Skip to main content
Log in

Multi-rotor drone tutorial: systems, mechanics, control and state estimation

  • Review Article
  • Published:
Intelligent Service Robotics Aims and scope Submit manuscript

Abstract

We present a tutorial introduction to the multi-rotor unmanned aerial vehicles, often simply referred as drones. We first explain typical configuration, components and construction of the drones. We then provide basic kinematic and dynamic modeling of drones and their principle of flight. Some representative motion control techniques are then presented, which take into account the issue of under-actuation of the drones. State estimation problem of the drones, that is crucial for their proper flying, yet, should be done only by using onboard sensors and their sensor fusion, is explained. Some emerging research directions requiring capability beyond typical drones are also mentioned.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Skynamic shooting for game of thrones commercial with RED EPIC Dragon Drone. https://www.skynamic.net/en/news/page/2. Accessed 20 Feb 2017

  2. D’Andrea R (2014) Guest editorial can drones deliver? IEEE Trans Autom Sci Eng 11(3):647–648

    Article  Google Scholar 

  3. Trimble Inc Trimble ZX5. http://www.trimble.com/Survey/ZX5.aspx?tab=Overview. Accessed 29 Dec 2016

  4. PrecisionHawk. http://www.precisionhawk.com/. Accessed 29 Dec 2016

  5. Özslan T, Mohta K, Keller J, Mulgaonkar Y, Taylor CJ, Kumar V, Wozencraft JM, Hood T (2016) Towards fully autonomous visual inspection of dark featureless dam penstocks using MAVs. In: Proceedings of IEEE international conference on robotics and automation

  6. Li Z, Liu Y, Walker R, Hayward R, Zhang J (2010) Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved hough transform. Mach Vis Appl 21(5):677–686

    Article  Google Scholar 

  7. Scentroid DR300, Flying Laboratory. http://scentroid.com/scentroid-sampling-drone/. Accessed 29 Dec 2016

  8. Achtelik M et al (2012) Sfly: swarm of micro flying robots. In: Proceedings of IEEE/RSJ International conference on intelligent robots and systems, pp 2649–2650

  9. Airdog, Inc Airdog. https://www.airdog.com/. Accessed 29 Dec 2016

  10. Intel, Corp Intel’s 500 Drone Light Show. http://www.intel.com/content/www/us/en/technology-innovation/aerial-technology-overview.html. Accessed 29 Dec 2016

  11. Parrot SA AR Drone 2.0. https://www.parrot.com/us/#drones. Accessed 29 Dec 2016

  12. 3D Robotics, Inc 3D Robotics Solo. https://3dr.com/solo-drone/. Accessed 29 Dec 2016

  13. DJI DJI drones. http://www.dji.com/products/drones. Accessed 29 Dec 2016

  14. Syma Co, Ltd Syma Cheerwing X5SW. http://www.symatoys.com/goods/fpv-quadcopter.html. Accessed 29 Dec 2016

  15. Yuneec Yuneec Typhoon. https://www.yuneec.com/en_US/products/typhoon/h/overview.html. Accessed 29 Dec 2016

  16. Cheerson Co, Ltd, Cheerson CX-10C. http://www.cheersonhobby.com/en-US/Home/ProductDetail/125. Accessed 17 Feb 2017

  17. TRNDlabs SKEYE Nano. https://www.trndlabs.com/product/skeye-nano-drone-with-camera. Accessed 17 Feb 2017

  18. GTF GTF AG-10. http://en.gtfdrone.com/goods/good?goods_id=45. Accessed 17 Feb 2017

  19. Aerial Technology International ATI AgBOT. http://www.aerialtechnology.com. Accessed 17 Feb 2017

  20. EHANG Inc EHANG 184. http://www.ehang.com/ehang184. Accessed 17 Feb 2017

  21. e-volo GmbH Volocopter VC200. http://volocopter.com. Accessed 20 Feb 2017

  22. Amazoncom, Inc Amazon Prime Air. https://www.amazon.com/Amazon-Prime-Air/b?ie=UTF8&node=8037720011. Accessed 29 Dec 2016

  23. Airbus SAS Airbus demonstrates aircraft inspection by drone at farnborough. http://www.airbusgroup.com/int/en/news-media/media~item=33fc85f6-e973-43c2-8259-e196158d7f80~.html. Accessed 29 Dec 2016

