Abstract
This paper describes a proposal of solution for target visual loss in autonomous navigation of UAVs by using artificial. Tests of target maintenance and position recovery have been included along with the sequence of images that verify the method performance.
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References
Limnaios, G.: Current usage of unmanned aircraft systems (UAS) and future challenges: a mission oriented simulator for UAS as a tool for design and performance evaluation. J. Comput. Model 4(1), 167–188 (2014)
Achille, C., et al.: UAV-based photogrammetry and integrated technologies for architectural applications—methodological strategies for the after-quake survey of vertical structures in Mantua (Italy). Sensors 15(7), 15520–15539 (2015)
Hassanalian, M., Abdelkefi, A.: Classifications, applications, and design challenges of drones: a review. Prog. Aerosp. Sci. 91, 99–131 (2017)
Aguilar, W.G., Salcedo, V.S., Sandoval, D.S., Cobeña, B.: Developing of a video-based model for UAV autonomous navigation. In: Barone, D.A.C., Teles, E.O., Brackmann, C.P. (eds.) LAWCN 2017. CCIS, vol. 720, pp. 94–105. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-71011-2_8
Duffy, J.P., et al.: Location, location, location: considerations when using lightweight drones in challenging environments. Remote Sens. Ecol. Conserv. 1–13 (2017)
Aguilar, W.G., et al.: Cascade classifiers and saliency maps based people detection. In: De Paolis, L.T., Bourdot, P., Mongelli, A. (eds.) AVR 2017. LNCS, vol. 10325, pp. 501–510. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-60928-7_42
Aguilar, W.G., Angulo, C.: Real-time model-based video stabilization for microaerial vehicles. Neural Process. Lett. 43(2), 459–477 (2016)
Aguilar, W.G., et al.: Pedestrian detection for UAVs using cascade classifiers and saliency maps. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2017. LNCS, vol. 10306, pp. 563–574. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59147-6_48
Tribukait, A., Bergsten, E., Eiken, O.: Pitch-plane angular displacement perception during helicopter flight and gondola centrifugation. Aerosp. Med. Hum. Perform. 87(10), 852–861 (2016)
Márquez Pardo, I.: Visual control of a mobile robot by means of an overhead view (Bachelor’s thesis) (2016)
Arróspide, J., Salgado, L.: Video based vehicle detection and tracking for driver assistance systems. Securitas Vialis 7(1–3), 41–49 (2015)
Urzua, S., Munguía, R., Grau, A.: Vision-based SLAM system for MAVs in GPS-denied environments. Int. J. Micro Air Veh. 9, 283–296 (2017)
Revollo Sarmiento, N., Delrieux, C., Perillo, G.M.: Software de visión por computador en sistemas de monitoreo ambiental. In: XIV Workshop de Investigadores en Ciencias de la Computación (2012)
Rituerto, A.: Modeling the environment with egocentric vision systems. ELCVIA Electron. Lett. Comput. Vis. Image Anal. 14(3), 49–51 (2015)
Rituerto, A., Puig, L., Guerrero, J.J.: Comparison of omnidirectional and conventional monocular systems for visual slam. In: 10th OMNIVIS with RSS (2010)
Grenzdörffer, G.J., Niemeyer, F.: UAV based BRDF-measurements of agricultural surfaces with PFIFFikus. Int. Arch. Photogr. Remote Sens. Spat. Inf. Sci. 38(1/C22), 229–234 (2011)
Remondino, F., Barazzetti, L., Nex, F., Scaioni, M., Sarazzi, D.: UAV photogrammetry for mapping and 3D modeling–current status and future perspectives. Int. Arch. Photogr. Remote Sens. Spat. Inf. Sci. 38(1), C22 (2011)
Guzmán, D.A.I., Alarcón, J.R.C., Torres, A.A., Bárcenas, M.A.M.: Design of an artificial neural network to detect obstacles on highways through the flight of an UAV. Res. Comput. Sci. 105, 31–40 (2015)
Paillard, A.C., Quarck, G., Denise, P.: Sensorial countermeasures for vestibular spatial disorientation. Aviat. Space environ. Med. 85(5), 563–567 (2014)
Clarke, R.: Understanding the drone epidemic. Comput. Law Secur. Rev. 30(3), 230–246 (2014)
Charmette, B., Royer, E., Chausse, F.: Vision-based robot localization based on the efficient matching of planar features. Mach. Vis. Appl. 27(4), 415–436 (2016)
Chmaj, G., Selvaraj, H.: Distributed processing applications for UAV/drones: a survey. In: Selvaraj, H., Zydek, D., Chmaj, G. (eds.) Progress in Systems Engineering. AISC, vol. 366, pp. 449–454. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-08422-0_66
Derpanis, K.G.: Overview of the RANSAC algorithm. Image Rochester NY 4(1), 2–3 (2010)
Kendoul, F.: Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems. J. Field Robot. 29(2), 315–378 (2012)
Jégou, H., Douze, M., Schmid, C., Pérez, P.: Aggregating local descriptors into a compact image representation. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3304–3311. IEEE (2010)
