A survey on vision-based UAV navigation

References

• Al-Kaff, A., Q. Meng, D. Martín, A. de la Escalera, and J. M. Armingol. 2016. “Monocular Vision-based Obstacle Detection/Avoidance for Unmanned Aerial Vehicles.” Intelligent Vehicles Symposium, IEEE, Gothenburg, Sweden, June 19–22.
   Google Scholar
• Andert, F., and F. Adolf. 2009. “Online World Modeling and Path Planning for an Unmanned Helicopter.” Autonomous Robots 27 (3): 147–164.10.1007/s10514-009-9134-y
   Web of Science ®Google Scholar
• Araar, O., and N. Aouf. 2014. “A New Hybrid Approach for the Visual Servoing of VTOL UAVs from Unknown Geometries.” Paper Presented at the Control and Automation, 22nd Mediterranean Conference of, Palermo, Italy, June 16–19.
   Google Scholar
• Aulinas, J., Y. R. Petillot, J. Salvi, and X. Lladó. 2008. “The SLAM Problem: A Survey.” Conference on Artificial Intelligence Research and Development, 11th International Conference of the Catalan Association for Artificial Intelligence, Spain, October 22–24.
   Google Scholar
• Bai, G., X. Xiang, H. Zhu, D. Yin, and L. Zhu. 2015. “Research on Obstacles Avoidance Technology for UAV Based on Improved PTAM Algorithm.” Paper Presented at the Progress in Informatics and Computing, IEEE International Conference on, Nanjing, China, December 18–20.
   Google Scholar
• Bertrand, O. J., J. P. Lindemann, and M. Egelhaaf. 2015. “A Bio-Inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes.” PLoS Computational Biology 11 (11): e1004339.10.1371/journal.pcbi.1004339
   PubMed Web of Science ®Google Scholar
• Bonin-Font, F., A. Ortiz, and G. Oliver. 2008. “Visual Navigation for Mobile Robots: A Survey.” Journal of Intelligent and Robotic Systems 53 (3): 263–296.10.1007/s10846-008-9235-4
   Web of Science ®Google Scholar
• Bortoff, S. A. 2000. “Path Planning for UAVs.” Paper Presented at the American Control Conference, IEEE, Chicago, IL, USA, June 8–30.
   Google Scholar
• Carrillo, L. R. G., A. E. D. López, R. Lozano, and C. Pégard. 2012. “Combining Stereo Vision and Inertial Navigation System for a Quad-Rotor UAV.” Journal of Intelligent & Robotic Systems 65 (1–4): 373–387.10.1007/s10846-011-9571-7
   Web of Science ®Google Scholar
• Celik, K., S. J. Chung, M. Clausman, and A. K. Somani. 2009. “Monocular Vision SLAM for Indoor Aerial Vehicles.” Paper Presented at the Intelligent Robots and Systems, IEEE/RSJ International Conference on, St. Louis, USA, October10–15.
   Google Scholar
• Cho, D., P. Tsiotras, G. Zhang, and M. Holzinger. 2013. “Robust Feature Detection, Acquisition and Tracking for Relative Navigation in Space with a Known Target.” Paper Presented at the AIAA Guidance, Navigation, and Control Conference, Boston, MA, August 19–22.
   Google Scholar
• Davison, A. J. 2003. “Real-Time Simultaneous Localisation and Mapping with a Single Camera.” Paper Presented at the Computer Vision, IEEE International Conference on, Nice, France, October 13–16.
   Google Scholar
• Desouza, G. N., and A. C. Kak. 2002. “Vision for Mobile Robot Navigation: A Survey.” IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (2): 237–267.10.1109/34.982903
   Web of Science ®Google Scholar
• Dryanovski, I., W. Morris, and J. Xiao. 2010. “Multi-Volume Occupancy Grids: An Efficient Probabilistic 3D Mapping Model for Micro Aerial Vehicles.” Paper Presented at the Intelligent Robots and Systems, IEEE/RSJ International Conference on, Taipei, China, October 18–22.
   Google Scholar
• Engel, J., T. Schöps, and D. Cremers. 2014. “LSD-SLAM: Large-scale Direct Monocular SLAM.” Paper presented at the European Conference on Computer Vision, Zurich, Switzerland, September 6–12, 834–849.
