Graph SLAM solver in Python
Project description
Documentation for this package can be found at https://python-graphslam.readthedocs.io/.
This package implements a Graph SLAM solver in Python.
Features
Optimize R^2, R^3, and SE(2) datasets
Analytic Jacobians
Supports odometry edges
Load SE(2) datasets from .g2o files
Planned Features
Optimize SE(3) datasets
Load SE(3) datasets from .g2o files
Installation
pip install graphslam
Example Usage
>>> from graphslam.load import load_g2o_se2
>>> g = load_g2o_se2("input_INTEL_g2o")
>>> g.calc_chi2()
10140102.260977369
>>> g.optimize()
Iteration 1: chi2_prev = 10140102.2610, self._chi2 = 20807915286.0808
Iteration 2: chi2_prev = 20807915286.0808, self._chi2 = 17138938.1459
Iteration 3: chi2_prev = 17138938.1459, self._chi2 = 8449141792.5765
Iteration 4: chi2_prev = 8449141792.5765, self._chi2 = 227464854.3710
Iteration 5: chi2_prev = 227464854.3710, self._chi2 = 24133028.4628
Iteration 6: chi2_prev = 24133028.4628, self._chi2 = 1971385.3240
Iteration 7: chi2_prev = 1971385.3240, self._chi2 = 3381916.5105
Iteration 8: chi2_prev = 3381916.5105, self._chi2 = 772245.1031
Iteration 9: chi2_prev = 772245.1031, self._chi2 = 453384.0468
Iteration 10: chi2_prev = 453384.0468, self._chi2 = 182479.5075
Iteration 11: chi2_prev = 182479.5075, self._chi2 = 172322.2547
Iteration 12: chi2_prev = 172322.2547, self._chi2 = 157810.0204
Iteration 13: chi2_prev = 157810.0204, self._chi2 = 158375.4994
Iteration 14: chi2_prev = 158375.4994, self._chi2 = 157012.2347
Iteration 15: chi2_prev = 157012.2347, self._chi2 = 156990.8030
Iteration 16: chi2_prev = 156990.8030, self._chi2 = 156860.7980
Iteration 17: chi2_prev = 156860.7980, self._chi2 = 156856.9133
References and Links
Live Coding Graph SLAM in Python
If you’re interested, you can watch as I coded this up.
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