Abstract
In this use case chapter, we summarize our experience during the development of an autonomous UAV for the German DLR Spacebot Cup robot competition. The autarkic UAV is designed as a companion robot for a ground robot supporting it with fast environment exploration and object localisation. On the basis of ROS Indigo we employed, extended and developed several ROS packages to build the intelligence of the UAV to let it fly autonomously and act meaningfully as an explorer to disclose the environment map and locate the target objects. Besides presenting our experiences and explaining our design decisions the chapter includes detailed descriptions of our hardware and software system as well as further references that provide a foundation for developing own autonomous UAV resolving complex tasks using ROS. A special focus is given on the navigation with SLAM and visual odometry, object localisation, collision avoidance, exploration and high level planning and decision making. Extended and developed packages are available for download, see footnotes in the respective sections of the chapter.
Keywords
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Complete task description in German at http://www.dlr.de/rd/Portaldata/28/Resources/dokumente/rr/AufgabenbeschreibungSpaceBotCup2015.pdf.
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manufactured by Ascending Technologies.
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References
Kryza, L, S. Kapitola, C. Avsar, and K. Briess. 2015. Developing technologies for space on a terrestrial system: A cost effective approach for planetary robotics research. In 1st syposium on space educational acitvities, Padova, Italy.
Mur-Artal, R, J.M.M. Montiel, and J.D. Tardós. 2015. ORB-SLAM: A versatile and accurate monocular SLAM system. CoRR. arXiv:abs/1502.00956.
Honegger, D., L. Meier, P. Tanskanen, and M. Pollefeys. 2013. An open source and open hardware embedded metric optical flow CMOS camera for indoor and outdoor applications. In 2013 IEEE international conference on robotics and automation (ICRA) 1736–1741.
Lecun, Y., L. Bottou, Y. Bengio, and P. Haffner. 1998. Gradient-based learning applied to document recognition. Proceedings of the IEEE 86 (11): 2278–2324.
Li, G., A. Yamashita, H. Asama, and Y. Tamura. 2012. An efficient improved artificial potential field based regression search method for robot path planning. In 2012 international conference on Mechatronics and automation (ICMA), 1227–1232.
Loianno, G., Y. Mulgaonkar, C. Brunner, D. Ahuja, A. Ramanandan, M. Chari, S. Diaz, and V. Kumar. 2015. Smartphones power flying robots. In 2015 IEEE/RSJ international conference on intelligent robots and systems (IROS), 1256–1263.
Tomic, T., K. Schmid, P. Lutz, A. Domel, M. Kassecker, E. Mair, I. Grixa, F. Ruess, M. Suppa, and D. Burschka. 2012. Toward a fully autonomous UAV: Research platform for indoor and outdoor urban search and rescue. IEEE Robotics Automation Magazine 19 (3): 46–56.
Schmid, K., P. Lutz, T. Tomić, E. Mair, and H. Hirschmüller. 2014. Autonomous vision-based micro air vehicle for indoor and outdoor navigation. Journal of Field Robotics 31 (4): 537–570.
Beul, M., N. Krombach, Y. Zhong, D. Droeschel, M. Nieuwenhuisen, and S. Behnke. 2015. A high-performance MAV for autonomous navigation in complex 3d environments. In 2015 international conference on unmanned aircraft systems (ICUAS), 1241–1250. IEEE: New York.
Sunderhauf, N., P. Neubert, M. Truschzinski, D. Wunschel, J. Poschmann, S. Lange, and P. Protzel. 2014. Phobos and deimos on mars - two autonomous robots for the DLR spacebot cup. In The 12th international symposium on artificial intelligence, robotics and automation in space (i-SAIRAS’14), Montreal, Canada, The Canadian Space Agency (CSA-ASC).
Endres, F., J. Hess, J. Sturm, D. Cremers, and W. Burgard. 2014. 3-d mapping with an RGB-d camera. IEEE Transactions on Robotics 30 (1): 177–187.
Labbe, M., and F. Michaud. 2014. Online global loop closure detection for large-scale multi-session graph-based SLAM. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, 2661–2666.
Engel, J., T. Schöps, and D. Cremers. 2014. LSD-SLAM: large-scale direct monocular SLAM. In Computer vision – ECCV 2014: 13th European conference, Zurich, Switzerland, September 6–12, 2014, Proceedings, Part II, 834–849. Springer International Publishing, Cham.
Forster, C., M. Pizzoli, and D. Scaramuzza. 2014. SVO: Fast semi-direct monocular visual odometry. In IEEE international conference on robotics and automation (ICRA).
Engel, J., J. Sturm, and D. Cremers. 2014. Scale-aware navigation of a low-cost quadrocopter with a monocular camera. Robotics and Autonomous Systems 62 (11): 1646–1656.
