ORB_SLAM3
SuperGluePretrainedNetwork
| ORB_SLAM3 | SuperGluePretrainedNetwork | |
|---|---|---|
| 15 | 5 | |
| 6,031 | 3,036 | |
| 2.4% | 4.3% | |
| 0.0 | 0.0 | |
| 21 days ago | over 1 year ago | |
| C++ | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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ORB_SLAM3
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How to make bot that can navigate to instructed positions in a 3d world using only rgb images
Thank you for the recommendation. Other's I've talked to have also mentioned slam. I think I might use this repo that looks promising: https://github.com/UZ-SLAMLab/ORB_SLAM3
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Bot that can navigate to instructed positions in a 3d world
https://github.com/UZ-SLAMLab/ORB_SLAM3 looks promising. Thank you for the recommendation!
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Any links/tutorials on how to integrate a mono cam with ros noetic for slam?
ORB_SLAM3 on GitHub: https://github.com/UZ-SLAMLab/ORB_SLAM3
- How to implement SLAM from scratch in C++
- ORB-SLAM3 memory leak
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Wiring in progress
Yeah pretty much. I'd say it can still be useful if your custom application only needs one or two new modules and can otherwise be formed from existing code. It's great if you make a lot of different systems with similar sub-modules. The bigger research institutions also open source a lot of their code with ROS integrations, so you can just drop in state of the art modules where appropriate. e.g. OrbSlam3,
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Doing SLAM with laptop sensors
You could try your luck with OrbSLAM3 or Kimera, they're pretty close to state of the art and open source. Might have a bit of a learning curve though.
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What's the current SOTA for vSLAM?
I hear good things about stereo-visual + inertial and OrbSlam3 seems pretty hot, but this is a couple years old now and I'm not active enough in the field to give a definitive opinion.
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Advice regarding software for indoor autonomous MAV/drone
I'm currently in the planning stage of building an indoor autonomous MAV/drone. Up until this point I thought this would require a SLAM solution, such as ORB-SLAM3, but now I see this framework by Intel which doesn't mention SLAM anywhere. All of the literature seems to be about SLAM so maybe I just don't know the terminology for what I'm looking for.
- Software advice for inside-out cave mapping
SuperGluePretrainedNetwork
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SuperGlue is a CVPR2022 research project done at Magicleap for pose estimation in real-world environments. Check out the tool link in the comments
Code: https://github.com/magicleap/SuperGluePretrainedNetwork
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Advances in SLAM since 2016
This basically includes a deep learning based approach to do keypoint detection, and match them across image frames. This includes papers like SuperPoint, Superglue, and more. There is also a way to do dense matching with neural networks.
- [D] Solo machine learning engineer woes
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How to train a CNN for a map localization task?
Feature matching is the way to go imo. Try out OpenCV's inbuilt feature matching methods like SIFT and FLANN. If the performance is poor, you can even try out CNN aided matching algos like SuperGlue Link (CVPR2020)
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What is the SOTA for feature extraction / description / matching ?
SIFT and brute force matching is your best bet in classical computer vision if you're unconcerned with runtime. There are methods from deep learning that can perform better, somewhat domain dependent. Check out superpoint and superglue from magic leap. https://github.com/magicleap/SuperGluePretrainedNetwork
What are some alternatives?
openvslam - OpenVSLAM: A Versatile Visual SLAM Framework
LoFTR - Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022
open_vins - An open source platform for visual-inertial navigation research.
nerfmm - (Arxiv 2021) NeRF--: Neural Radiance Fields Without Known Camera Parameters
Udacity-self-driving-car-engineer-P6-Kidnapped-Vehicle - 优达学城无人驾驶工程师纳米学位P6--被绑架的汽车--定位
dgl - Python package built to ease deep learning on graph, on top of existing DL frameworks.
VINS-Mono - A Robust and Versatile Monocular Visual-Inertial State Estimator
torchdrug - A powerful and flexible machine learning platform for drug discovery
vortex-auv - Software for guidance, navigation and control for the Vortex AUVs. Purpose built for competing in AUV/ROV competitions.
DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
Kalman-and-Bayesian-Filters-in-Python - Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.