Merge branch 'update_docs' into 'master'
Update documentation. See merge request basalt/basalt!29
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@ -56,8 +56,8 @@ make -j8
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NOTE: It is possible to compile the code on Ubuntu 16.04, but you need to install cmake-3.10 or higher and gcc-7. See corresponding [Dockerfile](docker/b_image_xenial/Dockerfile) as an example.
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## Usage
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* [Camera, IMU and Mocap calibration.](doc/Calibration.md)
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* [Visual-inertial odometry and mapping.](doc/VioMapping.md)
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* [Camera, IMU and Mocap calibration. (TUM-VI, Euroc and UZH-FPV datasets)](doc/Calibration.md)
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* [Visual-inertial odometry and mapping. (TUM-VI and Euroc datasets)](doc/VioMapping.md)
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* [Simulation tools to test different components of the system.](doc/Simulation.md)
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## Development
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@ -1,6 +1,6 @@
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# Calibration
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Here, we explain how to use the calibration tools with [TUM-VI](https://vision.in.tum.de/data/datasets/visual-inertial-dataset) and [EuRoC](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) datasets as an example.
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Here, we explain how to use the calibration tools with [TUM-VI](https://vision.in.tum.de/data/datasets/visual-inertial-dataset), [EuRoC](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) and [UZH-FPV](http://rpg.ifi.uzh.ch/uzh-fpv.html) datasets as an example.
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## TUM-VI dataset
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* `--dataset-type` type of the datset. Currently only `bag` and `euroc` formats of the datasets are supported.
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* `--result-path` path to the folder where the resulting calibration and intermediate results will be stored.
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* `--aprilgrid` path to the configuration file for the aprilgrid.
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* `--cam-types` camera models for the image streams in the dataset. For more detais see [arXiv:1807.08957](https://arxiv.org/abs/1807.08957).
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* `--cam-types` camera models for the image streams in the dataset. For more details see [arXiv:1807.08957](https://arxiv.org/abs/1807.08957).
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After that, you should see the calibration GUI:
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![tumvi_cam_calib](/doc/img/tumvi_cam_calib.png)
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* `init_cam_poses` computes an initial guess for camera poses given the current intrinsics.
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* `init_cam_extr` computes an initial transformation between the cameras.
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* `init_opt` initializes optimization and shows the projected points given the current calibration and camera poses.
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* `optimize` runs an iteration of the optimization and visualizes the result. You should press this button until the error printed in the console output stops decreasing and the optimization converges.
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* `optimize` runs an iteration of the optimization and visualizes the result. You should press this button until the error printed in the console output stops decreasing and the optimization converges. Alternatively, you can use the `opt_until_converge` checkbox that will run the optimization until it converges automatically.
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* `save_calib` saves the current calibration as `calibration.json` in the result folder.
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* `compute_vign` **(Experimental)** computes a radially-symmetric vignetting for the cameras. For the algorithm to work, **the calibration pattern should be static (camera moving around it) and have a constant lighting throughout the calibration sequence**. If you run `compute_vign` you should press `save_calib` afterwards. The png images with vignetting will also be stored in the result folder.
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* `show_ids` toggles the ID visualization for every point.
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* `huber_thresh` controls the threshold for the huber norm in pixels for the optimization.
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* `opt_intr` controls if the optimization can change the intrinsics. For some datasets it might be helpful to disable this option for several first iterations of the optimization.
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* `opt_until_convg` runs the optimization until convergence.
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* `opt_until_converge` runs the optimization until convergence.
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* `stop_thresh` defines the stopping criteria. Optimization will stop when the maximum increment is smaller than this value.
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* `load_dataset`, `detect_corners`, `init_cam_poses` same as above.
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* `init_cam_imu` initializes the rotation between camera and IMU by aligning rotation velocities of the camera to the gyro data.
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* `init_opt` initializes the optimization. Shows reprojected corners in magenta and the estimated values from the spline as solid lines below.