  24. Uragun B (2011) Energy efficiency for unmanned aerial vehicles. In: Proceedings of IEEE international conference on machine learning and applications and workshops, pp 316–320

  25. Stock D (2015) Fast and furious. New Sci 228(3052):60–61

    Article  Google Scholar 

  26. Briod A, Kornatowski P (2014) A collision-resilient flying robot. J Field Robot 31(4):496–509

    Article  Google Scholar 

  27. Scaramuzza D, Achtelik MC, Doitsidis L, Friedrich F, Kosmatopoulos E, Martinelli A, Achtelik MW, Chli M, Chatzichristofis S, Kneip L, Gurdan D, Heng L, Lee GH, Lynen S, Pollefeys M, Renzaglia A, Siegwart R, Stumpf JC, Tanskanen P, Troiani C, Weiss S, Meier S (2014) Vision-controlled micro flying robots: from system design to autonomous navigation and mapping in GPS-denied environments. IEEE Robot Autom Mag 21(3):26–40

    Article  Google Scholar 

  28. Tsui JB (2000) Fundamentals of global positioning system receivers: a software approach. Wiley, New York

    Book  Google Scholar 

  29. Kaplan ED, Hegarty CJ (2005) Understanding GPS: principles and applications, 2nd edn. Artech House, Norwood, MA

  30. Bristeau PJ, Callou F, Vissiere D, Petit N (2011) The navigation and control technology inside the AR.Drone micro UAV. In: Proceedings of IFAC world congress, pp 1477–1484

  31. Weiss S, Achtelik MW, Lynen S, Chli M, Siegwart R (2012) Real-time onboard visual-inertial state estimation and self-calibration of MAVs in unknown environments. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems, pp 957–964

  32. Hesch JA, Kottas DG, Bowman SL, Roumeliotis SI (2014) Camera-IMU-based localization: observability analysis and consistency improvement. Int J Robot Res 33(1):182–201

    Article  Google Scholar 

  33. Shen S, Michael N, Kumar V (2015) Tightly-coupled monocular visual-inertial fusion for autonomous flight of rotorcraft MAVs. In: Proceedings IEEE international conference on robotics and automation, pp 5303–5310

  34. 3D Robotics, Inc Pixhawk. https://pixhawk.org/modules/pixhawk. Accessed 29 Dec 2016

  35. DJI Dji flight controller. http://www.dji.com/products/industrial#developer-nav. Accessed 29 Dec 2016

  36. Hardkernel co, Ltd Odroid xu4. http://www.hardkernel.com/main/products/prdt_info.php?g_code=G143452239825. Accessed 29 Dec 2016

  37. Intel, Corp Intel nuc. http://www.intel.eu/content/www/eu/en/nuc/overview.html. Accessed 29 Dec 2016

  38. Nvidia, Corp Nvidia jetson tx1. http://www.nvidia.com/object/jetson-tx1-dev-kit.html. Accessed 29 Dec 2016

  39. Vásárhelyi G, Virágh C, Somorjai G, Tarcai N, Szörényi T, Nepusz T, Vicsek T (2014) Outdoor flocking and formation flight with autonomous aerial robots. In: Proceedings IEEE/RSJ international conference on intelligent robots and systems, pp 3866–3873

  40. Athukoralage D, Guvenc I, Saad W, Bennis M (2016) Regret based learning for UAV assisted LTE-u/wifi public safety networks. In: Proceedings IEEE conference on global communications, pp 1–7

  41. Qazi S, Siddiqui AS, Wagan AI (2015) UAV based real time video surveillance over 4g LTE. In: Proceedings of IEEE international conference on open source systems and technologies, pp 141–145

  42. Mueller MW, D’Andrea R (2014) Stability and control of a quadrotor despite the complete loss of one, two, or three propellers. In: Proceedings IEEE international conference on robotics and automation, pp 45–52

  43. Lee D (2012) Distributed backstepping control of multiple thrust-propelled vehicles on a balanced graph. Automatica 48(11):2971–2977

    Article  MathSciNet  MATH  Google Scholar 

  44. Ghadiok V, Goldin J, Ren W (2012) On the design and development of attitude stabilization, vision-based navigation, and aerial gripping for a low-cost quadrotor. Auton Robots 33:41–68

    Article  Google Scholar 

  45. Lim H, Park J, Lee D, Kim HJ (2012) Build your own quadrotor: open-source projects on unmanned aerial vehicles. IEEE Robot Autom Mag 19(3):33–45