   Google Scholar
• Esrafilian, O., and H. D. Taghirad. 2016. “Autonomous Flight and Obstacle Avoidance of a Quadrotor by Monocular SLAM.” Paper Presented at the Robotics and Mechatronics, 4th IEEE International Conference on, Tehran, Iran, October 26–28.
   Google Scholar
• Forster, C., M. Pizzoli, and D. Scaramuzza. 2014. “SVO: Fast Semi-direct Monocular Visual Odometry.” Paper Presented at the Robotics and Automation, IEEE International Conference on, Hong Kong, China, May 31–June 7.
   Google Scholar
• Forster, C., M. Faessler, F. Fontana, M. Werlberger, and D. Scaramuzza. 2015. “Continuous On-board Monocular-vision-based Elevation Mapping Applied to Autonomous Landing of Micro Aerial Vehicles.” Paper Presented at the Robotics and Automation, IEEE International Conference on, Seattle, USA, May 26–30.
   Google Scholar
• Fournier, J., B. Ricard, and D. Laurendeau. 2007. “Mapping and Exploration of Complex Environments Using Persistent 3D Model.” Paper Presented at the Computer and Robot Vision, Fourth Canadian Conference on, IEEE, Montreal, Canada, May 28–30.
   Google Scholar
• Gageik, N., P. Benz, and S. Montenegro. 2015. “Obstacle Detection and Collision Avoidance for a UAV with Complementary Low-Cost Sensors.” IEEE Access 3: 599–609.10.1109/ACCESS.2015.2432455
   Web of Science ®Google Scholar
• Gaspar, J., N. Winters, and J. Santos-Victor. 2000. “Vision-Based Navigation and Environmental Representations with an Omnidirectional Camera.” IEEE Transactions on Robotics and Automation 16 (6): 890–898.10.1109/70.897802
   Google Scholar
• Gilmore, J. F., and A. J. Czuchry. 1992. “A Neural Network Model for Route Planning Constraint Integration.” Paper Presented at the Neural Networks, IEEE International Joint Conference on, Baltimore, MD, USA, June 7–11.
   Google Scholar
• Gosiewski, Z., J. Ciesluk, and L. Ambroziak. 2011. “Vision-Based Obstacle Avoidance for Unmanned Aerial Vehicles.” Paper Presented at the Image and Signal Processing, 4th IEEE International Congress on, Shanghai, China, October 15–17.
   Google Scholar
• Gutmann, J., M. Fukuchi, and M. Fujita. 2008. “3D Perception and Environment Map Generation for Humanoid Robot Navigation.” The International Journal of Robotics Research 27 (10): 1117–1134.10.1177/0278364908096316
   Web of Science ®Google Scholar
• Haag, J., W. Denk, and A. Borst. 2004. “Fly Motion Vision is Based on Reichardt Detectors regardless of the Signal-to-Noise Ratio.” Proceedings of the National Academy of Sciences of the United States of America 101 (46): 16333–16338.10.1073/pnas.0407368101
   PubMed Web of Science ®Google Scholar
• Han, J., and Y. Chen. 2014. “Multiple UAV Formations for Cooperative Source Seeking and Contour Mapping of a Radiative Signal Field.” Journal of Intelligent & Robotic Systems 74 (1–2): 323–332.10.1007/s10846-013-9897-4
   Web of Science ®Google Scholar
• Harmat, A., M. Trentini, and I. Sharf. 2015. “Multi-camera Tracking and Mapping for Unmanned Aerial Vehicles in Unstructured Environments.” Journal of Intelligent & Robotic Systems 78 (2): 291–317.10.1007/s10846-014-0085-y
   Web of Science ®Google Scholar
• Herissé, B., T. Hamel, R. Mahony, and F. Russotto. 2012. “Landing a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow.” IEEE Transactions on Robotics 28 (1): 77–89.10.1109/TRO.2011.2163435
   Web of Science ®Google Scholar
• Herwitz, S. R., L. F. Johnson, S. E. Dunagan, R. G. Higgins, D. V. Sullivan, J. Zheng, and B. M. Lobitz. 2004. “Imaging from an Unmanned Aerial Vehicle: Agricultural Surveillance and Decision Support.” Computers and Electronics in Agriculture 44 (1): 49–61.10.1016/j.compag.2004.02.006
   Web of Science ®Google Scholar
• Horn, B. K., and B. G. Schunck. 1981. “Determining Optical Flow.” Artificial Intelligence 17 (1–3): 185–203.10.1016/0004-3702(81)90024-2
   Web of Science ®Google Scholar
• Hornung, A., K. M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard. 2013. “OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees.” Autonomous Robots 34 (3): 189–206.10.1007/s10514-012-9321-0
   Web of Science ®Google Scholar
• How, J. P., B. Behihke, A. Frank, D. Dale, and J. Vian. 2008. “Real-time Indoor Autonomous Vehicle Test Environment.” IEEE Control Systems 28 (2): 51–64.10.1109/MCS.2007.914691
   Web of Science ®Google Scholar
• Hrabar, S. 2008. “3D Path Planning and Stereo-based Obstacle Avoidance for Rotorcraft UAVs.” Paper Presented at the Intelligent Robots and Systems, IEEE/RSJ International Conference on, Nice, France, September 22–26.
