xivo
rtabmap
| xivo | rtabmap | |
|---|---|---|
| 2 | 14 | |
| 828 | 2,513 | |
| 0.0% | 2.9% | |
| 0.0 | 9.1 | |
| about 1 year ago | 6 days ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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xivo
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Unsupervised Depth Completion from Visual Inertial Odometry
Hey there, interested in camera and range sensor fusion for point cloud (depth) completion?
Here is an extended version of our [talk](https://www.youtube.com/watch?v=oBCKO4TH5y0) at ICRA 2020 where we do a step by step walkthrough of our paper Unsupervised Depth Completion from Visual Inertial Odometry (joint work with Fei Xiaohan, Stephanie Tsuei, and Stefano Soatto).
In this talk, we present an unsupervised method (no need for human supervision/annotations) for learning to recover dense point clouds from images, captured by cameras, and sparse point clouds, produced by lidar or tracked by visual inertial odometry (VIO) systems. To illustrate what I mean, here is an [example](https://github.com/alexklwong/unsupervised-depth-completion-visual-inertial-odometry/blob/master/figures/void_teaser.gif?raw=true) of the point clouds produced by our method.
Our method is light-weight (so you can run it on your computer!) and is built on top of [XIVO] (https://github.com/ucla-vision/xivo) our VIO system.
For those interested here are links to the [paper](https://arxiv.org/pdf/1905.08616.pdf), [code](https://github.com/alexklwong/unsupervised-depth-completion-visual-inertial-odometry) and the [dataset](https://github.com/alexklwong/void-dataset) we collected.
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[N][R] ICRA 2020 extended talk for Unsupervised Depth Completion from Visual Inertial Odometry
Our method is light-weight (so you can run it on your computer!) and is built on top of XIVO our VIO system.
rtabmap
- Generating a 3D point cloud map (simulation)
- Ros2 and native dependecies
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Lidar 3D Mapping Recommendations
I used RTAB Map for my masterthesis as well. You have to use the cloud topics and disable all scan parameters. There is a masterfile with 800 lines of parameters that should help you out. https://github.com/introlab/rtabmap/blob/master/corelib/include/rtabmap/core/Parameters.h
- What's the most odd thing you've got running on your steam deck?
- RTAB-Maap
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ROS: Simultaneous Mapping and Localization with RTABmap
RTABmap project homepage
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Software to process Kinect Xbox Data to point cloud
Website: http://introlab.github.io/rtabmap/
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How to reduce points in VSLAM to 3D meshes? Has it been done before?
I'd suggest RTABMAP.
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Need some help with SLAM and mapping with LIDAR
For your application rtabmap would be a good starting point I think. (You don't really need ROS either for rtabmap) http://introlab.github.io/rtabmap/
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Lidar and Stereo Vision for Biped
check out http://introlab.github.io/rtabmap/ and https://opensource.google/projects/cartographer and https://docs.nvidia.com/isaac/isaac/doc/tutorials/assemble\_kaya.html
What are some alternatives?
open_vins - An open source platform for visual-inertial navigation research.
cartographer - Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
openvslam - OpenVSLAM: A Versatile Visual SLAM Framework
void-dataset - Visual Odometry with Inertial and Depth (VOID) dataset
r3live - A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
SuperPoint_SLAM - SuperPoint + ORB_SLAM2
Open3D - Open3D: A Modern Library for 3D Data Processing
PythonRobotics - Python sample codes for robotics algorithms.
v-loam