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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, there is some code to adapt for your own use, and it is generally not advised (yet) to people who do not want to get their hands dirty. | |
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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, there is some code to adapt for your own use, and it is generally not advised (yet) to people who do not want to get their hands dirty. | |
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| * '''genericity''': sensor models, landmark types, landmark models, reparametrization from one landmark model to another one, estimating biases; | * '''genericity''': for sensor models, landmark types, landmark models, landmarks reparametrization, biases estimation; |
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| * '''flexibility''': different estimation/image processing sequencing (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. |
* '''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. |
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| * Anchored Homogeneous Points (Inverse Depth) that can be reparametrized into Euclidean Points * Pinhole cameras * Constant Velocity prediction model * Active search and 1-point Ransac for data association |
* '''Landmarks''': Anchored Homogeneous Points (Inverse Depth) that can be reparametrized into Euclidean Points; * '''Sensors''': Pinhole cameras; * '''Prediction''': Constant velocity model; * '''Data association''': Active search, 1-point Ransac, and mixed strategies. |
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| {{attachment:rtslam.png|RT-SLAM screen|width=800}} | |
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| * Inertial and Odometry Slam | * Inertial Slam * Odometry Slam |
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| * Segment Slam | * Segments Slam |
RT-SLAM
RT-SLAM stands for Real Time SLAM (Simultaneous Localization And Mapping).
Disclaimer: RT-SLAM is currently in development and has no official release. It is provided as-is, there is no standalone installation, there is some code to adapt for your own use, and it is generally not advised (yet) to people who do not want to get their hands dirty.
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;
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.
For now it provides:
Landmarks: Anchored Homogeneous Points (Inverse Depth) that can be reparametrized into Euclidean Points;
Sensors: Pinhole cameras;
Prediction: Constant velocity model;
Data association: Active search, 1-point Ransac, and mixed strategies.
Documentation
Screenshots and videos
Roadmap
- Stabilize and make a release
- Inertial Slam
- Odometry Slam
- Multimap Slam
- Segments Slam