Mobile Robot Programming Toolkit

The Mobile Robot Programming Toolkit (MRPT) is a cross-platform and open source C++ library aimed to help robotics researchers to design and implement algorithms related to Simultaneous Localization and Mapping (SLAM), computer vision and motion planning (obstacle avoidance). Different research groups have employed MRPT to implement projects reported in some of the major robotics journals and conferences.[1][2][3][4][5]

Mobile Robot Programming Toolkit (MRPT)
MRPT logo
Developer(s)José Luis Blanco Claraco, contributors
Stable release
MRPT 1.5.6 / Apr 24, 2018
Written inC++
Operating systemLinux, Windows
PlatformCross-platform
TypeRobotics suite
LicenseNew BSD License
Websitewww.mrpt.org

MRPT is open source and distributed under the New BSD License. Versions prior to 1.0.0 were released under the GPL.

Some features included in the project as user-applications:

  • Visualization and manipulation of large datasets.
  • SLAM algorithms: incremental mapping with ICP, Extended Kalman filtering, Rao-Blackwellized particle filters and GraphSLAM.
  • Grabbing datasets from robotic sensors.

Upon a selection of the individual libraries provided by MRPT,[6] users can develop new applications.

MRPT participated in Google Summer of Code in 2016-2018[7][8].


Representation of metric maps

Through polymorphism in the design of metric-map classes, observations (such as a laser scans) can be inserted into a grid-map or a map of points, or both simultaneously, transparently to the user.

The following representations of metric maps are implemented:

  • Occupancy grid maps.
  • Point maps.
  • Landmark maps: discrete elements are 3D points sensed through range and bearing. For example, visual landmarks.
  • Beacon maps: elements are also 3D points, but sensed by means of range-only devices.
  • Coloured point maps.
  • Gas concentration maps.
  • A "multi map", collections of any of the other maps, behaving as a single map.
gollark: This is why [REDACTED] apiaristic forkbomb.
gollark: I have a plan to beat all things ever, but it is SLIGHTLY cheating.
gollark: Yes, this is true.
gollark: I was going to make something guess what strategy the enemy is using and play against that.
gollark: We discussed this earlier. The handshakes are a bit suboptimal.

See also

References
  1. J.L. Blanco; J. Gonzalez; J. and J.A. Fernández-Madrigal (2006). "Consistent observation grouping for generating metric-topological maps that improves robot localization". IEEE International Conference on Robotics and Automation (ICRA). pp. 818–823. CiteSeerX 10.1.1.127.3097. doi:10.1109/ROBOT.2006.1641810.
  2. A. Harris; J.M. Conrad (March 2011). "Survey of popular robotics simulators, frameworks, and toolkits". Proceedings of IEEE Southeastcon. pp. 243–249. doi:10.1109/SECON.2011.5752942.
  3. Ryde, J.; Hu, H. (2010). "3D mapping with multi-resolution occupied voxel lists". Autonomous Robots. Springer. 28 (2): 169–185. CiteSeerX 10.1.1.153.5916. doi:10.1007/s10514-009-9158-3.
  4. Tuza, Z. and Rudan, J. and Szederkényi, G (Oct 2010). "Developing an integrated software environment for mobile robot navigation and control". International Conference on Indoor Positioning and Indoor Navigation. pp. 1–6. doi:10.1109/IPIN.2010.5647506.CS1 maint: multiple names: authors list (link)
  5. A list of scientific papers in which MRPT has been used for producing the results.
  6. MRPT.ORG (2013-10-08). "List of MRPT libraries". Retrieved 2014-04-19.
  7. GSOC (2018-08-07). "MRPT page in GSOC 2016". Retrieved 2018-08-07.
  8. GSOC (2018-08-07). "MRPT page in GSOC 2017". Retrieved 2018-08-07.


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