Awad, A.I., Hassaballah, M.: Image Feature Detectors and Descriptors: Foundations and Applications, vol. 630. Springer, Heidelberg (2016)
Sayem, A.S.S.: Vision-Aided Navigation for Autonomous Vehicles Using Tracked Feature Points (2016)
Zhang, X., Wang, X., Yuan, X., Wang, S.: An improved SIFT algorithm in the application of close-range stereo image matching. In: IOP Conference Series: Earth and Environmental Science, vol. 46, No. 1, p. 012009. IOP Publishing (2016)
Al-khafaji, S.L., Zhou, J., Zia, A., Liew, A.W.C.: Spectral-spatial scale invariant feature transform for hyperspectral images. IEEE Trans. Image Process. 27, 837–850 (2017)
Lowe, D.: Object recognition from local scale-invariant features. In: Proceedings of IEEE International Conference on Computer Vision, vol. 2, pp. 1150–1157 (1999)
Aguilar, W.G., Angulo, C.: Real-time video stabilization without phantom movements for micro aerial vehicles. EURASIP J. Image Video Process. 12(1), 46 (2014)
Zhu, Y., Shen, X., Chen, H.: Copy-move forgery detection based on scaled ORB. Multimed. Tools Appl. 75(6), 3221–3233 (2016)
Xie, S., Zhang, W., Ying, W., Zakim, K.: Fast detecting moving objects in moving background using ORB feature matching. In: 2013 Fourth International Conference on Intelligent Control and Information Processing (ICICIP), pp. 304–309. IEEE (2013)
Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to SIFT or SURF. In: ICCV (2011)
Ma, Y., Soatto, S., Kosecka, J., Sastry, S.S.: An Invitation to 3-D Vision: From Images to Geometric Models, vol. 26. Springer, Heidelberg (2012)
Aguilar, W.G., Casaliglla, V.P., Pólit, J.L.: Obstacle avoidance based-visual navigation for micro aerial vehicles. Electronics 6(1), 10 (2017)
Aguilar, W.G., Casaliglla, V.P., Pólit, J.L., Abad, V., Ruiz, H.: Obstacle avoidance for flight safety on unmanned aerial vehicles. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2017. LNCS, vol. 10306, pp. 575–584. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59147-6_49
Engel, J., Sturm, J., Cremers, D.: Accurate figure flying with a quadrocopter using onboard visual and inertial sensing. Imu 320, 240 (2012)
Engel, J., Sturm, J., Cremers, D.: Camera-based navigation of a low-cost quadrocopter. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2815–2821. IEEE (2012)
Papakonstantinou, A., Topouzelis, K., Pavlogeorgatos, G.: Coastline zones identification and 3D coastal mapping using UAV spatial data. ISPRS Int. J. Geo-Inf. 5(6), 75 (2016)
Urzua, S., Munguía, R., Grau, A.: Vision-based SLAM system for MAVs in GPS-denied environments. Int. J. Micro Air Veh. 9(4), 283–296 (2017)
Aguilar, W.G., Rodríguez, G.A., Álvarez, L., Sandoval, S., Quisaguano, F., Limaico, A.: Visual SLAM with a RGB-D camera on a quadrotor UAV using on-board processing. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2017. LNCS, vol. 10306, pp. 596–606. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59147-6_51
Aguilar, W.G., Rodríguez, G.A., Álvarez, L., Sandoval, S., Quisaguano, F., Limaico, A.: Real-time 3D modeling with a RGB-D camera and on-board processing. In: De Paolis, L.T., Bourdot, P., Mongelli, A. (eds.) AVR 2017. LNCS, vol. 10325, pp. 410–419. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-60928-7_35
Aguilar, W.G., Rodríguez, G.A., Álvarez, L., Sandoval, S., Quisaguano, F., Limaico, A.: On-board visual SLAM on a UGV using a RGB-D camera. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds.) ICIRA 2017. LNCS (LNAI), vol. 10464, pp. 298–308. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65298-6_28
Aguilar, W.G., Morales, S.G.: 3D environment mapping using the Kinect V2 and path planning based on RRT algorithms. Electronics 5(4), 70 (2016)
Aguilar, W.G., Morales, S., Ruiz, H., Abad, V.: RRT* GL based optimal path planning for real-time navigation of UAVs. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2017. LNCS, vol. 10306, pp. 585–595. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59147-6_50
Forster, C., Lynen, S., Kneip, L., Scaramuzza, D.: Collaborative monocular slam with multiple micro aerial vehicles. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3962–3970. IEEE, November 2013
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Salcedo, V.S., Aguilar, W.G., Cobeña, B., Pardo, J.A., Proaño, Z. (2018). On-Board Target Virtualization Using Image Features for UAV Autonomous Tracking. In: Boudriga, N., Alouini, MS., Rekhis, S., Sabir, E., Pollin, S. (eds) Ubiquitous Networking. UNet 2018. Lecture Notes in Computer Science(), vol 11277. Springer, Cham. https://doi.org/10.1007/978-3-030-02849-7_34
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