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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/2010-11-29_rtslam_grande-salle_q25.avi|Demo 1]] (v.a, 1'33, 23Mo): hand held alone camera at 60 fps indoor, with several loop closures. * [[http://homepages.laas.fr/croussil/videos/2011-02-15_rtslam-inertial-high-dyn.avi|Demo 2]] (v.b, 1'06, 20Mo): hand held IMU+camera at 50 fps indoor, with very high dynamic. |
* [[http://homepages.laas.fr/croussil/videos/2010-11-29_rtslam_grande-salle_q25.avi|Demo 1]] (v.a, 1'33, 23Mo, H264 AVI): hand held alone camera at 60 fps indoor, with several loop closures. * [[http://homepages.laas.fr/croussil/videos/2011-02-15_rtslam-inertial-high-dyn.avi|Demo 2]] (v.b, 1'06, 20Mo, H264 AVI): hand held IMU+camera at 50 fps indoor, with very high dynamic. * [[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]] == Papers == * __RT-SLAM: A Generic and Real-Time Visual SLAM Implementation__. Cyril Roussillon, Aurélien Gonzalez, Joan Solà, Jean-Marie Codol, Nicolas Mansard, Simon Lacroix, and Michel Devy. ICVS 2011, volume 6962 of Lecture Notes in Computer Science, page 31-40. Springer. [[http://homepages.laas.fr/croussil/publications/2011_ICVS_rtslam.pdf|Download PDF]] |
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| * Inertial Slam |
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.
Documentation
Screenshots and videos
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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)
Papers
RT-SLAM: A Generic and Real-Time Visual SLAM Implementation. Cyril Roussillon, Aurélien Gonzalez, Joan Solà, Jean-Marie Codol, Nicolas Mansard, Simon Lacroix, and Michel Devy. ICVS 2011, volume 6962 of Lecture Notes in Computer Science, page 31-40. Springer. Download PDF
Roadmap
- Stabilize and make a release
- Odometry Slam
- Multimap Slam
- Segments Slam