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2016 | OriginalPaper | Buchkapitel

RotorS—A Modular Gazebo MAV Simulator Framework

verfasst von : Fadri Furrer, Michael Burri, Markus Achtelik, Roland Siegwart

Erschienen in: Robot Operating System (ROS)

Verlag: Springer International Publishing

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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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Fußnoten
1
Ascending Technologies http://​www.​asctec.​de/​.
 
2
Be aware that in [10], the JPL quaternion notation is used, while [1] and many libraries, including ROS and Eigen, use the Hamilton notation.
 
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.
 
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.
 
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.
 
Literatur
1.
Zurück zum Zitat M.W. Achtelik, Advanced closed loop visual navigation for micro aerial vehicles. Ph.D. thesis, ETH Zurich, 2014 M.W. Achtelik, Advanced closed loop visual navigation for micro aerial vehicles. Ph.D. thesis, ETH Zurich, 2014
4.
Zurück zum Zitat 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 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
5.
Zurück zum Zitat 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 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
6.
Zurück zum Zitat 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 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
7.
Zurück zum Zitat 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 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
8.
Zurück zum Zitat 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 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
10.
Zurück zum Zitat 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 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
11.
Zurück zum Zitat S. Weiss, Vision based navigation for micro helicopters. Ph.D. thesis, ETH Zurich, 2012 S. Weiss, Vision based navigation for micro helicopters. Ph.D. thesis, ETH Zurich, 2012
Metadaten
Titel
RotorS—A Modular Gazebo MAV Simulator Framework
verfasst von
Fadri Furrer
Michael Burri
Markus Achtelik
Roland Siegwart
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-26054-9_23

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