Visual-GPS combined 'follow-me' tracking for selfie drones

被引:5
作者
Do, T. Tuan [1 ]
Ahn, Heejune [1 ]
机构
[1] Seoul Natl Univ Sci & Technol, Dept Elect & Informat Engn, Seoul, South Korea
关键词
Selfie drone; follow-me mode; sensor fusion; visual tracking; GPS; OBJECT TRACKING;
D O I
10.1080/01691864.2018.1501278
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
The 'follow-me' mode, where the drone autonomously follows and captures the user or target, is a new and attractive feature for camera drones, especially selfie drones. For this purpose, today's commercial drones use the difference between two GPS data in the drone and user-side mobile GCS, e.g. a smartphone, but the targeting performance is often not satisfactory due to the inaccuracy of the GPS data, ranging from a few to tens of meters. Visual tracking can be considered for a solution to this problem, but the reliability of visual tracking is still questionable for long-term tracking in unexpected operating environments. The paper proposes a hybrid approach that combines the high accuracy of a visual tracking algorithm in short-term tracking and the reliability of GPS-based one in long-term tracking. The experiment with our prototype drone system demonstrates that the proposed combined approach can accomplish the follow-me operation very successfully, capturing the target in the center of video contents over 50% higher accuracy than the GPS-based ones. Also, the extreme scenario experiments verify the system can recover vision tracking failure and Wi-Fi failure quickly in a short-term, e.g. 3-7 s.
引用
收藏
页码:1047 / 1060
页数:14
相关论文
共 15 条
[1]  
[Anonymous], MAVIC PRO ACTIVE TRA
[2]  
[Anonymous], PHANT 4 ACT TRACK AL
[3]  
[Anonymous], 2015 14 MEX INT C AR
[4]  
[Anonymous], IEEE ROBOT AUTOM MAG
[5]  
[Anonymous], 2016, IEEE T PATTERN ANAL, DOI DOI 10.1109/TPAMI.2015.2509974
[6]  
Hedgecock Will., 2013, Proceeding of the 11th annual international conference on Mobile systems, applications, and services (MobiSys '13), P221, DOI DOI 10.1145/2462456.2464456
[7]   Tracking-Learning-Detection [J].
Kalal, Zdenek ;
Mikolajczyk, Krystian ;
Matas, Jiri .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 34 (07) :1409-1422
[8]   The Visual Object Tracking VOT2015 challenge results [J].
Kristan, Matej ;
Matas, Jiri ;
Leonardis, Ales ;
Felsberg, Michael ;
Cehovin, Luka ;
Fernandez, Gustavo ;
Vojir, Tomas ;
Hager, Gustav ;
Nebehay, Georg ;
Pflugfelder, Roman ;
Gupta, Abhinav ;
Bibi, Adel ;
Lukezic, Alan ;
Garcia-Martins, Alvaro ;
Saffari, Amir ;
Petrosino, Alfredo ;
Montero, Andres Solis ;
Varfolomieiev, Anton ;
Baskurt, Atilla ;
Zhao, Baojun ;
Ghanem, Bernard ;
Martinez, Brais ;
Lee, ByeongJu ;
Han, Bohyung ;
Wang, Chaohui ;
Garcia, Christophe ;
Zhang, Chunyuan ;
Schmid, Cordelia ;
Tao, Dacheng ;
Kim, Daijin ;
Huang, Dafei ;
Prokhorov, Danil ;
Du, Dawei ;
Yeung, Dit-Yan ;
Ribeiro, Eraldo ;
Khan, Fahad Shahbaz ;
Porikli, Fatih ;
Bunyak, Filiz ;
Zhu, Gao ;
Seetharaman, Guna ;
Kieritz, Hilke ;
Yau, Hing Tuen ;
Li, Hongdong ;
Qi, Honggang ;
Bischof, Horst ;
Possegger, Horst ;
Lee, Hyemin ;
Nam, Hyeonseob ;
Bogun, Ivan ;
Jeong, Jae-chan .
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOP (ICCVW), 2015, :564-586
[9]   Build Your Own Quadrotor Open-Source Projects on Unmanned Aerial Vehicles [J].
Lim, Hyon ;
Park, Jaemann ;
Lee, Daewon ;
Kim, H. J. .
IEEE ROBOTICS & AUTOMATION MAGAZINE, 2012, 19 (03) :33-45
[10]  
Meier Lorenz., Mavlink: Micro air vehicle communication protocol