Abstract
Indoor navigation with micro aerial vehicles (MAVs) is of growing importance nowadays. State of the art flight management controllers provide extensive interfaces for control and navigation, but most commonly aim for performing in outdoor navigation scenarios. Indoor navigation with MAVs is challenging, because of spatial constraints and lack of drift-free positioning systems like GPS. Instead, vision and/or inertial-based methods are used to localize the MAV against the environment. For educational purposes and moreover to test and develop such algorithms, since 2015 the so called droneSpace was established at the Institute of Computer Graphics and Vision at Graz University of Technology. It consists of a flight arena which is equipped with a highly accurate motion tracking system and further holds an extensive robotics framework for semi-autonomous MAV navigation. A core component of the droneSpace is a Scalable and Lightweight Indoor-navigation MAV design, which we call the SLIM (A detailed description of the SLIM and related projects can be found at our website: https://sites.google.com/view/w-a-isop/home/education/slim). It allows flexible vision-sensor setups and moreover provides interfaces to inject accurate pose measurements form external tracking sources to achieve stable indoor hover-flights. With this work we present capabilities of the framework and its flexibility, especially with regards to research and education at university level. We present use cases from research projects but also courses at the Graz University of Technology, whereas we discuss results and potential future work on the platform.
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Notes
- 1.
A detailed description of the droneSpace, the SLIM and related projects can be found at our website: https://www.tugraz.at/institutes/icg/education/the-dronespace/.
References
ORBBEC: Orbbec Astra Pro (2017). https://orbbec3d.com/
Logitech: C270 HD Webcam (2010). https://www.logitech.com/
Hardkernel: Odroid XU3/XU4 (2014). https://www.hardkernel.com/
Qualcomm: Snapdragon Flight (2014). https://shop.intrinsyc.com/products/snapdragon-flight-dev-kit
Tripicchio, P., Satler, M., Dabisias, G., Ruffaldi, E., Avizzano, C.A.: Towards smart farming and sustainable agriculture with drones. In: 2015 International Conference on Intelligent Environments (IE), pp. 140–143. IEEE, July 2015
Puerta, J.P., Maurer, M., Muschick, D., Adlakha, D., Bischof, H., Fraundorfer, F.: Package Delivery Experiments with a Camera Drone (2017)
Silvagni, M., Tonoli, A., Zenerino, E., Chiaberge, M.: Multipurpose UAV for search and rescue operations in mountain avalanche events. Geomat. Nat. Hazards Risk 8(1), 18–33 (2017)
Meier, L., Tanskanen, P., Heng, L., Lee, G.H., Fraundorfer, F., Pollefeys, M.: PIXHAWK: a micro aerial vehicle design for autonomous flight using onboard computer vision. Auton. Robot. 33(1–2), 21–39 (2012)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3, no. 3.2, p. 5, May 2009
Bouabdallah, S., Murrieri, P., Siegwart, R.: Design and control of an indoor micro quadrotor. In: 2004 IEEE International Conference on Robotics and Automation, Proceedings, ICRA 2004, vol. 5, pp. 4393–4398. IEEE, April 2004
How, J.P., Behihke, B., Frank, A., Dale, D., Vian, J.: Real-time indoor autonomous vehicle test environment. IEEE Control Syst. 28(2), 51–64 (2008)
Vempati, A.S., Choudhary, V., Behera, L.: Quadrotor: design, control and vision based localization. IFAC Proc. Vol. 47(1), 1104–1110 (2014)
Loianno, G., Brunner, C., McGrath, G., Kumar, V.: Estimation, control, and planning for aggressive flight with a small quadrotor with a single camera and IMU. IEEE Robot. Autom. Lett. 2(2), 404–411 (2017)
Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: RGB-D mapping: using depth cameras for dense 3D modeling of indoor environments. In: The 12th International Symposium on Experimental Robotics (ISER) (2010)
Kushleyev, A., Mellinger, D., Powers, C., Kumar, V.: Towards a swarm of agile micro quadrotors. Auton. Robots 35(4), 287–300 (2013)
DJI: Ryze Tello, Mavic 2 and Spark. (2017). https://www.dji.com/at
Infineon: Educopter (2018). https://www.infineon.com/cms/en/applications/consumer/multicopters-and-drones/
Intel: Intel Aero (2016). https://software.intel.com/en-us/aero
Bitcraze: Bitcraze Crazyflie 2.0 (2014). https://www.bitcraze.io/
Parrot, S.A.: Parrot Bebop 2 (2016). http://www.parrot.com/
Falanga, D., Mueggler, E., Faessler, M., Scaramuzza, D.: Aggressive quadrotor flight through narrow gaps with onboard sensing and computing using active vision. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 5774–5781. IEEE, May 2017
Austro Control: Regulations for Unmanned Aerial Vehicles (2014). https://www.austrocontrol.at/drohnen
DroneArt: DroneArt Aeon X-Frame (2018). https://redbee.de/DRONEART-Aeon-HighEnd-Series-X-Frame-UL12
Ramamurthy, S.: Thrust models (2018). http://www.dept.aoe.vt.edu/~lutze/AOE3104/thrustmodels.pdf
Choi, Y.C., Ahn, H.S.: Nonlinear control of quadrotor for point tracking: actual implementation and experimental tests. IEEE/ASME Transactions Mechatron. 20(3), 1179–1192 (2015)
Beard, R.: Quadrotor dynamics and control rev 0.1 (2008)
Ziegler, J.G., Nichols, N.B.: Optimum settings for automatic controllers. Trans. ASME, 64(11) (1942)
Seidel, M.S.C.: Entwurf und Stabilitätsanalyse der Höhenregelung und Wandvermeidung des FINken II Quadrokopters
Joyo, M.K., Hazry, D., Ahmed, S.F., Tanveer, M.H., Warsi, F.A., Hussain, A.T.: Altitude and horizontal motion control of quadrotor UAV in the presence of air turbulence. In: 2013 IEEE Conference on Systems, Process and Control (ICSPC), pp. 16–20. IEEE, December 2013
Andreas, R.: Dynamics identification & validation, and position control for a quadrotor. Swiss Federal Institute of Technology Zurich, Spring Term (2010)
Isop, W.A., Pestana, J., Ermacora, G., Fraundorfer, F., Schmalstieg, D.: Micro aerial projector-stabilizing projected images of an airborne robotics projection platform. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5618–5625. IEEE, October 2016
Erat, O., Isop, W.A., Kalkofen, D., Schmalstieg, D.: Drone-augmented human vision: exocentric control for drones exploring hidden areas. IEEE Trans. Vis. Comput. Graph. 24(4), 1437–1446 (2018)
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Isop, W.A., Fraundorfer, F. (2020). SLIM - A Scalable and Lightweight Indoor-Navigation MAV as Research and Education Platform. In: Merdan, M., Lepuschitz, W., Koppensteiner, G., Balogh, R., Obdržálek, D. (eds) Robotics in Education. RiE 2019. Advances in Intelligent Systems and Computing, vol 1023. Springer, Cham. https://doi.org/10.1007/978-3-030-26945-6_17
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