Rovio
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Research | 3,896 | 4 years ago | 32 | bsd-3-clause | Python | |||||
| dataset and code for 2016 paper "Learning a Driving Simulator" | ||||||||||
| Dso | 2,039 | 6 months ago | 130 | gpl-3.0 | C++ | |||||
| Direct Sparse Odometry | ||||||||||
| Objectron | 1,958 | a year ago | 21 | other | Jupyter Notebook | |||||
| Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes | ||||||||||
| Ml Hypersim | 1,419 | 4 months ago | other | Python | ||||||
| Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding | ||||||||||
| Pykitti | 889 | 4 | a year ago | 9 | March 01, 2019 | 21 | mit | Python | ||
| Python tools for working with KITTI data. | ||||||||||
| Rovio | 871 | 2 years ago | 82 | other | C++ | |||||
| Awesome Reid Dataset | 793 | a month ago | 12 | |||||||
| Collection of public available person re-identification datasets | ||||||||||
| Gslam | 593 | 3 years ago | 17 | bsd-2-clause | C++ | |||||
| A General Simultaneous Localization and Mapping Framework which supports feature based or direct method and different sensors including monocular camera, RGB-D sensors or any other input types can be handled. | ||||||||||
| Vdo_slam | 568 | 4 months ago | 20 | other | C++ | |||||
| VDO-SLAM: A Visual Dynamic Object-aware SLAM System | ||||||||||
| Woodscape | 515 | a month ago | 55 | Python | ||||||
| The repository containing tools and information about the WoodScape dataset. | ||||||||||
README
This repository contains the ROVIO (Robust Visual Inertial Odometry) framework. The code is open-source (BSD License). Please remember that it is strongly coupled to on-going research and thus some parts are not fully mature yet. Furthermore, the code will also be subject to changes in the future which could include greater re-factoring of some parts.
Video: https://youtu.be/ZMAISVy-6ao
Papers:
- http://dx.doi.org/10.3929/ethz-a-010566547 (IROS 2015)
- http://dx.doi.org/10.1177/0278364917728574 (IJRR 2017)
Please also have a look at the wiki: https://github.com/ethz-asl/rovio/wiki
Install without opengl scene
Dependencies:
- ros
- kindr (ethz-asl/kindr)
- lightweight_filtering (as submodule, use "git submodule update --init --recursive")
#!command
catkin build rovio --cmake-args -DCMAKE_BUILD_TYPE=Release
Install with opengl scene
Additional dependencies: opengl, glut, glew (sudo apt-get install freeglut3-dev, sudo apt-get install libglew-dev)
#!command
catkin build rovio --cmake-args -DCMAKE_BUILD_TYPE=Release -DMAKE_SCENE=ON
Euroc Datasets
The rovio_node.launch file loads parameters such that ROVIO runs properly on the Euroc datasets. The datasets are available under: http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets
Further notes
- Camera matrix and distortion parameters should be provided by a yaml file or loaded through rosparam
- The cfg/rovio.info provides most parameters for rovio. The camera extrinsics qCM (quaternion from IMU to camera frame, Hamilton-convention) and MrMC (Translation between IMU and Camera expressed in the IMU frame) should also be set there. They are being estimated during runtime so only a rough guess should be sufficient.
- Especially for application with little motion fixing the IMU-camera extrinsics can be beneficial. This can be done by setting the parameter doVECalibration to false. Please be carefull that the overall robustness and accuracy can be very sensitive to bad extrinsic calibrations.