    Article  Google Scholar 

  46. Mahony R, Kumar V, Corke P (2012) Multirotor aerial vehicles: modeling, estimation, and control of quadrotor. IEEE Robot Autom Mag 19(3):20–32

    Article  Google Scholar 

  47. Lee DJ, Franchi A, Son HI, Ha C, Bulthoff HH, Giordano PR (2014) Semiautonomous haptic teleoperation control architecture of multiple unmanned aerial vehicles. IEEE/ASME Trans Mechatron 18(4):1334–1345

    Article  Google Scholar 

  48. Mahony R, Hamel T (2004) Robust trajectory tracking for a scale model autonomous helicopter. Int J Robust Nonlinear Control 14:1035–1059

    Article  MathSciNet  MATH  Google Scholar 

  49. Hua MD, Hamel T, Morin P, Samson C (2009) A control approach for thrust-propelled underactuated vehicles and its application to vtol drones. IEEE Trans Autom Control 54(8):1837–1853

    Article  MathSciNet  Google Scholar 

  50. Ha C, Zuo Z, Choi FB, Lee DJ (2014) Passivity-based adaptive backstepping control of quadrotor-type UAVs. Robot Auton Syst 62(9):1305–1315

    Article  Google Scholar 

  51. Lee T, Leok M, McClamroch NH (2010) Geometric tracking control of a quadrotor UAV on se(3). In: Proceedings IEEE conference on decision and control, pp 5420–5425

  52. Mellinger D, Kumar V (2011) Minimum snap trajectory generation and control for quadrotors. In: Proceedings IEEE international conference on robotics and automation, pp 2520–2525

  53. Bouabdallah S, Siegwart R (2007) Full control of a quadrotor. In: Proceedings IEEE/RSJ international conference on intelligent robots and systems, pp 153–158

  54. Lee D, Kim HJ, Sastry S (2009) Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter. Int J Control Autom Syst 7(3):419–428

    Article  Google Scholar 

  55. Mahony R, Hamel T, Pflimlin JM (2008) Nonlinear complementary filters on the special orthogonal group. IEEE Trans Autom Control 53(5):1203–1217

    Article  MathSciNet  Google Scholar 

  56. Shen S, Mulgaonkar Y, Michael N, Kumar V (2013) Vision-based state estimation for autonomous rotorcraft MAVs in complex environments. In: Proc. IEEE international conference on robotics and automation, pp 1758–1764

  57. Shen S, Mulgaonkar Y, Michael N, Kumar V (2014) Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft MAV. In: Proceedings of IEEE international conference on robotics and automation, pp 4974–4981

  58. Forster C, Pizzoli M, Scaramuzza D (2014) SVO: fast semi-direct monocular visual odometry. In: Proceedings of IEEE international conference on robotics and automation, pp 15–22

  59. Bloesch M, Omari S, Hutter M, Siegwart R (2015) Robust visual inertial odometry using a direct EKF based approach. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems, pp 298–304

  60. Lee Y, Yoon J, Yang H, Kim C, Lee D (2016) Camera-GPS-IMU sensor fusion for autonomous flying. In: Proceedings of IEEE international conference on ubiquitous and future networks, pp 85–88

  61. Gebre-Egziabher D, Hayward RC, Powell JD (2004) Design of multi-sensor attitude determination systems. IEEE Trans Aerosp Electron Syst 40(2):627–649

    Article  Google Scholar 

  62. Markley FL, Crassidis JL, Cheng Y (2005) Nonlinear attitude filtering methods. In: Proceedings of AIAA guidance, navigation, and control conference, pp 15–18

  63. Baerveldt AJ, Klang R (1997) A low-cost and low-weight attitude estimation system for an autonomous helicopter. In: Proceedings of IEEE International Conference on Intelligent Engineering Systems, pp 391–395

  64. Vik B, Fossen TI (2001) A nonlinear observer for GPS and INS integration. In: Proceedings of IEEE conference on decision and control, vol 3, pp 2956–2961

  65. Lefferts EJ, Markley FL, Shuster MD (1982) Kalman filtering for spacecraft attitude estimation. J Guid Control Dyn 5(5):417–429

    Article  Google Scholar 

  66. Gross J, Gu Y, Gururajan S, Seanor B, Napolitano MR (2010) A comparison of extended kalman filter, sigma-point Kalman filter, and particle filter in GPS/INS sensor fusion. In: Proceedings of AIAA guidance, navigation, and control conference, pp 1–19

