Abstract
In this chapter we present a modular Micro Aerial Vehicle (MAV) simulation framework, which enables a quick start to perform research on MAVs. After reading this chapter, the reader will have a ready to use MAV simulator, including control and state estimation. The simulator was designed in a modular way, such that different controllers and state estimators can be used interchangeably, while incorporating new MAVs is reduced to a few steps. The provided controllers can be adapted to a custom vehicle by only changing a parameter file. Different controllers and state estimators can be compared with the provided evaluation framework. The simulation framework is a good starting point to tackle higher level tasks, such as collision avoidance, path planning, and vision based problems, like Simultaneous Localization and Mapping (SLAM), on MAVs. All components were designed to be analogous to its real world counterparts. This allows the usage of the same controllers and state estimators, including their parameters, in the simulation as on the real MAV.
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Notes
- 1.
Ascending Technologies http://www.asctec.de/.
- 2.
- 3.
Octree2 by WhiteTimberwolf, PNG version: Nü—Own work. Licensed under CC BY-SA 3.0 via Wikimedia Commons—http://commons.wikimedia.org/wiki/File:Octree2.svg#/media/File:Octree2.svg.
- 4.
As described on: http://docs.ros.org/api/nav_msgs/html/msg/Odometry.html.
- 5.
The official Gazebo sensor tutorials can be accessed on: http://gazebosim.org/tutorials?cat=sensors.
- 6.
More on namespaces can be found on: http://wiki.ros.org/Names.
- 7.
Additional Gazebo plugins are listed on: http://gazebosim.org/tutorials?tut=ros_gzplugins.
- 8.
A video of a Firefly following a path in real world and in the RotorS simulator can be seen on http://youtu.be/3cGFmssjNy8.
References
M.W. Achtelik, Advanced closed loop visual navigation for micro aerial vehicles. Ph.D. thesis, ETH Zurich, 2014
T. Field, J. Leibs, J. Bowman, Rosbag (2015), http://wiki.ros.org/rosbag. Accessed 27 Mar 2015
S. Glaser, W. Woodall, Xacro (2015), http://wiki.ros.org/xacro. Accessed 27 Mar 2015
A. Hornung, K.M. Wurm, M. Bennewitz, C. Stachniss, W. Burgard, OctoMap: An efficient probabilistic 3D mapping framework based on octrees. Auton. Robots (2013). http://octomap.github.com
T. Lee, M. Leoky, N.H. McClamroch, Geometric tracking control of a quadrotor UAV on SE (3), in 2010 49th IEEE Conference on Decision and Control (CDC) (IEEE, 2010), pp. 5420–5425
S. Lynen, M.W. Achtelik, S. Weiss, M. Chli, R. Siegwart, A robust and modular multi-sensor fusion approach applied to mav navigation, in 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE, 2013), pp. 3923–3929
P. Martin, E. Salaun, The true role of accelerometer feedback in quadrotor control, in 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 1623–1629, May 2010
L. Matthies, R. Brockers, Y. Kuwata, S. Weiss, Stereo vision-based obstacle avoidance for micro air vehicles using disparity space, in 2014 IEEE International Conference on Robotics and Automation (ICRA) (IEEE, 2014), pp. 3242–3249
S.A. Sucan, S. Chitta, Moveit! (2015), http://moveit.ros.org. Accessed 10 Aug 2015
N. Trawny, S.I. Roumeliotis, Indirect Kalman filter for 3D attitude estimation. Technical Report 2005-002, University of Minnesota, Department of Computer Science and Engineering, 2005
S. Weiss, Vision based navigation for micro helicopters. Ph.D. thesis, ETH Zurich, 2012
Wikipedia, Airspeed indicator (2015), http://en.wikipedia.org/wiki/Airspeed_indicator. Accessed 27 Mar 2015
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Furrer, F., Burri, M., Achtelik, M., Siegwart, R. (2016). RotorS—A Modular Gazebo MAV Simulator Framework. In: Koubaa, A. (eds) Robot Operating System (ROS). Studies in Computational Intelligence, vol 625. Springer, Cham. https://doi.org/10.1007/978-3-319-26054-9_23
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