Abstract
The present study deals with the risky and daunting tasks of flying and landing in non-stationary environments. Using a two Degree-Of-Freedom (DOF) tethered micro-air vehicle (MAV), we show the benefits of an autopilot dealing with a variable - the optic flow - which depends directly on two relative variables, the groundspeed and the groundheight. The micro-helicopter was shown to follow the ups and downs of a rotating platform that was also oscillated vertically. At no time did the MAV know in terms of ground height whether it was approaching the moving ground or whether the ground itself was rising to it dangerously. Nor did it know whether its current groundspeed was caused only by its forward thrust or whether it was partly due to the ground moving backwards or forwards. Furthermore, the MAV was shown to land safely on a platform set into motion along two directions, vertical and horizontal. This paper extends to non-stationary environments a former approach that introduced the principle of “optic flow regulation” for altitude control. Whereas in the former approach no requirement was set on the robot’s landing target, the target’s elevation angle was used here in a second feedback loop that gradually altered the robot’s pitch and therefore its airspeed, leading to smooth landing in the vicinity of the target. Whether dealing with terrain following or landing, the MAV followed followed appropriately the unpredictable changes in the environment although it had no explicit knowledge of groundheight and groundspeed. The MAV did not make use of any rangefinders or velocimeters and was simply equipped with a 2-gram vision-based autopilot.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
Abbreviations
- OF:
-
Optic flow
References
Ruffier, F., Franceschini, N.: Optic flow regulation: the key to aircraft automatic guidance. Robot. Auton. Syst. 50(4), 177–194 (2005)
Franceschini, N., Ruffier, F., Serres, J.: A bio-inspired flying robot sheds light on insect piloting abilities. Curr. Biol. 17, 329–335 (2007)
Sousa, P., Wellons, L., Colby, G., Walters, J., Weir, J.: Test results of an f/a-18 automatic carrier landing using shipboard relative global positioning system. Technical report, Naval Air Warfare Center Aircraft Division, Tech. Rep (2003)
Reboulet, C.: Appontage automatique d’un uav -onera dcsd toulouse-. In: Proceedings of the JNRR’99, Montpellier (1999)
Coutard, L., Chaumette, F., Pflimlin, J.M.: Automatic landing on aircraft carrier by visual servoing. In: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS’11. San Francisco, pp 2843–2848 (2011)
Vu, B., Lemoing, T., Costes, P.: Integration of flight and carrier landing aid systems for shipboard operations. In: AGARD, Aircraft Ship Operations 15 (1991)
Subrahmanyam, M.: H infinity design of f/a-18a automatic carrier landing system. Journal of Guidance. Control Dyn. 17(1), 187–191 (1994)
Zufferey, J.C., Floreano, D.: Fly-inspired visual steering of ultralight indoor aircraft. IEEE Trans. Robot. 22(1), 137–146 (2006)
de Croon, G., Ho, H., Wagter, C.D., van Kampen, E., Remes, B., Chu, Q.: Optic-flow based slope estimation for autonomous landing. In: International Micro Air Vehicle Conference and Flight Competition (IMAV2013). Toulouse (2013)
Briod, A., Zufferey, J.C., Floreano, D.: Optic-flow based control of a 46g quadrotor. In: Workshop on Vision-based Closed-Loop Control and Navigation of Micro Helicopters in GPS-denied Environments. IROS, Tokyo (2013)
Ma, K., Chirarattananon, P., Fuller, S., Wood, R.: Controlled flight of a biologically inspired, insect-scale robot. Science 340(6132), 603–607 (2013)
Voskuijl, M., Padfield, G., Walker, D., Manimala, B., Gubbels, A.: Simulation of automatic helicopter deck landings using nature inspired flight control and flight envelope protection. Aeronaut. J. 114(1151): Paper No. 3426. (2008)