   Google Scholar
• Jones, E. S. 2009. “Large Scale Visual Navigation and Community Map Building.” PhD diss., University of California at Los Angeles.
   Google Scholar
• Klein, G., and D. Murray. 2007. “Parallel Tracking and Mapping for Small AR Workspaces.” Paper Presented at the Mixed and Augmented Reality, 6th IEEE and ACM International Symposium on, Nara, Japan, November 13–16.
   Google Scholar
• Kümmerle, R., G. Grisetti, H. Strasdat, K. Konolige, and W. Burgard. 2011. “g2o: A General Framework for Graph Optimization.” Paper Presented at the Robotics and Automation, IEEE International Conference on, Shanghai, China, May 9–13.
   Google Scholar
• Langelaan, J. W., and N. Roy. 2009. “Enabling New Missions for Robotic Aircraft.” Science 326 (5960): 1642–1644.10.1126/science.1182497
   PubMed Web of Science ®Google Scholar
• Leutenegger, S., S. Lynen, M. Bosse, R. Siegwart, and P. Furgale. 2015. “Keyframe-Based Visual–inertial Odometry Using Nonlinear Optimization.” The International Journal of Robotics Research 34 (3): 314–334.10.1177/0278364914554813
   Web of Science ®Google Scholar
• Li, J., and N. M. Allinson. 2008. “A Comprehensive Review of Current Local Features for Computer Vision.” Neurocomputing 71 (10): 1771–1787.10.1016/j.neucom.2007.11.032
   Web of Science ®Google Scholar
• Li, H., and S. X. Yang. 2003. “A Behavior-based Mobile Robot with a Visual Landmark-recognition System.” IEEE/ASME Transactions on Mechatronics 8 (3): 390–400.10.1109/TMECH.2003.816818
   Web of Science ®Google Scholar
• Lucas, B. D., and T. Kanade. 1981. “An Iterative Image Registration Technique with an Application to Stereo Vision.” Paper Presented at the DARPA Image Understanding Workshop, 7th International Joint Conference on Artificial Intelligence, Vancouver, Canada, August 24–28.
   Google Scholar
• Lynen, S., M. W. Achtelik, S. Weiss, M. Chli, and R. Siegwart. 2013. “A Robust and Modular Multi-Sensor Fusion Approach Applied to Mav Navigation.” Paper Presented at the Intelligent Robots and Systems, IEEE/RSJ International Conference on, Tokyo, Japan, November 3–7.
   Google Scholar
• Magree, D., and E. N. Johnson. 2014. “Combined Laser and Vision-Aided Inertial Navigation for an Indoor Unmanned Aerial Vehicle.” Paper Presented at the American Control Conference, IEEE, Portland, USA, June 4–6.
   Google Scholar
• Mahon, I., S. B. Williams, O. Pizarro, and M. Johnson-Roberson. 2008. “Efficient View-based SLAM Using Visual Loop Closures.” IEEE Transactions on Robotics 24 (5): 1002–1014.10.1109/TRO.2008.2004888
   Web of Science ®Google Scholar
• Maier, J., and M. Humenberger. 2013. “Movement Detection Based on Dense Optical Flow for Unmanned Aerial Vehicles.” International Journal of Advanced Robotic Systems 10 (2): 146. 10.5772/52764
   Google Scholar
• Márquez-Gámez, D. 2012. “Towards Visual Navigation in Dynamic and Unknown Environment: Trajectory Learning and following, with Detection and Tracking of Moving Objects.” PhD diss., l’Institut National des Sciences Appliquées de Toulouse.
