Experimental evaluation of a real-time GPU-based pose estimation system for autonomous landing of rotary wings UAVs

Control Theory and Technology - Tập 16 Số 2 - Trang 145-159 - 2018
Alessandro Benini1, Matthew J. Rutherford1, Kimon P. Valavanis1
1DU Unmanned Systems Research Institute (DU2SRI), University of Denver (DU), Denver, U.S.A.

Tóm tắt

Từ khóa


Tài liệu tham khảo

C. Bu, Y. Ai, H. Du. Vision-based autonomous landing for rotorcraft unmanned aerial vehicle. IEEE International Conference on Vehicular Electronics and Safety (ICVES), Beijing: IEEE, 2016: 1–6. DOI 10.1109/ICVES.2016.7548174.

A. Gautam, P. B. Sujit, S. Saripalli. A survey of autonomous landing techniques for UAVs. International Conference on Unmanned Aircraft Systems (ICUAS), Orlando: IEEE, 2014: 1210–1218. DOI 10.1109/ICUAS.2014.6842377.

M. F. R. Lee, S. F. Su, J. W. E. Yeah, et al. Autonomous landing system for aerial mobile robot cooperation. The Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS), Kitakyushu: IEEE, 2014: 1306–1311. DOI 10.1109/SCIS-ISIS.2014.7044826.

X. Guan, H. Bai. A GPU accelerated real-time self-contained visual navigation system for UAVs. IEEE International Conference on Information and Automation, Shenyang: IEEE, 2012: 578–581. DOI 10.1109/ICInfA.2012.6246879.

S. Yang, S. A. Scherer, K. Schauwecker, et al. Onboard monocular vision for landing of an MAV on a landing site specified by a single reference image. International Conference on Unmanned Aircraft Systems (ICUAS), Atlanta: IEEE, 2013: 318–325. DOI 10.1109/ICUAS.2013.6564704.

S. Yang, S. A. Scherer, K. Schauwecker, A. Zell. Autonomous Landing of MAVs on an arbitrarily textured landing site using onboard monocular vision. Journal of Intelligent & Robotic Systems, 2014, 74(1/2): 27–43.

G. Klein, D. Murray. Parallel tracking and mapping for small AR workspaces. The 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, Nara: IEEE, 2007: 225–234. DOI 10.1109/ISMAR.2007.4538852.

F. Cocchioni, A. Mancini, S. Longhi. Autonomous navigation, landing and recharge of a quadrotor using artificial vision. International Conference on Unmanned Aircraft Systems (ICUAS), Orlando: IEEE, 2014: 418–429. DOI 10.1109/ICUAS.2014. 6842282.

Y. Jung, D. Lee, H. Bang. Study on ellipse fitting problem for vision-based autonomous landing of an UAV. The 14th International Conference on Control, Automation and Systems (ICCAS), Seoul: IEEE, 2014: 1631–1634. DOI 10.1109/ICCAS.2014.6987819

K. Li, P. Liu, T. Pang, et al. Development of an unmanned aerial vehicle for rooftop landing and surveillance. International Conference on Unmanned Aircraft Systems (ICUAS), Denver: IEEE, 2015: 832–838. DOI 10.1109/ICUAS.2015.7152368.

A. Masselli, S. Yang, K. E. Wenzel, et al. A cross-platform comparison of visual marker based approaches for autonomous flight of quadrocopters. International Conference on Unmanned Aircraft Systems (ICUAS), Atlanta: IEEE, 2013: 685–693. DOI 10.1109/ICUAS.2013.6564749.

W. Roozing, A. H. Goktogan. Low-cost vision-based 6-DOF MAV localization using IR beacons. IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Wollongong: IEEE, 2013: 1003–1009. DOI 10.1109/AIM.2013.6584225.

H. Cheng, Y. Chen, X. Li, et al. Autonomous takeoff, tracking and landing of a UAV on a moving UGV using onboard monocular vision. Proceedings of the 32nd Chinese Control Conference, Xi’an: IEEE, 2013: 5895–5901.

S. Lange, N. Sunderhauf, P. Protzel. A vision based onboard approach for landing and position control of an autonomous multirotor UAV in GPS-denied environments. International Conference on Advanced Robotics, Munich, 2009: 1–6.

K. H. Hsia, S. F. Lien, J. P. Su. Height estimation via stereo vision system for unmanned helicopter autonomous landing. International Symposium on Computer, Communication, Control and Automation (3CA), Tainan: IEEE, 2010: 257–260. DOI 10.1109/3CA.2010.5533535.

S. Saripalli, G. S. Sukhatme. Landing on a moving target using an autonomous helicopter. Field and Service Robotics: Recent Advances in Research and Applications. Berlin: Springer, 2006: 277–286. DOI 10.1007/10991459_27.

D. Jeon, D.-H. Kim, Y.-G. Ha, et al. Image processing acceleration for intelligent unmanned aerial vehicle on mobile GPU. Soft Computing, 2016, 20(5): 1713–1720. DOI http://dx.doi.org/10.1007/s00500-015-1656-y.

F. Ababsa, M. Mallem. A robust circular fiducial detection technique and real-time 3D camera tracking. Journal of Multimedia, 2008, 3(4): 34–41

L. Calvet, P. Gurdjos, V. Charvillat. Camera tracking using concentric circle markers: Paradigms and algorithms. The 19th IEEE International Conference on Image Processing, Orlando: IEEE, 2012: 1361–1364. DOI 10.1109/ICIP.2012.6467121.

F. Ababsa, M. Mallem. A robust circular fiducial detection technique and real-time 3D camera tracking. Journal of Multimedia, 2008, 3(4): 34–41.

A. Benini, M. J. Rutherford, K. P. Valavanis. Real-time, GPUbased pose estimation of a UAV for autonomous takeoff and landing. IEEE International Conference on Robotics and Automation (ICRA), Stockholm: IEEE, 2016: 3463–3470. DOI 10.1109/ICRA.2016.7487525.

S. A. Conyers, N. I. Vitzilaios, M. J. Rutherford, et al. A mobile self-leveling landing platform for VTOL UAVs. IEEE International Conference on Robotics and Automation (ICRA), Seattle: IEEE, 2015: 815–822. DOI 10.1109/ICRA.2015.7139272.

CUDA Programming Guide: http://docs.nvidia.com/cuda/cuda-cprogramming-guide.

Pinhole Camera Model: https://docs.opencv.org/2.4/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html.