Michael Leichtfried
ABSTRACT
In this paper, we present a low-weight and low-cost Unmanned Aerial Vehicle (UAV) for autonomous flight and navigation in GPS-denied environments using an off-the-shelf smartphone as its core on-board processing unit. Thereby, our approach is independent from additional ground hardware and the UAV core unit can be easily replaced with more powerful hardware that simplifies setup updates as well as maintenance. The UAV is able to map, locate and navigate in an unknown indoor environment fusing vision based tracking with inertial and attitude measurements. We choose an algorithmic approach for mapping and localization that does not require GPS coverage of the target area, therefore autonomous indoor navigation is made possible. We demonstrate the UAVs capabilities of mapping, localization and navigation in an unknown 2D marker environment. Our promising results enable future research on 3D self-localization and dense mapping using mobile hardware as the only on-board processing unit.
- M. Achtelik, S. Weiss, and R. Siegwart. Onboard IMU and Monocular Vision based Control for MAVs in Unknown In- and Outdoor Environments. In IEEE International Conference on Robotics and Automation, pages 3056--3063, Shanghai, China, 2011.Google Scholar
Cross Ref
- M. Achtelik, T. Zhang, K. Kuhnlenz, and M. Buss. Visual Tracking and Control of a Quadcopter using a Stereo Camera System and Inertial Sensors. In International Conference on Mechatronics and Automation, pages 2863--2869, 2009.Google ScholarCross Ref
- AeroQuad. The Open Source Multicopter. {Online} http://www.aeroquad.com/, Apr. 2013.Google Scholar
- Arduino. {Online} http://www.arduino.cc/, Apr. 2013.Google Scholar
- Ascending Technologies GmbH. {Online} http://www.asctec.de/, Feb. 2013.Google Scholar
- R. Büchi and P. Dauner. Fascination Quadrocopter: Basics - Electronics - Flight Experience. Vth-Fachbuch. Verlag f.Technik/Handwerk, 2010.Google Scholar
- J. Eckert, R. German, and F. Dressler. An Indoor Localization Framework for Four-Rotor Flying Robots Using Low-Power Sensor Nodes. IEEE Transactions on Instrumentation and Measurement, 60(2):336--344, Feb. 2011.Google ScholarCross Ref
- S. Erhard, K. E. Wenzel, and A. Zell. Flyphone: Visual Self-Localisation Using a Mobile Phone as Onboard Image Processor on a Quadrocopter. Journal of Intelligent and Robotic Systems, 57(1-4):451--465, Sept. 2009. Google ScholarDigital Library
- Google Inc. Android NDK. {Software} Revision 8e http://developer.android.com/tools/sdk/ndk/, Jan. 2013.Google Scholar
- Google Inc. Android SDK. {Software} Version 4.0.3 http://developer.android.com/sdk/, Jan. 2013.Google Scholar
- S. Grzonka, G. Grisetti, and W. Burgard. Towards a Navigation System for Autonomous Indoor Flying. In IEEE International Conference on Robotics and Automation, ICRA '09, pages 2878--2883, 2009. Google ScholarDigital Library
- J. Hertzberg, K. Lingemann, and A. Nüchter. Mobile Roboter: Eine Einführung aus Sicht der Informatik. Springer, 2012.Google Scholar
- A. S. Huang, A. Bachrach, P. Henry, M. Krainin, D. Maturana, D. Fox, and N. Roy. Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera. In International Symposium on Robotics Research (ISRR), Flagstaff, Arizona, USA, Aug. 2011.Google Scholar
- G. Klein and D. Murray. Parallel Tracking and Mapping for Small AR Workspaces. In International Symposium on Mixed and Augmented Reality, pages 225--234, 2007. Google ScholarDigital Library
- S. Klose, M. Achtelik, G. Panin, F. Holzapfel, and A. Knoll. Markerless, Vision-assisted Flight Control of a Quadrocopter. 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 5712--5717, Oct. 2010.Google ScholarCross Ref
- H. Lim, H. Lee, and H. J. Kim. Onboard Flight Control of a Micro Quadrotor using Single Strapdown Optical Flow Sensor. In International Conference on Intelligent Robots and Systems, pages 495--500, 2012.Google ScholarCross Ref
- L. Meier, P. Tanskanen, F. Fraundorfer, and M. Pollefeys. PIXHAWK: A System for Autonomous Flight using Onboard Computer Vision. In IEEE International Conference on Robotics and Automation, pages 2992--2997, Shanghai, China, May 2011.Google ScholarCross Ref
- Parrot SA. Parrot ARDrone. {Online} http://ardrone2.parrot.com/, Apr. 2013.Google Scholar
- Qualcomm Inc. Vuforia SDK. {Software} Version 1.5.9 https://developer.vuforia.com/resources/sdk/android/, Jan. 2013.Google Scholar
- S. Shen, N. Michael, and V. Kumar. Autonomous Multi-Floor Indoor Navigation with a Computationally Constrained MAV. In IEEE International Conference on Robotics and Automation, pages 20--25, Shanghai, China, May 2011.Google ScholarCross Ref
- S. Weiss, D. Scaramuzza, and R. Siegwart. Monocular-SLAM-based Navigation for Autonomous Micro Helicopters in GPS-denied Environments. Journal of Field Robotics, 28(6):854--874, 2011. Google ScholarDigital Library
- Willow Garage Inc. Robot Operating System. {Online} http://www.willowgarage.com/pages/software/ros-platform/, Feb. 2013.Google Scholar
- T. Zhang, Y. Kang, M. Achtelik, K. Kuhnlenz, and M. Buss. Autonomous Hovering of a Vision/IMU guided Quadrotor. In International Conference on Mechatronics and Automation, pages 2870--2875, 2009.Google Scholar
Index Terms
- Autonomous Flight using a Smartphone as On-Board Processing Unit in GPS-Denied Environments
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