   Google Scholar
• Matsumoto, Y., K. Ikeda, M. Inaba, and H. Inoue. 1999. “Visual Navigation Using Omnidirectional View Sequence.” Paper Presented at the Intelligent Robots and Systems, IEEE/RSJ International Conference on, Kyongju, South Korea, October17–21.
   Google Scholar
• Maza, I., F. Caballero, J. Capitán, J. R. Martínez-de-Dios, and A. Ollero. 2011. “Experimental Results in Multi-UAV Coordination for Disaster Management and Civil Security Applications.” Journal of Intelligent & Robotic Systems 61 (1): 563–585.10.1007/s10846-010-9497-5
   Web of Science ®Google Scholar
• Mirowski, P., R. Pascanu, F. Viola, H. Soyer, A. Ballard, A. Banino, and M. Denil. 2017. “Learning to Navigate in Complex Environments.” The 5th International Conference on Learning Representations, Toulon, France, April 24–26.
   Google Scholar
• Moravec, H. P. 1983. “The Stanford Cart and the CMU Rover.” Proceedings of the IEEE 71 (7): 872–884.10.1109/PROC.1983.12684
   Web of Science ®Google Scholar
• Moreno-Armendáriz, M. A., and H. Calvo. 2014. “Visual SLAM and Obstacle Avoidance in Real Time for Mobile Robots Navigation.” Paper Presented at the Mechatronics, Electronics and Automotive Engineering (ICMEAE), IEEE International Conference on, Cuernavaca, Mexico, November 18–21.
   Google Scholar
• Newcombe, R. A., S. J. Lovegrove, and A. J. Davison. 2011. “DTAM: Dense Tracking and Mapping in Real-time.” Paper Presented at the Computer Vision (ICCV), IEEE International Conference on, Washington, DC, USA, November 6–13.
   Google Scholar
• Nourani-Vatani, N., P. Vinicius, K. Borges, J. M. Roberts, and M. V. Srinivasan. 2014. “On the Use of Optical Flow for Scene Change Detection and Description.” Journal of Intelligent & Robotic Systems 74 (3–4): 817.10.1007/s10846-013-9840-8
   Web of Science ®Google Scholar
• Parunak, H. V., M. Purcell, and R. O’Connell. 2002. “Digital Pheromones for Autonomous Coordination of Swarming UAV’s.” Paper Presented at the 1st UAV Conference, Portsmouth, Virginia, May 20–23.
   Google Scholar
• Pellazar, M. B. 1998. “Vehicle Route Planning with Constraints Using Genetic Algorithms”. Paper Presented at the Aerospace and Electronics Conference, NAECON, 1998, IEEE National, Dayton, USA, July 17.
   Google Scholar
• Ranftl, R., V. Vineet, Q. Chen, and V. Koltun. 2016. “Dense Monocular Depth Estimation in Complex Dynamic Scenes.” Paper Presented at the Computer Vision and Pattern Recognition, IEEE Conference on, Las Vegas, USA, June 27–30.
   Google Scholar
• Roberge, V., M. Tarbouchi, and G. Labonté. 2013. “Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-time UAV Path Planning.” IEEE Transactions on Industrial Informatics 9 (1): 132–141.10.1109/TII.2012.2198665
   Web of Science ®Google Scholar
• Rogers, B., and M. Graham. 1979. “Motion Parallax as an Independent Cue for Depth Perception.” Perception 8 (2): 125–134.10.1068/p080125
   PubMed Web of Science ®Google Scholar
• Rouse, D. M. 1989. “Route Planning Using Pattern Classification and Search Techniques.” Aerospace and Electronics Conference, IEEE National, Dayton, USA, May 22–26.
   Google Scholar
• Ruffier, F., S. Viollet, S. Amic, and N. Franceschini. 2003. “Bio-inspired Optical Flow Circuits for the Visual Guidance of Micro Air Vehicles.” Paper Presented at the Circuits and Systems, IEEE International Symposium on, Bangkok, Thailand, May 25–28.
   Google Scholar
• Santos-Victor, J., G. Sandini, F. Curotto, and S. Garibaldi. 1993. “Divergent Stereo for Robot Navigation: Learning from Bees.” Paper Presented at the Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, New York, USA, June 15–17.
   Google Scholar
• Seitz, S. M., B. Curless, J. Diebel, D. Scharstein, and R. Szeliski. 2006. “A Comparison and Evaluation of Multi-view Stereo Reconstruction Algorithms.” Paper Presented at the Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, New York, USA, June 17–22.
