dfjimu 0.2.1

Drift-free IMU-based joint kinematics estimation (Weygers & Kok, 2020)

Drift-Free Joint Kinematics from Dual IMUs

High-performance Python/Cython implementation of the drift-free joint kinematics estimation method from Weygers & Kok (2020), "Drift-Free Inertial Sensor-Based Joint Kinematics for Long-Term Arbitrary Movements".

Two algorithms are provided:

• MEKF-acc — online Multiplicative Extended Kalman Filter
• MAP-acc — offline Gauss-Newton optimizer for higher accuracy

Installation

Pre-built wheels with the fast Cython backend are available for Linux, macOS, and Windows (Python 3.10+):

pip install dfjimu

When installing from the source distribution (no matching wheel), a C compiler is required for the Cython extension. If compilation fails, the package falls back to a pure Python backend automatically.

Usage

from dfjimu import mekf_acc, map_acc

# MEKF-acc — lever arms r1, r2 are auto-estimated when omitted
q1, q2 = mekf_acc(gyr1, gyr2, acc1, acc2, Fs=Fs, q_init=q_init)

# Or provide lever arms explicitly
q1, q2 = mekf_acc(gyr1, gyr2, acc1, acc2, r1, r2, Fs, q_init)

# MAP-acc (optimization-based smoothing)
q1, q2 = map_acc(gyr1, gyr2, acc1, acc2, Fs=Fs, q_init=q_init,
                 cov_w=cov_w, cov_i=cov_i, cov_lnk=cov_lnk)

See examples/demo.ipynb for a full walkthrough with plots.

API

Function	Description
mekf_acc() / MekfAcc	MEKF-acc filter (online)
map_acc() / MapAcc	MAP-acc optimizer (offline, higher accuracy)
estimate_lever_arms()	Lever arm estimation from dual-IMU data

Both mekf_acc and map_acc accept optional r1, r2 lever arm vectors. When omitted (None), they are auto-estimated via estimate_lever_arms().

Development

# Install in editable mode with dev tools
pip install -e ".[dev]"

# Build Cython extensions in-place
python setup.py build_ext --inplace

# Run tests
pytest tests/

# Install with Jupyter and matplotlib for the example notebook
pip install -e ".[examples]"

Benchmarks

Evaluate accuracy and speed of the solvers across all datasets:

python tests/evaluate_package.py

Reference

Weygers, I., & Kok, M. (2020). Drift-Free Inertial Sensor-Based Joint Kinematics for Long-Term Arbitrary Movements. IEEE Sensors Journal, 20(14), 7969-7979.