Izzo, D., and G. de Croon. 2012. Landing with time-to-contact and ventral optic flow estimates. Journal of Guidance, Control, and Dynamics 35 (4): 1362–1367.
Deng, L. 2012. The mnist database of handwritten digit images for machine learning research. IEEE Signal Processing Magazine 29 (6): 141–142.
Li, G., A. Yamashita, H. Asama, and Y. Tamura. 2012. An efficient improved artificial potential field based regression search method for robot path planning. In: 2012 international conference on Mechatronics and automation (ICMA), 1227–1232. New York: IEEE
Thrun, S., D. Fox, and W. Burgard. 2005. Probabilistic robotics. Cambridge: The MIT Press.
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.
Koenig, S., and M. Likhachev. 2005. Fast replanning for navigation in unknown terrain. IEEE Transactions on Robotics 21 (3): 354–363.
Du, Z., D. Qu, F. Xu, and D. Xu. 2007. A hybrid approach for mobile robot path planning in dynamic environments. In IEEE international conference on robotics and biomimetics, 2007. ROBIO 2007, 1058–1063. New York: IEEE.
Oriolo, G., M. Vendittelli, L. Freda, and G. Troso. 2004. The SRT method: Randomized strategies for exploration. In 2004 IEEE international conference on robotics and automation, 2004. Proceedings. ICRA’04, vol. 5, 4688–4694. New York: IEEE.
Yamauchi, B. 1997. A frontier-based approach for autonomous exploration. In Proceedings of the 1997 IEEE international symposium on computational intelligence in robotics and automation, 1997. CIRA’97, 146–151. New York: IEEE
Surmann, H., A. Nüchter, and J. Hertzberg. 2003. An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments. Robotics and Autonomous Systems 45 (3): 181–198.
Tovar, B., L. Munoz-Gómez, R. Murrieta-Cid, M. Alencastre-Miranda, R. Monroy, and S. Hutchinson. 2006. Planning exploration strategies for simultaneous localization and mapping. Robotics and Autonomous Systems 54 (4): 314–331.
Hrabia, C.E., N. Masuch, and S. Albayrak. 2015. A metrics framework for quantifying autonomy in complex systems. In Multiagent System Technologies: 13th German Conference, MATES 2015, Cottbus, Germany, September 28–30, 2015, Revised Selected Papers, 22–41. Springer International Publishing, Cham.
Quigley, M., K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, and A.Y. Ng. 2009. Ros: An open-source robot operating system. In ICRA Workshop on Open Source Software 3 (3.2): 5. Kobe.
Bohren, J., and S. Cousins. 2010. The SMACH high-level executive [ros news]. IEEE Robotics Automation Magazine 17 (4): 18–20.
Goebel R.P. 2014. ROS by example: Packages and programs For advanced robot behaviors. Pi Robot Production, vol. 2, 61–88. Lulu.com.
CogniTeam Ltd. Cognitao (think as one). [Online]. Available: http://www.cogniteam.com/cognitao.html.
Jung, D. 1998. An architecture for cooperation among autonomous agents. PhD thesis, University of South Australia.
Maes, P. 1989. How to do the right thing. Connection Science 1 (3): 291–323.
Allgeuer, P., S. Behnke. 2013. Hierarchical and state-based architectures for robot behavior planning and control. In Proceedings of 8th Workshop on Humanoid Soccer Robots, IEEE-RAS International Conference on Humanoid Robots, Atlanta, USA.
Hoffmann, J. 2002. Extending FF to numerical state variables. In Proceedings of the 15th European conference on artificial intelligence, 571–575. New York: Wiley.
Yan, Z., L. Fabresse, J. Laval, and N. Bouraqadi. 2014. Team size optimization for multi-robot exploration. In Proceedings of the 4th international conference on simulation, modeling, and programming for autonomous robots (SIMPAR 2014), Bergamo, Italy (October 2014), 438–449.
Echeverria, G., N. Lassabe, A. Degroote, and S. Lemaignan. 2011. Modular open robots simulation engine: MORSE. In Proceedings of the 2011 IEEE international conference on robotics and automation.
Acknowledgements
The presented work was partially funded by the German Aerospace Center (DLR) with funds from the Federal Ministry of Economics and Technology (BMWi) on the basis of a decision of the German Bundestag (Grant No: 50RA1420).
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Hrabia, CE. et al. (2017). An Autonomous Companion UAV for the SpaceBot Cup Competition 2015. In: Koubaa, A. (eds) Robot Operating System (ROS). Studies in Computational Intelligence, vol 707. Springer, Cham. https://doi.org/10.1007/978-3-319-54927-9_11
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