   Google Scholar
• Shen, S., Y. Mulgaonkar, N. Michael, and V. Kumar. 2014. “Multi-Sensor Fusion for Robust Autonomous Flight in Indoor and Outdoor Environments with a Rotorcraft MAV.” Paper Presented at the Robotics and Automation (ICRA), IEEE International Conference on, Hong Kong, China, May 31–June 7.
   Google Scholar
• Silveira, G., E. Malis, and P. Rives. 2008. “An Efficient Direct Approach to Visual SLAM.” IEEE Transactions on Robotics 24 (5): 969–979.10.1109/TRO.2008.2004829
   Web of Science ®Google Scholar
• Srinivasan, M. V., and R. L. Gregory. 1992. “How Bees Exploit Optic Flow: Behavioural Experiments and Neural Models [and Discussion].” Philosophical Transactions of the Royal Society of London B: Biological Sciences 337 (1281): 253–259.10.1098/rstb.1992.0103
   Google Scholar
• Stentz, A. 1994. “Optimal and Efficient Path Planning for Partially-Known Environments.” Paper Presented at the IEEE International Conference on Robotics and Automation, San Diego, CA, USA, May 8–13.
   Google Scholar
• Strasdat, H., J. M. Montiel, and A. J. Davison. 2012. “Visual SLAM: Why Filter?” Image and Vision Computing 30 (2): 65–77.10.1016/j.imavis.2012.02.009
   Web of Science ®Google Scholar
• Strohmeier, M., M. Schäfer, V. Lenders, and I. Martinovic. 2014. “Realities and Challenges of Nextgen Air Traffic Management: The Case of ADS-B.” IEEE Communications Magazine 52 (5): 111–118.10.1109/MCOM.2014.6815901
   Web of Science ®Google Scholar
• Sugihara, K., and I. Suzuki. 1996. “Distributed Algorithms for Formation of Geometric Patterns with Many Mobile Robots.” Journal of Robotic Systems 13 (3): 127–139.10.1002/(SICI)1097-4563(199603)13:3<>1.0.CO;2-Z
   Google Scholar
• Szczerba, R. J., P. Galkowski, I. S. Glicktein, and N. Ternullo. 2000. “Robust Algorithm for Real-time Route Planning.” IEEE Transactions on Aerospace and Electronic Systems 36 (3): 869–878.10.1109/7.869506
   Web of Science ®Google Scholar
• Szeliski, R. 2010. Computer Vision: Algorithms and Applications. London: Springer Science & Business Media.
   Google Scholar
• Szenher, M. D. 2008. “Visual Homing in Dynamic Indoor Environments.” PhD diss., University of Edinburgh.
   Google Scholar
• Tuytelaars, T., and K. Mikolajczyk. 2008. “Local Invariant Feature Detectors: A Survey.” Foundations and Trends in Computer Graphics and Vision 3 (3): 177–280.
   Google Scholar
• Vachtsevanos, G., W. Kim, S. Al-Hasan, F. Rufus, M. Simon, D. Shrage, and J. Prasad. 1997. “Autonomous Vehicles: From Flight Control to Mission Planning Using Fuzzy Logic Techniques.” Paper Presented at the Digital Signal Processing, 13th International Conference on, IEEE, Santorini, Greece, July 2–4.
   Google Scholar
• Valgaerts, L., A. Bruhn, M. Mainberger, and J. Weickert. 2012. “Dense versus Sparse Approaches for Estimating the Fundamental Matrix.” International Journal of Computer Vision 96 (2): 212–234.10.1007/s11263-011-0466-7
   Web of Science ®Google Scholar
• Yershova, A., L. Jaillet, T. Simeon, and S. M. Lavalle. 2005. “Dynamic-Domain RRTs: Efficient Exploration by Controlling the Sampling Domain.” Paper Presented at the IEEE International Conference on Robotics and Automation, Barcelona, Spain, April 18–22.
   Google Scholar
• Zhang, Q., J. Ma, and Q. Liu. 2012. “Path Planning Based Quadtree Representation for Mobile Robot Using Hybrid-Simulated Annealing and Ant Colony Optimization Algorithm.” Paper Presented at The Intelligent Control and Automation (WCICA), 10th World Congress on, IEEE, Beijing, China, July 6–8.
   Google Scholar