  67. Zhang P, Gu J, Milios EE, Huynh P (2005) Navigation with IMU/GPS/digital compass with unscented Kalman filter. In: Proceedings of IEEE international conference on mechatronics and automation, vol 3, pp 1497–1502

  68. Yun B, Peng K, Chen BM (2007) Enhancement of GPS signals for automatic control of a UAV helicopter system. In: Proceedings of IEEE international conference on control and automation, pp 1185–1189

  69. El-Rabbany A (2002) Introduction to GPS: the global positioning system. Artech House, Norwood, MA

  70. Duffield R, Reid M, Baker J, Spratford W (2010) Accuracy and reliability of GPS devices for measurement of movement patterns in confined spaces for court-based sports. J Sci Med Sport 13(5):523–525

    Article  Google Scholar 

  71. Grzonka S, Grisetti G, Burgard W (2012) A fully autonomous indoor quadrotor. IEEE Trans Robot 28(1):90–100

  72. Santamaria-Navarro A, Sola J, Andrade-Cetto J (2015) High-frequency MAV state estimation using low-cost inertial and optical flow measurement units. In: Proceedings of IEEE/RJS international conference on intelligent robots and systems, pp 1864–1871

  73. Kendoul F, Fantoni I, Nonami K (2009) Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles. Robot Auton Syst 57(6):591–602

    Article  Google Scholar 

  74. Honegger D, Meier L, Tanskanen P, Pollefeys M (2013) An open source and open hardware embedded metric optical flow CMOS camera for indoor and outdoor applications. In: Proceedings IEEE international conference on robotics and automation, pp 1736–1741

  75. Davison AJ (2003) Real-time simultaneous localisation and mapping with a single camera. In: Proceedings of IEEE international conference on computer vision, pp 1403–1410

  76. Klein G, Murray D (2007) Parallel tracking and mapping for small AR workspaces. In: Proceedings of IEEE/ACM international symposium on mixed and augmented reality. IEEE, pp 225–234

  77. Monajjemi VM, Wawerla J, Vaughan R, Mori G (2013) Hri in the sky: creating and commanding teams of UAVs with a vision-mediated gestural interface. In: Proceedings of IEEE/RJS international conference on intelligent robots and systems, pp 617–623

  78. Mur-Artal R, Montiel J, Tardós JD (2015) ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE Trans Robot 31(5):1147–1163

    Article  Google Scholar 

  79. Grisetti G, Kummerle R, Stachniss C, Burgard W (2010) A tutorial on graph-based SLAM. IEEE Intell Transp Syst Mag 2(4):31–43

    Article  Google Scholar 

  80. Engel J, Schöps T, Cremers D (2014) LSD-SLAM: Large-scale direct monocular SLAM. In: Proceedings of European conference on computer vision, pp 834–849

  81. Nieto J, Guivant J, Nebot E (2006) Denseslam: simultaneous localization and dense mapping. Int J Robot Res 25(8):711–744

    Article  Google Scholar 

  82. Li M, Mourikis AI (2013) High-precision, consistent EKF-based visual-inertial odometry. Int J Robot Res 32(6):690–711

    Article  Google Scholar 

  83. Hesch JA, Kottas DG, Bowman SL, Roumeliotis SI (2014) Camera-IMU-based localization: observability analysis and consistency improvement. Int J Robot Res 33(1):182–201

    Article  Google Scholar 

  84. Yang Z, Shen S (2017) Monocular visual-inertial state estimation with online initialization and camera-IMU extrinsic calibration. IEEE Trans Autom Sci Eng 14(1):39–51

    Article  Google Scholar 

  85. Leutenegger S, Lynen S, Bosse M, Siegwart R, Furgale P (2015) Keyframe-based visual-inertial odometry using nonlinear optimization. Int J Robot Res 34(3):314–334

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dongjun Lee.

Additional information

Research supported in part by the Bio-Mimetic Robot Research Center (UD130070ID) funded by the Defense Acquisition Program Administration (DAPA) and by the Agency for Defense Development (ADD) of Korea.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, H., Lee, Y., Jeon, SY. et al. Multi-rotor drone tutorial: systems, mechanics, control and state estimation. Intel Serv Robotics 10, 79–93 (2017). https://doi.org/10.1007/s11370-017-0224-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11370-017-0224-y

Keywords

Navigation