Abstract
In this research chapter, we present our work on a universal grid map library for use as mapping framework for mobile robotics. It is designed for a wide range of applications such as online surface reconstruction and terrain interpretation for rough terrain navigation. Our software features multi-layered maps, computationally efficient repositioning of the map boundaries, and compatibility with existing ROS map message types. Data storage is based on the linear algebra library Eigen, offering a wide range of data processing algorithms. This chapter outlines how to integrate the grid map library into the reader’s own applications. We explain the concepts and provide code samples to discuss various features of the software. As a use case, we present an application of the library for online elevation mapping with a legged robot. The grid map library and the robot-centric elevation mapping framework are available open-source at http://github.com/ethz-asl/grid_map and http://github.com/ethz-asl/elevation_mapping.
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Notes
- 1.
A video demonstration is available at http://youtu.be/I9eP8GrMyNQ.
- 2.
A video demonstration is available at http://youtu.be/phaBKFwfcJ4.
- 3.
For simplicity, we use the list initialization feature of C++11 on Line 16.
- 4.
Available at: http://github.com/ethz-asl/elevation_mapping.
References
P. Fankhauser, M. Bloesch, C. Gehring, M. Hutter, R. Siegwart, Robot-centric elevation mapping with uncertainty estimates, in International Conference on Climbing and Walking Robots (CLAWAR) (2014)
P. Fankhauser, M. Bloesch, D. Rodriguez, R. Kaestner, M. Hutter, R. Seigwart, Kinect v2 for mobile robot navigation: evaluation and modeling, in International Conference on Advanced Robotics (ICAR) (2015)
G. Guennebaud, B. Jacob, Eigen 3, http://eigen.tuxfamily.org. Accessed Aug 2015
E. Marder-Eppstein, D.V. Lu, D. Hershberger. costmap\(\_\)2d, http://wiki.ros.org/costmap_2d. Accessed Aug 2015
D.V. Lu, D. Hershberger, W.D. Smart, Layered costmaps for context-sensitive navigation, in IEEE International Conference on Intelligent Robots and Systems (IROS) (2014)
D.V. Lu, M. Ferguson, navigation, http://wiki.ros.org/navigation. Accessed Aug 2015
A. Hornung, K.M. Wurm, M. Bennewitz, C. Stachniss, W. Burgard, OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Auton. Robot. 34(3), 189–206 (2013)
K.M. Wurm, A. Hornung. octomap, http://wiki.ros.org/octomap. Accessed Aug 2015
C. Forster, M. Faessler, F. Fontana, M. Werlbeger, D. Scaramuzza, Continuous on-board monocular-vision–based elevation mapping applied to autonomous landing of micro aerial vehicles, in IEEE International Conference on Robotics and Automation (ICRA) (2015)
M. Hutter, C. Gehring, M. Hoepflinger, M. Bloesch, R. Siegwart, Towards combining speed, efficiency, versatility and robustness in an autonomous quadruped. IEEE Trans. Robot. 30(6), 1427–1440 (2014)
ROS.org. Ubuntu install of ROS Indigo, http://wiki.ros.org/indigo/Installation/Ubuntu. Accessed Aug 2015
ROS.org. Installing and Configuring Your ROS Environment, http://wiki.ros.org/ROS/Tutorials/InstallingandConfiguringROSEnvironment. Accessed Aug 2015
ROS.org. filters, http://wiki.ros.org/filters. Accessed Aug 2015
J.E. Bresenham, Algorithm for computer control of a digital plotter. IBM Syst. J. 4(1), 25–30 (1965)
M. Bloesch, C. Gehring, P. Fankhauser, M. Hutter, M.A. Hoepflinger, R. Siegwart, State estimation for legged robots on unstable and slippery terrain, in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2013)
LaValle, S.M. Rapidly-Exploring Random Trees: A New Tool for Path Planning (1998)
Acknowledgments
This work was supported in part by the Swiss National Science Foundation (SNF) through project 200021_149427/1 and the National Centre of Competence in Research Robotics.
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Fankhauser, P., Hutter, M. (2016). A Universal Grid Map Library: Implementation and Use Case for Rough Terrain Navigation. 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_5
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