the performance of both a small form-factor LiDAR and radar sensors. Obstacle detection range versus obstacle size is determined for both sensors in static and dynamic flight modes.
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页数:11
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