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* `optimize` runs an iteration of the optimization. You should press it several times until convergence before proceeding to next steps.
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* `optimize` runs an iteration of the optimization. You should press it several times until convergence before proceeding to next steps. Alternatively, you can use the `opt_until_converge` checkbox that will run the optimization until it converges automatically.
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* `init_mocap` initializes the transformation from the Aprilgrid calibration pattern to the Mocap coordinate system.
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* `save_calib` save the current calibration as `calibration.json` in the result folder.
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* `save_mocap_calib` save the current Mocap to IMU calibration as `mocap_calibration.json` in the result folder.
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basalt_calibrate_imu --dataset-path ~/euroc_calib_data/imu_april.bag --dataset-type bag --aprilgrid /usr/etc/basalt/aprilgrid_6x6.json --result-path ~/euroc_calib_result/ --gyro-noise-std 0.000282 --accel-noise-std 0.016 --gyro-bias-std 0.0001 --accel-bias-std 0.001
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```
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![euroc_imu_calib](/doc/img/euroc_imu_calib.png)
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## UZH dataset
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Download the datasets for camera and camera-IMU calibration:
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```
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mkdir ~/uzh_calib_data
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cd ~/uzh_calib_data
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wget http://rpg.ifi.uzh.ch/datasets/uzh-fpv/calib/indoor_forward_calib_snapdragon_cam.bag
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wget http://rpg.ifi.uzh.ch/datasets/uzh-fpv/calib/indoor_forward_calib_snapdragon_imu.bag
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```
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### Camera calibration
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Run the camera calibration:
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```
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basalt_calibrate --dataset-path ~/uzh_calib_data/indoor_forward_calib_snapdragon_cam.bag --dataset-type bag --aprilgrid /usr/etc/basalt/aprilgrid_5x4_uzh.json --result-path ~/uzh_calib_result/ --cam-types ds ds
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```
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![uzh_cam_calib](/doc/img/uzh_cam_calib.png)
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### Camera + IMU calibration
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After calibrating the camera you can run the camera + IMU calibration. The result-path should point to the same folder as before:
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```
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basalt_calibrate_imu --dataset-path ~/uzh_calib_data/indoor_forward_calib_snapdragon_imu.bag --dataset-type bag --aprilgrid /usr/etc/basalt/aprilgrid_5x4_uzh.json --result-path ~/uzh_calib_result/ --gyro-noise-std 0.05 --accel-noise-std 0.1 --gyro-bias-std 4e-5 --accel-bias-std 0.002
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```
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![uzh_imu_calib](/doc/img/uzh_imu_calib.png)
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brew install clang-format
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```
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### Realsense Drivers (Optional)
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If you want to use the code with Realsense T265 cameras you should install the realsense library.
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On **Ubuntu 18.04** run the following commands:
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```
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sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-key C8B3A55A6F3EFCDE
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sudo sh -c 'echo "deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo bionic main" > /etc/apt/sources.list.d/realsense.list'
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sudo apt-get update
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sudo apt-get install librealsense2-dev librealsense2-gl-dev librealsense2-dkms librealsense2-utils librealsense2-dkms
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```
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On **MacOS** run:
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```
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brew install librealsense
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```
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### Install and configure QtCreator
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Download and install QtCreator. On **Ubuntu 18.04** run:
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```
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wget https://download.qt.io/official_releases/qtcreator/4.9/4.9.0/qt-creator-opensource-linux-x86_64-4.9.0.run
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chmod +x qt-creator-opensource-linux-x86_64-4.9.0.run
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./qt-creator-opensource-linux-x86_64-4.9.0.run
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wget https://download.qt.io/official_releases/qtcreator/4.9/4.9.2/qt-creator-opensource-linux-x86_64-4.9.2.run
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chmod +x qt-creator-opensource-linux-x86_64-4.9.2.run
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./qt-creator-opensource-linux-x86_64-4.9.2.run
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```
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On **MacOS** run:
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