TY - GEN
T1 - Evaluation of ORB-SLAM based Stereo Vision for the Aircraft Landing Status Detection
AU - Peng, Chao Chung
AU - He, Rong
AU - Chuang, Chin Sheng
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by the Ministry of Science and Technology under Grant No. MOST 110-2221-E-006-095 and MOST 111-2923-E-006-004-MY3.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - When encountering emergency conditions, the pilot may lose the help from the modern navigation systems and be forced to perceive the surrounding environment only through vision, which means the safety of manual landing depends heavily on human factors. To provide the pilot with additional information about the status of the aircraft, helping increase the safety during the landing procedure, ORB-SLAM2, a state-of-the-art SLAM algorithm, is used in this paper to estimate the 6DoF localization of the aircraft. To evaluate the performance for aircraft landing, this work used Unreal Engine to generate the simulation runway scene with built-in stereo cameras. The results show that for the landing scenario, ORB-SLAM2 can provide the pilot with an alarm message when the descending speed or the glide angle of the aircraft is inappropriate. Also, as a lightweight, real-time, and stand-alone features, ORB-SLAM2 could be easily applied to other smart and capability-limited unmanned aerial vehicles.
AB - When encountering emergency conditions, the pilot may lose the help from the modern navigation systems and be forced to perceive the surrounding environment only through vision, which means the safety of manual landing depends heavily on human factors. To provide the pilot with additional information about the status of the aircraft, helping increase the safety during the landing procedure, ORB-SLAM2, a state-of-the-art SLAM algorithm, is used in this paper to estimate the 6DoF localization of the aircraft. To evaluate the performance for aircraft landing, this work used Unreal Engine to generate the simulation runway scene with built-in stereo cameras. The results show that for the landing scenario, ORB-SLAM2 can provide the pilot with an alarm message when the descending speed or the glide angle of the aircraft is inappropriate. Also, as a lightweight, real-time, and stand-alone features, ORB-SLAM2 could be easily applied to other smart and capability-limited unmanned aerial vehicles.
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U2 - 10.1109/IECON49645.2022.9969111
DO - 10.1109/IECON49645.2022.9969111
M3 - Conference contribution
AN - SCOPUS:85143905261
T3 - IECON Proceedings (Industrial Electronics Conference)
BT - IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
PB - IEEE Computer Society
T2 - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022
Y2 - 17 October 2022 through 20 October 2022
ER -