Saripalli, S., Montgomery, J., Sukhatme, G.: Visually guided landing of an unmanned aerial vehicle. IEEE Trans. Robot. Autom. 19(3), 371–380 (2003)
Saripalli, S., Sukhatme, G.S.: Landing a helicopter on a moving target. In: Proceedings of 2007 IEEE International Conference on Robotics and Automation (2007)
Edwards, B., Archibald, J., Fife, W., Lee, D.J.: A vision system for precision MAV targeted landing. In: International Symposium on Computational Intelligence in Robotics and Automation (CIRA 2007), 20–23 June 2007, pp. 125–130 (2007)
Rui, W., Guangjun, Z., Peng, Y.: Optical flow based 3d motion estimation for autonomous landing an uav on deck. In: Proceedings of SPIE, the International Society for Optical Engineering ISSN 0277-786X CODEN PSISD, International conference on space information technology (19–20 November, 2005, Wuhan, China ). Volume 5985 (2006)
Portelli, G., Ruffier, F., Franceschini, N.: Honeybees change their height to restore their optic flow. J. Comp. Physiol. A. 196(4), 307–313 (2010)
Zhang, S., Wang, X., Liu, Z., Srinivasan, M.: Visual tracking of moving targets by freely flying honeybees. Vis. Neurosci. 4(4), 379–86 (1990)
Iida, F.: Goal-directed navigation of an autonomous flying robot using biogically inspired cheap vision. In: Proceedings of the 32nd International Symposium on Robotics, pp 1404–1409. ISR, Seoul (2001)
Green, W., Oh, P., Barrows, G.: Flying insect inspired vision for autonomous aerial robot maneuvers in near-earth environments. In: Proceeding of IEEE International Conference of Robotics and Automation (ICRA), pp. 2347–2352. New Orleans (2004)
Beyeler, A., Zufferey, J.C., Floreano, D.: Vision-based control of near-obstacle flight. Auton. Robot. 27(3), 201–219 (2009)
Zufferey, J.C., Beyeler, A., Floreano, D.: Autonomous flight at low altitude using light sensors and little computational power. Int. J. Micro Air Veh. 2(2), 107–117 (2010)
Netter, T., Franceschini, N.: A robotic aircraft that follows terrain using a neuromorphic eye. In: Proceedings of IEEE Conference on Intelligent Robots and Systems (IROS), Lausanne (2002)
Ruffier, F., Viollet, S., Amic, S., Franceschini, N.: Bio-inspired optical flow circuits for the visual guidance of micro-air vehicles. In: Proceedings of IEEE Int. Symposium on Circuits and Systems (ISCAS), Vol. III, pp. 846–849. Bangkok (2003)
Ruffier, F., Franceschini, N.: Aerial robot piloted in steep relief by optic flow sensors. In: International Conference on Intelligent Robots and Systems (IROS), pp. 1266–1273. Nice (2008)
Herisse, B., Russotto, F., Hamel, T., Mahony, R.: Hovering flight and vertical landing control of a VTOL unmanned aerial vehicle using optical flow. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1404–1409. Nice (2008)
Kendoul, F., Nonami, K., Fantoni, I., Lozano, R.: An adaptive vision-based autopilot for mini flying machines guidance, navigation and control. Auton. Robot. 27(3), 165–188 (2009)
Viollet, S., Franceschini, N.: Biologically-inspired visual scanning sensor for stabilization and tracking. In: Proceeding IEEE/RSJ International Conference on Intelligent Robots and System (IROS), pp. 204–209. Kyongju (1999)
Kerhuel, L., Viollet, S., Franceschini, N.: Steering by gazing: An efficient biomimetic control strategy for visually guided micro aerial vehicles. IEEE Trans. Robot. 26, 307–319 (2010)
Garratt, M., Chahl, J.: Vision-based terrain following for an unmanned rotorcraft. J. Field Robot. 25, 284–301 (2008)
Garcia-Carrillo, L.R., Flores, G., Sanahuja, G., Lozano, R.: Quad-rotor switching control: An application for the task of path following. In: American Control Conference (ACC). Montreal (2012)
Conroy, J., Gremillion, G., Ranganathan, B., Humbert, J.: Implementation of wide-field integration of optic flow for autonomous quadrotor navigation. Auton. Robot. 27(3), 189–198 (2009)
