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71 public repositories
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A Robust and Versatile Monocular Visual-Inertial State Estimator
Track Advancement of SLAM 跟踪SLAM前沿动态【2020 version】
Monocular Visual-Inertial State Estimator on Mobile Phones
Visual Inertial Odometry with SLAM capabilities and 3D Mesh generation.
A small c++11 header-only library for Lie theory.
Convenient Power System Modelling and Analysis based on PYPOWER and pandas
Updated
Aug 19, 2020
Python
Updated
Aug 5, 2020
Python
(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping
Fusing GPS, IMU and Encoder sensors for accurate state estimation.
Unscented Kalman Filter library for state and parameter estimation
Data Assimilation with Python: a Package for Experimental Research (DAPPER)
Updated
Aug 14, 2020
Python
Resources on various topics being worked on at IvLabs
SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)
SEROW Framework for Humanoid Robot Walking Estimation
Vehicle State Estimation using Error-State Extended Kalman Filter
Updated
Aug 16, 2019
Python
Course on data assimilation (DA)
Updated
Aug 7, 2020
Jupyter Notebook
state estimation for slam
Simple particle/kalman filtering, smoothing and parameter estimation
Updated
May 25, 2020
Julia
Unscented kalman filter (UKF) library in python that supports multiple measurement updates
Updated
Aug 9, 2017
Python
Software Release for "Incremental Covariance Estimation for Robust Localization"
Updated
Apr 29, 2020
Shell
Tubex is a library providing tools for constraint programming over reals and trajectories.
Kalman Filter for Pose estimation using Lie Algebra
A Kalman Filter library in go. Includes several examples in statistical orbit determination.
The Simultaneous Trajectory Estimation and Mapping (STEAM) Engine.
MATGRID is an easy-to-use power system simulation tool for researchers and educators provided as a MATLAB package.
Updated
Apr 22, 2019
MATLAB
RINS-W: Robust Inertial Navigation System on Wheels
Updated
Aug 8, 2020
Python
Software release for "Enabling Robust State Estimation through Measurement Error Covariance Adaptation"
Updated
Oct 11, 2019
Shell
Scripted a state estimator for a quadrotor in C++, incorporating a sensor fusion (IMU, GPS, Magnetometer) environment using the EFK and MCL algorithms
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Rather than hard yes or no on DEV MASTERS when running Travis for release/v0.x branches, perhaps there is a way to do a conditional allow_failure setup where stable releases are still tested against upsteam masters, but a failure is allowed.
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