Differences between revisions 16 and 20 (spanning 4 versions)

RT-SLAM

RT-SLAM stands for Real Time SLAM (Simultaneous Localization And Mapping).

Presentation

RT-SLAM is a fast Slam library and test framework based on EKF. Its main qualities are:

genericity: for sensor models, landmark types, landmark models, landmarks reparametrization, biases estimation;
speed: real time at 60 fps (VGA, gray level) on a decent machine (at least one Core2 core at 2.2GHz)
flexibility: different estimation/image processing sequencing strategies (active search), independent base brick for a hierarchical multimap and multirobots architecture;
robustness: near-optimal repartition of landmarks, data association errors detection (gating, ransac);
developer-friendly: visualization tools (2D and 3D), offline replay step by step, logs, simulation.
open source: in C++ for Linux and MacOS

For now it provides:

Landmarks: Anchored Homogeneous Points (Inverse Depth) that can be reparametrized into Euclidean Points;
Sensors: Pinhole cameras;
Prediction: Constant velocity model, inertial sensor;
Data association: Active search, 1-point Ransac, and mixed strategies.

3D view

2D view

Demo 1 (v.a, 1'33, 23Mo, H264 AVI): hand held alone camera at 60 fps indoor, with several loop closures.
Demo 2 (v.b, 1'06, 20Mo, H264 AVI): hand held IMU+camera at 50 fps indoor, with very high dynamic.
Demo 3 (v.a, 1'25, 27Mo, H264 AVI): IMU+camera on a rover robot on grass, with short term memory (lost landmarks are removed, no loop closure)
Additional videos referenced in papers

-  ⇤ ← Revision 16 as of 2011-02-25 17:00:17 → 
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-<!> '''Disclaimer:''' RT-SLAM is currently in development and has no official release. It is provided as-is, there is no standalone installation, and it is generally not advised (yet) to people who do not want to get their hands dirty.
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- * '''speed''': real time at 60 fps, VGA, gray level;
+ * '''speed''': real time at 60 fps (VGA, gray level) on a decent machine (at least one Core2 core at 2.2GHz)
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+ * '''open source''': in C++ for Linux and MacOS
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- * '''Prediction''': Constant velocity model;
+ * '''Prediction''': Constant velocity model, inertial sensor;
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+ * [[http://homepages.laas.fr/croussil/videos/2011-06-09_rtslam-inertial-robot-grass.avi|Demo 3]] (v.a, 1'25, 27Mo, H264 AVI): IMU+camera on a rover robot on grass, with short term memory (lost landmarks are removed, no loop closure)
 * [[/Material|Additional videos referenced in papers]]
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- * Inertial Slam