Hérissé, B., Hamel, T., Mahony, R., Russotto, F.X.: A terrain-following control approach for a vtol unmanned aerial vehicle using average optical flow. Auton. Robot. 29(3–4), 381–399 (2010)
Griffiths, S., Saunders, J., Curtis, A., Barber, B., McLain, T., Beard, R.: Maximizing miniature aerial vehicles. IEEE Robot. Autom. Mag. 13, 34–43 (2006)
Mellinger, D., Michael, N., Kumar, V.: Trajectory generation and control for precise aggressive maneuvers with quadrotors. Int. J. Robot. Res. 31(5), 664–674 (2012)
Shen, S., Mulgaonkar, Y., Michael, N., Kumar, V.: Vision-based state estimation for autonomous rotorcraft mavs in complex environments. In: IEEE International Conference on Robotics and Automation (ICRA). Karlsruhe, pp 1758–1764 (2013)
Herisse, B., Hamel, T., Mahony, R., Russotto, F.X.: The landing problem of a vtol unmanned aerial vehicle on a moving platform using optical flow. In: Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. Taipei, p 2010
Herisse, B., Hamel, T., Mahony, R., Russotto, F.X.: Landing a vtol unmanned aerial vehicle on a moving platform using optical flow. IEEE Trans. Robot. 28(1), 77–89 (2012)
Wenzel, K.E., Masselli, A., Zell, A.: Automatic take off, tracking and landing of a miniature uav on a moving carrier vehicle. J. Intell. Robot. Syst 61, 221–238 (2011)
Webb, B.: Can robots make good models of biological behavior? Behav. Brain Sci. 24, 1033–1050 (2001)
Kennedy, J.S.: The migration of the desert locust (schistocerca gregaria forsk.)Phil. Trans. Royal Soc. B 235, 163–290 (1951)
Koenderink, J., van Doorn, A.: Facts on optic flow. Biol. Cybern. 56, 247–254 (1987)
Pichon, J.M., Blanes, C., Franceschini, N.: Visual guidance of a mobile robot equipped with a network of self-motion sensors. In: Wolfe, W.J., Chun, W.H. (eds.) Proceedings of SPIE Conf. on Mobile Robots IV, Vol. 1195, pp 44–53. SPIE, Bellingham (1989)
Ruffier, F., Franceschini, N.: Octave, a bioinspired visuo-motor control system for the guidance of micro-air vehicles. In: Rodriguez-Vazquez, A., Abbott, D., Carmona, R. (eds.) SPIE Vol. 5119, Bioengineered and Bioinspired Systems, pp 1–12. SPIE, Bellingham (2003)
Ruffier, F., Franceschini, N.: Visually guided micro-aerial vehicle : automatic take off, terrain following, landing and wind reaction. In: Proceeding of IEEE International Conference on Robotics and Automation (ICRA). New Orleans, pp 2339–2346 (2004)
Ruffier, F.: Pilote Automatique Biomimétique, Système générique inspiré du contrôle visuomoteur des insectes pour : le décollage, le suivi de terrain, la réaction au vent et l’ atterrissage automatiques d’ un micro-aéronef. PhD thesis, INP Grenoble, Ecole Doctorale EEATS, Spécialité : Signal, Image, Parole, Télécommunications (2004)
Ruffier, F., Benacchio, S., Expert, E., Ogam, E.: A tiny directional sound sensor inspired by crickets designed for micro-air vehicles. In: Proceeding of IEEE Sensors 2011 conference, Limerick, Ireland, pp. 970–973 (2011)
Reichardt, W., Wenking, H.: Optical detection and fixation of objects by fixed flying flies (Musca domestica). Naturwissenschaften 56, 424–425 (1969)
van Breugel, F., Dickinson, M.H.: The visual control of landing and obstacle avoidance in the fruit fly, drosophila melanogaster. J. Exp. Biol. 215, 1783–1798 (2012)
Valette, F., Ruffier, F., Viollet, S., Seidl, T.: Biomimetic optic flow sensing applied to a lunar landing scenario. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA 2010), pp. 2253–2260 (2010)
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
About this article
Cite this article
Ruffier, F., Franceschini, N. Optic Flow Regulation in Unsteady Environments: A Tethered MAV Achieves Terrain Following and Targeted Landing Over a Moving Platform. J Intell Robot Syst 79, 275–293 (2015). https://doi.org/10.1007/s10846-014-0062-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-014-0062-5